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Heavy is the head that wears the crown during a Wall Street bull run, and Nvidia’s status as the king of the ongoing generative AI boom means that the stock can be especially vulnerable to the prospect of weakening investor appetite. Nvidia (NASDAQ:NVDA) became Wall Street’s most exciting story in 2023. The chipmaker rallied some 239% throughout the year, smashing through the $1 trillion market capitalization glass ceiling before peaking at a cap in excess of $2tn. The optimism, fuelled by the ongoing generative AI market rally, continued to make waves in the first-quarter of 2024. NVDA rallied almost 90% in the opening three months of the year to continue its strong spell of dominance. But finally, at the beginning of April, the stock took its biggest tumble in four years. The wider implications of the Nvidia sell-off are likely to shake up the entire generative AI market. Counting the Cost of NVDA Sell-Offs The first three weeks of April 2024 saw NVDA shed more than 15% of its value amid widespread investor sell-offs. Although greater degrees of volatility can be expected for stocks caught up in the hype phase of an emerging market, Nvidia’s April downturn has been the company’s biggest dip since the initial outbreak of the Covid-19 pandemic in March 2020. For Nvidia, the pandemic era must seem like a lifetime ago. Its March 2020 sell-offs saw the stock tumble to $51.44. The stock’s peak closing price in March 2024 was $950.02. But after four years of meteoric growth, Nvidia’s recent market downturn is particularly concerning–particularly now the stock’s gained the status as a tech pioneer that’s been driving the S&P 500 higher on a consistent basis. Nvidia’s position at the pinnacle of the generative AI boom could mean that the stock would always be the first to absorb the impact of a change in investor sentiment, and the fears are that NVDA would be the canary in the mine should we suddenly discover that generative AI has been in a hype bubble that’s ready to burst for some time. Although Nvidia’s recent difficulties have coincided with the news that US inflation rates have continued to defy expectations, placing the prospect of interest rate cuts on hold for the foreseeable future, analysts suggest that fears over a cooling generative AI boom remain the key cause of investor concern in the wake of the underperformance. “The stock pullback has very little to do with rates,” explained Parag Thatte, strategist at Deutsche Bank, in a recent Financial Times interview. “It’s more to do with investors pricing in slower earnings growth.” There’s also a growing concern that generative AI has begun to transform from its hype phase towards the question of implementation. While Large Language Models (LLMs) like ChatGPT have been excellent tools in showcasing the sheer power and potential of generative AI, they’ve also been largely error-prone in a manner that could cause more hesitancy among enterprises seeking to embrace the technology. It’s for this reason that Gil Luria, analyst at DA Davidson, warned that a 20% slide in Nvidia stock could take place by the end of 2024. Luria suggests that the implementation phase of Nvidia’s products, which are currently being bought en masse by the likes of Microsoft and Amazon, could run into trouble when key buyers reach capacity and demand begins to fall. However, other analysts suggest that the end of the generative AI hype phase will be met by a more strategic implementation phase which could keep the industry growing. “Concerns about GenAI failing to meet expectations in 2024 should be seen in the context of the natural cycle of hype and maturity of new technologies,” said Maxim Manturov, head of investment research at Freedom Finance Europe. “While some industry leaders have expressed frustration with the speed of progress in artificial intelligence and GenAI in their organisations, others remain optimistic about its potential.” “Companies heavily invested in GenAI are under pressure to prove profitability, and industry reports indicate a shift to more strategic AI initiatives in the coming years,” Manturov added. Is the Generative AI an Exceptional Case? Here, it’s worth reminding ourselves that we’re talking about the generative AI boom. This is an industry that Bloomberg Intelligence last year suggested would grow at a CAGR of 42% into a $1.3 trillion industry by 2032. Fresh demand for generative AI products was predicted to add around $280 million in new software revenue. Could we be talking about an emerging technology that’s market impact is without precedent? Morgan Stanley analysts have underlined the indecisive outlook for Nvidia and the wider generative AI market in Q2 2024 by proposing a more bullish outlook for NVDA as well as the generative AI-focused Amazon (AMZN). As Nvidia reported Q4 2023 revenue increases of 265% to $22 billion, CEO Jensen Huang claimed that "accelerated computing and generative AI have hit the tipping point," before adding that "demand is surging worldwide across companies, industries and nations." The company’s innovations in recent weeks have included the text-to-3D tool, LATTE3D, which Nvidia described as a ‘virtual 3D printer’, as well as a collaboration with Hipocratic AI to develop a network of generative AI nurses that could cost $9 an hour. Nvidia’s quick 5% rebound following its record sell-offs should serve as a wider vote of confidence in the innovation that the company is capable of. Regardless of whether its success has made it the GenAI canary, NVDA is certainly an innovative stock that’s capable of sustaining its impressive growth. Bubble or Boom? Ultimately, Nvidia’s performance over the past 12 months means that the stock has become a live litmus test for investor sentiment in generative AI. Whether that’s a good thing or not depends wholly on the capabilities of the industry itself. Nvidia’s rapid growth has seen the stock rub shoulders with the likes of Microsoft, Apple, and Alphabet, and the company will be keen to follow the lead of other industry giants to continue sustaining its growth through innovation. As a semiconductor leader, the possibilities are nearly endless for Nvidia. As long as the capabilities of generative AI continue to astound clients and deliver on its promises, NVDA remains a stock that can continue to grow. If investors get a whiff of saturation or inefficiency, the Nvidia litmus test could face some further challenges ahead. Heavy is the head that wears the crown during a Wall Street bull run, and Nvidia’s status as the king of the ongoing generative AI boom means that the stock can be especially vulnerable to the prospect of weakening investor appetite. Nvidia (NASDAQ:NVDA) became Wall Street’s most exciting story in 2023. The chipmaker rallied some 239% throughout the year, smashing through the $1 trillion market capitalization glass ceiling before peaking at a cap in excess of $2tn. Nvidia The optimism, fuelled by the ongoing generative AI market rally, continued to make waves in the first-quarter of 2024. NVDA rallied almost 90% in the opening three months of the year to continue its strong spell of dominance. But finally, at the beginning of April, the stock took its biggest tumble in four years. The wider implications of the Nvidia sell-off are likely to shake up the entire generative AI market. Counting the Cost of NVDA Sell-Offs The first three weeks of April 2024 saw NVDA shed more than 15% of its value amid widespread investor sell-offs. Although greater degrees of volatility can be expected for stocks caught up in the hype phase of an emerging market, Nvidia’s April downturn has been the company’s biggest dip since the initial outbreak of the Covid-19 pandemic in March 2020. For Nvidia, the pandemic era must seem like a lifetime ago. Its March 2020 sell-offs saw the stock tumble to $51.44. The stock’s peak closing price in March 2024 was $950.02. But after four years of meteoric growth, Nvidia’s recent market downturn is particularly concerning–particularly now the stock’s gained the status as a tech pioneer that’s been driving the S&P 500 higher on a consistent basis. Nvidia’s position at the pinnacle of the generative AI boom could mean that the stock would always be the first to absorb the impact of a change in investor sentiment, and the fears are that NVDA would be the canary in the mine should we suddenly discover that generative AI has been in a hype bubble that’s ready to burst for some time. Although Nvidia’s recent difficulties have coincided with the news that US inflation rates have continued to defy expectations, placing the prospect of interest rate cuts on hold for the foreseeable future, analysts suggest that fears over a cooling generative AI boom remain the key cause of investor concern in the wake of the underperformance. prospect of interest rate cuts on hold prospect of interest rate cuts on hold “The stock pullback has very little to do with rates,” explained Parag Thatte , strategist at Deutsche Bank, in a recent Financial Times interview. “It’s more to do with investors pricing in slower earnings growth.” explained Parag Thatte explained Parag Thatte There’s also a growing concern that generative AI has begun to transform from its hype phase towards the question of implementation. While Large Language Models (LLMs) like ChatGPT have been excellent tools in showcasing the sheer power and potential of generative AI, they’ve also been largely error-prone in a manner that could cause more hesitancy among enterprises seeking to embrace the technology. largely error-prone largely error-prone It’s for this reason that Gil Luria, analyst at DA Davidson, warned that a 20% slide in Nvidia stock could take place by the end of 2024. Luria suggests that the implementation phase of Nvidia’s products, which are currently being bought en masse by the likes of Microsoft and Amazon, could run into trouble when key buyers reach capacity and demand begins to fall. 20% slide in Nvidia stock 20% slide in Nvidia stock However, other analysts suggest that the end of the generative AI hype phase will be met by a more strategic implementation phase which could keep the industry growing. “Concerns about GenAI failing to meet expectations in 2024 should be seen in the context of the natural cycle of hype and maturity of new technologies,” said Maxim Manturov, head of investment research at Freedom Finance Europe . “While some industry leaders have expressed frustration with the speed of progress in artificial intelligence and GenAI in their organisations, others remain optimistic about its potential.” Freedom Finance Europe Freedom Finance Europe “Companies heavily invested in GenAI are under pressure to prove profitability, and industry reports indicate a shift to more strategic AI initiatives in the coming years,” Manturov added. Is the Generative AI an Exceptional Case? Here, it’s worth reminding ourselves that we’re talking about the generative AI boom. This is an industry that Bloomberg Intelligence last year suggested would grow at a CAGR of 42% into a $1.3 trillion industry by 2032 . $1.3 trillion industry by 2032 $1.3 trillion industry by 2032 Fresh demand for generative AI products was predicted to add around $280 million in new software revenue. Could we be talking about an emerging technology that’s market impact is without precedent? Morgan Stanley analysts have underlined the indecisive outlook for Nvidia and the wider generative AI market in Q2 2024 by proposing a more bullish outlook for NVDA as well as the generative AI-focused Amazon (AMZN). more bullish outlook more bullish outlook As Nvidia reported Q4 2023 revenue increases of 265% to $22 billion, CEO Jensen Huang claimed that "accelerated computing and generative AI have hit the tipping point," before adding that "demand is surging worldwide across companies, industries and nations." claimed that claimed that The company’s innovations in recent weeks have included the text-to-3D tool , LATTE3D, which Nvidia described as a ‘virtual 3D printer’, as well as a collaboration with Hipocratic AI to develop a network of generative AI nurses that could cost $9 an hour. text-to-3D tool text-to-3D tool collaboration with Hipocratic AI collaboration with Hipocratic AI Nvidia’s quick 5% rebound following its record sell-offs should serve as a wider vote of confidence in the innovation that the company is capable of. Regardless of whether its success has made it the GenAI canary, NVDA is certainly an innovative stock that’s capable of sustaining its impressive growth. Bubble or Boom? Ultimately, Nvidia’s performance over the past 12 months means that the stock has become a live litmus test for investor sentiment in generative AI. Whether that’s a good thing or not depends wholly on the capabilities of the industry itself. Nvidia’s rapid growth has seen the stock rub shoulders with the likes of Microsoft, Apple, and Alphabet, and the company will be keen to follow the lead of other industry giants to continue sustaining its growth through innovation. As a semiconductor leader, the possibilities are nearly endless for Nvidia. As long as the capabilities of generative AI continue to astound clients and deliver on its promises, NVDA remains a stock that can continue to grow. If investors get a whiff of saturation or inefficiency, the Nvidia litmus test could face some further challenges ahead.

Nvidia’s Shaky Q2 Underlines the Stock as Generative AI’s Sentiment Litmus Test

এনভিডিয়ার শ্যাকি Q2 জেনারেটিভ এআই এর সেন্টিমেন্ট লিটমাস টেস্ট হিসাবে স্টককে আন্ডারলাইন করেছে

Nvidias wackeliges zweites Quartal unterstreicht die Aktie als Lackmustest für die Stimmung von Generative AI

El inestable segundo trimestre de Nvidia subraya la acción como prueba de fuego del sentimiento de la IA generativa

Le Shaky Q2 de Nvidia souligne le titre en tant que test décisif du sentiment de Generative AI

एनवीडिया की अस्थिर Q2 स्टॉक को जेनरेटिव एआई के सेंटीमेंट लिटमस टेस्ट के रूप में रेखांकित करती है

エヌビディアの第2四半期の不安定さは、ジェネレーティブAIの感情リトマス試験として株価を浮き彫りにする

Nvidia의 Shaky Q2는 Generative AI의 감정 리트머스 테스트로서 주식을 강조합니다.

Shaky Q2 da Nvidia destaca o estoque como teste decisivo de sentimento da IA generativa

Нестабильный второй квартал Nvidia подчеркивает, что акции являются лакмусовой бумажкой настроений генеративного ИИ

Nvidia'nın Titrek 2. Çeyreği Hisse Senedinin Üretken Yapay Zekanın Duyarlılık Turnusol Testi Olduğunu Vurguluyor

Q2 run rẩy của Nvidia nhấn mạnh cổ phiếu là bài kiểm tra tình cảm của AI sáng tạo

Nvidia 第二季度业绩表现不佳，凸显其股票是生成式 AI 情绪的试金石

is a framework for practising chaos engineering in cloud-native environments. Litmus provides a chaos operator, a large set of chaos experiments on its , detailed , and a friendly community. Litmus Cross-Cloud Chaos Orchestration hub documentation In this blog, we'll take a look at how Litmus Orchestrates Chaos Experiments and the individual components/resource breakdowns to get a perfect step by step understanding of how things happen behind the hood The Basics First Litmus takes a cloud-native approach to create, manage and monitor chaos. Litmus orchestrates Chaos using the following Kubernetes Custom Resources: Primary : This is a low-level definition of the Chaos Experiment itself, in this CR you'd find the different chaos parameters, the libraries used to implement chaos, the permissions associated with the particular experiment as well as some Operational characteristics like if the privileged mode is enabled, the security context of your experiment, etc. The experiment tunables like the , , etc, is already set to a default value with the help of this CR. Chaos Experiment TOTAL_CHAOS_DURATION LIB_IMAGE (The default experiment parameters are pulled from the ChaosHub) : This user-facing CR helps in binding the with the . It defines the Run Policies and also holds the status of your experiment. This CR helps you customize the experiment according to your need since it can override some of the default characteristics/tunables in your experiment CR. This CR reconciles with the Chaos Operator . Chaos Engine application instance ChaosExperiment (We'll get to more details about Chaos Operator soon, but for now think about it as a chaos generator that takes your tuned settings and applies the chaos) : This resource is created by the experiment and is used to store details of the experiment run. It contains important experiment level details like the current Verdict (Awaited, Passed, Failed), the current status and the nature of the experiment results, the Chaos Engine reference, salient application/result attributes. It is also a source for metrics collection. It is updated/patched with the status of the experiment run. It is not removed as part of the default cleanup procedures to allow for extended reference. Chaos Result The Run Time Flow The first and foremost step is to install Litmus, either by directly applying the Kubernetes manifest or by doing a helm install of the litmus chart. helm install litmuschaos  --namespace litmus ./charts/litmus-2-0-0-beta/ or kubectl apply -f https://raw.githubusercontent.com/litmuschaos/litmus/master/litmus-portal/cluster-k8s-manifest.yml NOTE: Take a look at the to have Litmus installed step by step in your system detailed installation instructions Once Litmus has been installed in your cluster, it'd create the CRDs and the Chaos Operator as a part of the installation. Once you have the basic CRDs up and running in your cluster, you can pull your experiments from the Hub of experiments, the ChaosHub, containing 30+ experiments for you to try out. After successfully pulling the experiment in your cluster as CRs, the ChaosEngine has to be created which binds your application instance to the chaos experiment you just pulled. This whole time, the Chaos Operator keeps a watch at the ChaosEngine and as soon as it detects a new experiment installation it spawns up a which is responsible for executing the Chaos Experiment with the help of (The Jobs are spawned by the Chaos Runner based on how you have created the Chaos Engine) Chaos Runner Experiment Jobs These Experiment Jobs then create the Chaos Results, which are continually updated as the experiment is being executed. The Chaos Runner listens to these results and patches them to the Chaos Engine accordingly. How the Chaos Operator works Now at this point, we are already aware of Chaos Engine being one of the important Custom Resources in this project, but there's much more to it that just binding application instances. The Chaos Engine CR is what holds the crucial information of which is the target application to induce chaos on! The Operator on the other hand is responsible for identifying whether the target application is existing on the cluster from the Chaos Engine (It does so with the help of app namespace and app label which is defined as a part of the Chaos Engine CRD). Once it gets confirmation that these applications are present on the cluster, it does a routine annotation check (Can be turned off as well, but in case you are someone worried about controlling the blast radius, do keep it enabled). Next comes validating the policies/run properties that have been constructed as a part of Chaos Engine (Default as well as when modified), the Engine is what holds the service accounts which is responsible for creating the Chaos Runner and Experiment Pods (RBAC). Role Bindings are very helpful when it comes to assessing the permissions you have given for a workflow or individual experiments. It is then followed by a validation of the experiment tunables that had been overridden on added, for example, adding a new ConfigMap to push some secret to it, Overriding the default experiment parameters, pushing instance-specific data dynamically during experiment run, etc. The operator also takes note/validates the Chaos Runner attributes as well, it checks whether the pull policy, the set of images and arguments are correct or not, it comes really handy when you are targeting infra changes. Job Cleanup Policy This is a tunable property of the workflow which decides whether you want to clear all the resources used for inducing chaos in your application and revert it back to the original state, or you want to retain all the resources created and use it to export metrics in your own Analytical solutions. Monitoring The operator is also responsible for monitoring your application state, if this tunable is set to true then the experiment metrics are monitored. The operator ensures that these metrics are collected and enables the exporter to scrape them from the Chaos Engine. In the future releases, Litmus won't have this tunable parameter anymore, since it won't be available anymore in the Chaos Engine the users can't use this tunable from there, instead, if they don't want to collect the metrics of their workflows they have to skip the installation of the . chaos-exporter Apart from all the above Jobs of the Chaos Operator, it also reconciles the state of the Chaos Engine and takes certain steps based on the result of the Chaos Experiment. The Three modes of the Operator Litmus provides certain operational modes when it comes to diversifying the range of chaos operations for different personas making it suitable for use-cases of SREs, Developers, Service Owners, etc so that they can induce chaos on their specific cluster (individual or shared). There are three modes that the Chaos Operator supports Standard Admin Namespaced - The Standard Mode is where Litmus run on a centralized namespace (typically litmus) and it watches for Chaos Engines created in the cluster in different namespaces. Mostly suited for SREs, DevOps Admins, etc. Standard - Admin mode is one of the ways the chaos orchestration is set up in Litmus, wherein all chaos resources (i.e., install time resources like the operator, Chaos Experiment CRs, Chaos Service Account and runtime resources like Chaos Engine, Chaos Runner, etc) are set up in a single admin namespace (typically, litmus). This mode typically needs a "wider" & "stronger" ClusterRole, albeit one that is still just a superset of the individual experiment permissions. In this mode, the applications in their respective namespaces are subjected to chaos while the chaos job runs elsewhere, i.e., admin namespace. Admin - This mode constraints developers to very strict environments where they are very conscious about the blast radius and the policies are set in such a way that they don't get the visibility to watch the Chaos Operators in any other namespace. Namespaced Chaos Orchestration Now that you are aware of all the Chaos Resources and the primary details which make up the Chaos Experiment, its time to take a look at the main Orchestration. There are three main states of Chaos Orchestration namely Initialization Completed Stopped Initialization Once the operator triggers Chaos and spawns the Chaos Runner Pod, the experiment is in the Initialization phase. The Chaos Operator is instrumented with Kubernetes Finalizers which ensures to only delete the supporting chaos resources if and only if all the child resources have been exhausted/reached a logical conclusion and your experiment have been finished. Completed The execution of the experiment is verified by the Chaos Runner with the help of the Chaos Result resource which then states/validates that the experiment has been completed. At this point, re-applying the Chaos Engine would repeat the same steps and the experiment would be repeated seamlessly. Depending upon your job cleanup policy the Chaos Operator might either remove or retain your experiment Pods. If you decide to remove all the Chaos Resources, the Finalizer would be removed as well. Stopped Once initialized, you are having second thoughts about your experiments and want to abruptly stop it in the middle! You can actually do so by either patching the Engine state to stop or delete the Chaos Engine resource completely. If you have patched the Operator then it will set the Engine Status to Stopped. If you re-apply the experiment at this point, it'll re-trigger the experiment run. As a part of this abort operation, it forcefully deletes the Chaos Pods. Conclusion That's all folks 👨‍🏫, Thank you for reading it till the end. I hope you had a productive time learning about Litmus and how it works internally. Are you an or a enthusiast? Does excite you? SRE Kubernetes Chaos Engineering Join Our Community On Slack For Detailed Discussion, Feedback & Regular Updates On Chaos Engineering For Kubernetes: https://kubernetes.slack.com/messages/CNXNB0ZTN (#litmus channel on the Kubernetes workspace) Check out the Litmus Chaos GitHub repo and do share your feedback: https://github.com/litmuschaos/litmus Submit a if you identify any necessary changes. pull request Don't forget to share these resources with someone who you think might need some help learn/explore more about Chaos Engineering. Peace out. ✌🏼 Also published on Dev.to

Solid Tips on How to Manage and Monitor Chaos via Litmus Custom Resources

No, it isn’t related to your compensation or job title. We measure our jobs through the impact it creates. And to measure that impact, we start monitoring the change in our titles when compared to our peers, our compensation as benchmarked by the industry, the number of appreciations, or any other reasonable metric created by our organization. All of them collectively make mini moments-of-truth of your impact in an organization. But the is when you gather the courage with your manager. There are few possible scenarios of how this conversation might flow - true litmus test to talk about moving on The manager’s sudden cardiac arrest #1 A few nerve-wrecking moments followed by a conversation to get into the depth of #2 “what caused this move and what can be done to mitigate it?” After a few formalities, a conversation that immediately jumps to deciding your last date with the organization. #3 The manager doesn’t even blink her eyes, talks about the Plan B, and decides the last date for you #4 Scenario and are manifestation of the value you are creating. Perhaps the organization couldn’t make you realize the importance of your contributions and that’s why you started looking for jobs. If this was the only reason then a transparent discussion can easily solve this problem rather than you moving on. #1 #2 Scenario and are terrible. Probably she wanted you to leave but didn’t have the courage to express it. And now that you said it, she was thankful for it and wants it to be finally over. These are a clear sign that you were under-performing. I understand that your views may differ and in that case I believe you can have a transparent discussion. Perhaps there was a gap in expectation setting. #3 #4 (again) But, let’s for a moment set all this aside and look at who would lose the most from you walking away? You or your manager? Well, the answer is- your manager. She would have to take scores of interview to fill your position; would have to spend days, weeks and months to make the new person understand and align with the organizational culture; would have the uphill task to plan and execute the training ramp-up of a new person. Basically, she would invest a gazillion hours of her life to build a new relationship all over again. So, logically- if you were creating tremendous value, why would your manager want to go through such an ordeal? She wouldn’t want to, right? Heck, you wouldn’t want to, if you were in her position. So my point is- if you think you are conscientious; take your work seriously, want to create value in this world then it’s a worthwhile exercise to explore why your manager welcomes the thought of you moving on to a new job. Because, let’s face it- there isn’t any point in moving to a new job with your execution skills. If you couldn’t create value in your current job, then there is a chance that you might not be able to do so in the next one either. Here’s what you can do instead - not-so-great Ask your manager what skills you need to develop further to start creating a positive impact. Are there any behavior patterns that you need to work on to create a positive experience for the team? Share your reasons why she might have had a cardiac arrest after hearing the news of you moving on, and then have her respond to those claims. Maybe, , you find out that your ‘claim to fame’ weren’t really that big of a deal. (or, claim to fame) just maybe You should do all or some of the above only when you thought you were doing a kick-ass job while your manager thought there was a vast room for improvement. And, if you were doing a suboptimal job on purpose ( ), then you must move on quickly. Life is too short to waste on jobs that you don’t like. which I fail to understand why anyone would Also, I’m not suggesting you should take everything on the face value that your manager suggests. But have the conversation to understand a different perspective of your contributions, reflect on it, deliberate on it, and , learn from it. if possible Don’t want the resignation drama? Still want to know your impact? I would suggest you to do the ‘ ’. The test is simple and has been made popular by Netflix. Keeper’s Test Every few months, you could ask your manager a hypothetical question- “ ” If I say that I am moving on then how hard would you fight to change my mind? It’s a difficult conversation but can be uplifting if done transparently and thoughtfully. After all, in the end, you are the only one who is going to benefit from it. Thus, it’s in one’s best interest to indulge in that kind of conversation.

The litmus test to know the impact you are making at work

This year Bitcoin has caused the biggest buzz in the world of Web3 since its launch in 2009. It has been a huge year for Bitcoin, the world’s largest cryptocurrency. It hit a new all-time high this year as ETFs were approved in the US, Australia, and Hong Kong and institutions jumped on the BTC bandwagon. New exciting ways to interact with Bitcoin also emerged such as Casey Rodarmor’s Runes protocol and there have also been several significant technological breakthroughs making advanced computation possible on Bitcoin for the first time such as BitVMX and SNARKnado. At the same time, a huge wave of new projects emerged claiming to have built new innovations on top of Bitcoin, some of them raising ridiculous amounts of money. Many have already fallen foul to criticism or called scams such as SatoshiVM and Merlin. Others have yet to prove they have real connections to Bitcoin beyond just marketing and hype. But what many people don’t know is that real layers on top of Bitcoin have existed for some time and a dedicated crew of cypherpunks, freedom maximalists, and daring developers have been building on top of Bitcoin for years, taking it from a store of value and transforming it into something that could power the global financial system of the future. In this article, I wanted to shine a light on the true Bitcoin L2s with real use cases and adoption that I believe will gain even greater popularity in 2024 and beyond. Enter the world of Bitcoin L2s & Sidechains So first, what is a Bitcoin Layer Two? I think that Sergio Lerner, long-time Bitcoin contributor and creator of Rootstock, explained it well in a recent interview with CoinTelegraph. “It must use BTC as its native asset and as a settlement mechanism to enforce transactions and demonstrate a functional dependence on Bitcoin.” Many people have different ideas than this but for me this definition is close. It’s a great litmus test to avoid scammers and shilling. Beyond the technological dependence of Bitcoin, my definition is that a true Bitcoin layer two should support the growth and adoption of layer one Bitcoin. A real Bitcoin Layer 2s should ultimately contribute to the success of Bitcoin but it should exist to provide functionality that the layer one was never designed for. This allows Bitcoin to remain secure, pure and home of the hardest form of money while allowing new features and functionality to be developed on top of it. So which Bitcoin L2s should we be exploring in 2024? Lightning Lightning is essentially the payment network for Bitcoin. It allows for near-instantaneous Bitcoin payments and has gained widespread adoption in retail environments. I’ve personally paid for many a beer and coffee with Lightning over the years. It allows for the unilateral transfer of Bitcoin between the main chain and the Lightning layer2 and its laser focus on Bitcoin payments has made it a critical piece of the Bitcoin puzzle. Lightning launched in 2019 with a smart “Pass The Torch” campaign where users would add 10,000 SATS (0.00002451 BTC) to a Lightning payment and pass it one. The campaign reached the likes of Block Inc founder, Jack Dorsey, Litecoin Creator Charlie Lee, Lightning Labs CEO Elizabeth Stark, and CZ of Binance fame. One really cool feature of Lightning Network is that an increasing amount of crypto exchanges have started adding Lightning support as way for users to withdraw and deposit Bitcoin from the exchange. This means faster transaction times and cheaper fees. The most recent exchange to do this was Coinbase in partnership with Lightspark. There are many different wallets available that support Lightning. Some custodial and non-custodial. Its always worth doing your research thoroughly before deciding on which one is for you. Custodial lightning wallets tend to be easier to use but you are reliant on a third party to keep your bitcoin safe. Rootstock Rootstock is the home of apps on Bitcoin. It combines all the programmability of Ethereum with the security and store of value of Bitcoin. Developers have launched lots of different dApps on top of Bitcoin using Rootstock including DEXes like Sovryn, Bitcoin collateralized stablecoins like Money on Chain, and even a naming service known as RIF Name Service which is similar to Ethereum’s ENS. Rootstock uses the Solidity programming language and has all the same developer tools as Ethereum Layer2s making it easy to get started on. It is also supported by MetaMask which makes it easy for users of other EVM chains to easily connect to the network. One neat dApp on Rootstock I discovered  recently is called Asami Club. It pays people in Bitcoin-backed stablecoins for sharing content on social media. The Rootstock ecosystem site has over 100 different apps, exchanges, and wallets listed. Users move their Bitcoin into Rootstock through a bridge known as the PowPeg, described as the most secure, permissionless, and uncensorable Bitcoin bridge. From my research, it seems it was also the first-ever bridge between Bitcoin and another network. Some of the contributors to the network are still working on ways to improve this connection using BitVMX. Rootstock was created by a group of Bitcoin OGs out of Argentina in 2015. It was launched to the public in 2018. The cool thing for me is anyone can build whatever they want on the blockchain in a truly permissionless manner, it’s fully open source and already has lots of individuals and organizations around the world working on it. Liquid For me, Liquid is exciting as it was created by Adam Back, a British cryptographer, and cypherpunk who spoke directly to Satoshi Nakamoto, the legendary creator of Bitcoin. Satoshi credits Adam’s work in the original Bitcoin whitepaper. Liquid has a different focus from Lightning and Rootstock as it is primarily focused on enabling the issuance of security tokens and other digital assets secured by Bitcoin. This is things like the much discussed El Salvador Bitcoin Bond which will be tokenized on Liquid as well as the recently announced tokenized version of MicroStrategy's Class A Common Stock known as CMSTR Note. Liquid is one to watch as we see more institutions exploring how they tokenize assets on Bitcoin whether it be fine art or real estate. In fact, while researching this article I found some very recent news that Bitfinex just launched a $6.25 million token bond on Liquid to fund the construction of a Hilton hotel at the San Salvador International Airport. Sounds like things are taking off! (pun intended) Beyond Bitcoin’s Big Three In this article, I’ve written about what I believe to be three of the critical networks for scaling Bitcoin and allowing it to reach worldwide adoption. I’ve intentionally avoided talking about the typical crypto casino world of meme coins. These can be a lot of fun to play around with but ultimately have no real value or utility to the world. The three examples given above all support real use cases and will prosper whatever current crypto cycle we are in which is a major reason I’m so bullish on them. There is a lot of innovation happening right now on Bitcoin. I’m excited to see what comes next for the world’s most decentralized cryptocurrency as well as the three most important layers built on top of it. I’m sure that the innovations will continue and there is much more to explore. Perhaps in 2035, I’ll write another article diving into just how far Bitcoin’s Big Three have come and what other interesting networks have emerged onto the scene. This year Bitcoin has caused the biggest buzz in the world of Web3 since its launch in 2009. This year Bitcoin has caused the biggest buzz in the world of Web3 since its launch in 2009. This year Bitcoin has caused the biggest buzz in the world of Web3 since its launch in 2009. It has been a huge year for Bitcoin , the world’s largest cryptocurrency. It hit a new all-time high this year as ETFs were approved in the US , Australia , and Hong Kong and institutions jumped on the BTC bandwagon. New exciting ways to interact with Bitcoin also emerged such as Casey Rodarmor’s Runes protocol and there have also been several significant technological breakthroughs making advanced computation possible on Bitcoin for the first time such as BitVMX and SNARKnado . Bitcoin US Australia Hong Kong BTC Runes BitVMX SNARKnado At the same time, a huge wave of new projects emerged claiming to have built new innovations on top of Bitcoin, some of them raising ridiculous amounts of money. Many have already fallen foul to criticism or called scams such as SatoshiVM and Merlin . Others have yet to prove they have real connections to Bitcoin beyond just marketing and hype. SatoshiVM Merlin But what many people don’t know is that real layers on top of Bitcoin have existed for some time and a dedicated crew of cypherpunks, freedom maximalists, and daring developers have been building on top of Bitcoin for years, taking it from a store of value and transforming it into something that could power the global financial system of the future. In this article, I wanted to shine a light on the true Bitcoin L2s with real use cases and adoption that I believe will gain even greater popularity in 2024 and beyond. Enter the world of Bitcoin L2s & Sidechains So first, what is a Bitcoin Layer Two? I think that Sergio Lerner, long-time Bitcoin contributor and creator of Rootstock, explained it well in a recent interview with CoinTelegraph . CoinTelegraph “It must use BTC as its native asset and as a settlement mechanism to enforce transactions and demonstrate a functional dependence on Bitcoin.” “It must use BTC as its native asset and as a settlement mechanism to enforce transactions and demonstrate a functional dependence on Bitcoin.” Many people have different ideas than this but for me this definition is close. It’s a great litmus test to avoid scammers and shilling. Beyond the technological dependence of Bitcoin, my definition is that a true Bitcoin layer two should support the growth and adoption of layer one Bitcoin. A real Bitcoin Layer 2s should ultimately contribute to the success of Bitcoin but it should exist to provide functionality that the layer one was never designed for. This allows Bitcoin to remain secure, pure and home of the hardest form of money while allowing new features and functionality to be developed on top of it. So which Bitcoin L2s should we be exploring in 2024? Lightning Lightning Lightning is essentially the payment network for Bitcoin. It allows for near-instantaneous Bitcoin payments and has gained widespread adoption in retail environments. I’ve personally paid for many a beer and coffee with Lightning over the years. It allows for the unilateral transfer of Bitcoin between the main chain and the Lightning layer2 and its laser focus on Bitcoin payments has made it a critical piece of the Bitcoin puzzle. Lightning launched in 2019 with a smart “Pass The Torch” campaign where users would add 10,000 SATS (0.00002451 BTC) to a Lightning payment and pass it one. The campaign reached the likes of Block Inc founder, Jack Dorsey, Litecoin Creator Charlie Lee, Lightning Labs CEO Elizabeth Stark, and CZ of Binance fame. One really cool feature of Lightning Network is that an increasing amount of crypto exchanges have started adding Lightning support as way for users to withdraw and deposit Bitcoin from the exchange. This means faster transaction times and cheaper fees. The most recent exchange to do this was Coinbase in partnership with Lightspark . Coinbase in partnership with Lightspark There are many different wallets available that support Lightning. Some custodial and non-custodial. Its always worth doing your research thoroughly before deciding on which one is for you. Custodial lightning wallets tend to be easier to use but you are reliant on a third party to keep your bitcoin safe. Rootstock Rootstock is the home of apps on Bitcoin. It combines all the programmability of Ethereum with the security and store of value of Bitcoin. Developers have launched lots of different dApps on top of Bitcoin using Rootstock including DEXes like Sovryn , Bitcoin collateralized stablecoins like Money on Chain , and even a naming service known as RIF Name Service which is similar to Ethereum’s ENS. Rootstock uses the Solidity programming language and has all the same developer tools as Ethereum Layer2s making it easy to get started on. It is also supported by MetaMask which makes it easy for users of other EVM chains to easily connect to the network. Sovryn Money on Chain RIF Name Service One neat dApp on Rootstock I discovered  recently is called Asami Club . It pays people in Bitcoin-backed stablecoins for sharing content on social media. The Rootstock ecosystem site has over 100 different apps, exchanges, and wallets listed. Asami Club Rootstock ecosystem Users move their Bitcoin into Rootstock through a bridge known as the PowPeg, described as the most secure, permissionless, and uncensorable Bitcoin bridge . From my research, it seems it was also the first-ever bridge between Bitcoin and another network. Some of the contributors to the network are still working on ways to improve this connection using BitVMX . most secure, permissionless, and uncensorable Bitcoin bridge improve this connection using BitVMX Rootstock was created by a group of Bitcoin OGs out of Argentina in 2015. It was launched to the public in 2018. The cool thing for me is anyone can build whatever they want on the blockchain in a truly permissionless manner, it’s fully open source and already has lots of individuals and organizations around the world working on it. Liquid For me, Liquid is exciting as it was created by Adam Back, a British cryptographer, and cypherpunk who spoke directly to Satoshi Nakamoto, the legendary creator of Bitcoin. Satoshi credits Adam’s work in the original Bitcoin whitepaper. original Bitcoin whitepaper. Liquid has a different focus from Lightning and Rootstock as it is primarily focused on enabling the issuance of security tokens and other digital assets secured by Bitcoin. This is things like the much discussed El Salvador Bitcoin Bond which will be tokenized on Liquid as well as the recently announced tokenized version of MicroStrategy's Class A Common Stock known as CMSTR Note . El Salvador Bitcoin Bond CMSTR Note Liquid is one to watch as we see more institutions exploring how they tokenize assets on Bitcoin whether it be fine art or real estate. In fact, while researching this article I found some very recent news that Bitfinex just launched a $6.25 million token bond on Liquid to fund the construction of a Hilton hotel at the San Salvador International Airport . Sounds like things are taking off! (pun intended) fund the construction of a Hilton hotel at the San Salvador International Airport (pun intended) Beyond Bitcoin’s Big Three In this article, I’ve written about what I believe to be three of the critical networks for scaling Bitcoin and allowing it to reach worldwide adoption. I’ve intentionally avoided talking about the typical crypto casino world of meme coins. These can be a lot of fun to play around with but ultimately have no real value or utility to the world. The three examples given above all support real use cases and will prosper whatever current crypto cycle we are in which is a major reason I’m so bullish on them. There is a lot of innovation happening right now on Bitcoin. I’m excited to see what comes next for the world’s most decentralized cryptocurrency as well as the three most important layers built on top of it. I’m sure that the innovations will continue and there is much more to explore. Perhaps in 2035, I’ll write another article diving into just how far Bitcoin’s Big Three have come and what other interesting networks have emerged onto the scene.

Bitcoin's Big Three: The Best Layer 2s in 2024

বিটকয়েনের বিগ থ্রি: 2024 সালে সেরা স্তর 2

Die großen Drei von Bitcoin: Die besten Layer 2s im Jahr 2024

Los tres grandes de Bitcoin: las mejores capas 2 en 2024

Les trois grands de Bitcoin : les meilleures couches 2 en 2024

बिटकॉइन के बिग थ्री: 2024 में सर्वश्रेष्ठ लेयर 2

ビットコインのビッグスリー：2024年のベストレイヤー2

비트코인의 빅 3: 2024년 최고의 레이어 2

As três grandes do Bitcoin: as melhores camadas 2 em 2024

Большая тройка Биткойна: лучшие уровни 2 в 2024 году

Bitcoin'in Üç Büyükleri: 2024'ün En İyi Katman 2'leri

Bộ ba lớn của Bitcoin: Lớp 2 tốt nhất năm 2024

比特币三大巨头：2024 年最佳第二层

In a comprehensive investigation into Fiverr.com's SEO freelancers, shocking revelations have emerged, suggesting that over 98% of self-proclaimed SEO professionals on the platform may lack the SEO expertise they claim to possess. The study, which involved creating 20 new Fiverr user accounts, aimed to assess the credibility of freelancers offering SEO services. However, the investigation took an unexpected turn as it uncovered that 100% of the freelancers surveyed were from India or Pakistan. Shockingly, my small team found only 1% of the respondents demonstrated only a partial understanding fundamental and basic SEO concepts or were seen to be , casting doubt on the legitimacy of their claims. authentic What's more alarming is the emerging trend among freelancers from India and Pakistan, who seem to be misrepresenting their SEO knowledge, potentially leading clients astray in their quest for genuine expertise in search engine optimisation. Many of these self-proclaimed experts are accused of merely reselling generic blog posts rather than implementing effective SEO strategies. The investigation has shone a spotlight on the prevalence of misleading information on freelancer profiles, with numerous individuals allegedly embellishing their qualifications and experience. SEO industry experts emphasize the need for caution and thorough due diligence when hiring freelancers for SEO services on Fiverr. The investigation highlights the challenges faced by both freelancers and clients in navigating the complexities of the online marketplace, underscoring the necessity for increased transparency to foster a trustworthy environment for all stakeholders. As the investigation unfolds, lingering questions surround the potential impact on Fiverr's reputation and the steps the platform will take to remedy the situation and restore confidence among its user base. The concentration of the issue within freelancers from India and Pakistan adds a layer of complexity to the ongoing discussions about the integrity of the Fiverr platform. Scrutiny Over Efficacy of Freelancer Testing On Fiverr. As Fiverr undergoes increased scrutiny over the proficiency of its freelancers, questions are arising about the effectiveness of the platform's testing process. While Fiverr requires freelancers to take tests before they can offer their services, concerns have been raised about the reliability of these assessments. This skepticism has intensified as it became apparent that many freelancers, who purportedly passed these tests, struggled to answer basic SEO questions during live chats. Fiverr's testing system is designed to assess the skills and knowledge of freelancers before they are permitted to offer their services on the platform. However, recent revelations suggest that the testing might not be stringent enough, with freelancers allegedly finding ways to obtain answers or even having others complete the assessments on their behalf. While Fiverr's testing process may be comprehensive on paper, the real litmus test comes in the form of practical application. The inability of a significant number of freelancers (98%) to answer live SEO questions has prompted concerns about the integrity of the testing system and its effectiveness in ensuring that freelancers possess the claimed expertise. As the investigation into Fiverr's SEO freelancers continues, the effectiveness of the platform's testing procedures will likely remain a focal point of discussion, with implications for the overall quality and reliability of services offered on Fiverr. Caution Advised: Considerations Regarding Fiverr.com for SEO Services - Avoid The Platform. In light of recent revelations surrounding Fiverr.com's SEO freelancers and the efficacy of their testing procedures, a note of caution is sounded for those seeking SEO services, supposed outreach blogging, or technical SEO tasks on the platform. Given the challenges uncovered in the investigation, it is highly recommended to totally avoid Fiverr.com and, where possible, to consider alternative platforms or avenues for procuring SEO services. The reported misrepresentations, lack of proficiency, and potential issues with Fiverr's testing process underscore the importance of thorough due diligence when selecting freelancers for SEO-related tasks. In 2024, as a journalist and marketing enthusiast I suggest avoiding Fiverr and not spending a single dime on the platform. I personally hope to see it flop just as an alternative SEO freelancer platform recently did in 2023 - (Land of the SEO & Link Scams). SEOclerks.com The Perfect Fiverr Scam Example - Rubbish Ranking Scammer Oh really? Rank 1st in Google above website owners and businesses who have 100k digital marketing budgets and real industry experts with some trashy spammy links for your stated price of just $46.23AUD Wow!!! - Hey, let’s get in touch with and dominate the search engines! this guru No market analysis No research. No on page technical SEO optimizations No Google Search Console Setup No hosting site performance optimizations. - Just some spammy noindex spam blog links and rank No1 !! THIS GURU MUST HAVE GOOGLE’S SECRET SAUCE Fiverr, allowing this? You are kidding me, right? Please - Stay away from far far far Fiverr. In turns out after receiving a sample report from this scammer that he is using free public noindex web 2.0 PBN blogs. The posts do not index in Google, the links are ignored by the search engines and are coupled with scrapped copyright and re spun content. His links have zero impact in the search engines. Here is the sample provided by the scammer. People buying this rubbish have no SEO knowledge and don’t understand they have been scammed. These URLs are from what are called no-index public web 2.0 PBN spam blogs. They are also created on sub-domains which means they simply have zero authority even if they did index in the search engines. (Total worthless junk) Examples of the worthless scam links & URLs created by the Fiverr scammer. https://jareddwlv46036.pages10.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-59884048 https://angelonkfy73838.ampblogs.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-60835799 https://manuelgwuj01000.blogocial.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-60199774 https://johnathanspjz71504.onesmablog.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-64180092 https://claytonectc38483.blogolize.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-63631470 https://codycsfq25713.shotblogs.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-38125468 https://simonwsyc29631.pages10.com/harmonizing-home-decor-with-feng-shui-remedies-59884066 https://angelohduh43209.bloguetechno.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-59647812 https://israelmylu36025.tribunablog.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-38381867 https://jeffreyfagf63074.ampblogs.com/harmonizing-home-decor-with-feng-shui-remedies-60835819 https://zanderwpdn03692.blogzet.com/elevating-soulful-living-interior-design-and-feng-shui-in-nyc-38809594 The above URLS are impossible to index. They never will. This is the same link building scam provided by Linkdaddy.com - https://linkdaddy.com/domain-power-booster/ With Fiverr.com allowing this gig to stay advertised, allowing more and more people to get scammed without knowing and after advising Fiverr directly this is scam, makes the platform officially a scam also.  (Advertising and profiting from known fraudulent services and scams) The Dark Underbelly of Fiverr.com Let me tell you about the dark underbelly of Fiverr.com, a breeding ground for freelancing scammers preying on unsuspecting victims. It's a virtual den of deceit, a platform that has become a playground for those who want to exploit the desperation of people clueless about SEO and the intricacies of the freelancing industry. In 2021, I delved into the abyss, armed with the noble mission of exposing these freelance scammers. Over 40 of them, to be precise. I meticulously reported and technically demonstrated the scams, laying bare the deceit that runs rampant on Fiverr. These scammers, like cunning chameleons, mask themselves as experts, luring in desperate souls seeking a break in the competitive world of freelancing. The most insidious part? Users, despite my warnings, were left powerless, unable to change their feedback after leaving positive reviews. And, in my opinion, Fiverr.com are as bad as the Freelancer scammers operating on it. Oh, the bitter taste of betrayal! Weeks later, the bitter truth revealed itself – those seemingly impactful gigs had zero positive effect on SEO or rankings. Fiverr, it seems, is complicit in this elaborate ruse, preying on the vulnerable and banking on the ignorance of those who know nothing about the treacherous maze of SEO and the scammers who push it. This platform, once heralded as a haven for freelancers, has transformed into a breeding ground for exploitation. Fiverr thrives on the desperation of people desperately trying to make their mark in the digital wilderness. It's a cesspool were scammers parade as experts, siphoning money from the pockets of the unsuspecting while the flatform itself promotes the scammers for a commission. So please, for the love of all the remaining good in the digital marketing sector, unless you are a cashed up and ready to pay today’s real industry pricing for real expert services, stay away from Fiverr.com and spend your money on new pair of shoes!

Fiverr's SEO Gig Landscape: Fake Freelancer Experts in Question

Fiverr এর এসইও গিগ ল্যান্ডস্কেপ: প্রশ্ন জাল ফ্রিল্যান্সার বিশেষজ্ঞদের

Fiverrs SEO-Gig-Landschaft: Fake-Freelancer-Experten in Frage

Panorama de trabajos de SEO de Fiverr: falsos expertos autónomos en cuestión

Le paysage des concerts SEO de Fiverr : les faux experts indépendants en question

फाइवर का एसईओ गिग लैंडस्केप: सवालों के घेरे में नकली फ्रीलांसर विशेषज्ञ

Fiverr の SEO ギグ風景: 問題の偽フリーランサー専門家

Fiverr의 SEO 공연 환경: 문제의 가짜 프리랜서 전문가

Cenário de shows de SEO de Fiverr: falsos especialistas freelancers em questão

SEO-концепция Fiverr: под вопросом фальшивые эксперты-фрилансеры

Fiverr'ın SEO Performansı: Sahte Freelancer Uzmanları Söz konusu

Toàn cảnh buổi biểu diễn SEO của Fiverr: Các chuyên gia làm việc tự do giả mạo đang được đề cập

Fiverr 的 SEO 工作格局：假自由职业专家受到质疑

How to Effectively Evaluate Your RAG + LLM Applications

কীভাবে কার্যকরভাবে আপনার RAG + LLM অ্যাপ্লিকেশনগুলিকে মূল্যায়ন করবেন

So bewerten Sie Ihre RAG- und LLM-Anwendungen effektiv

Cómo evaluar eficazmente sus solicitudes RAG + LLM

Comment évaluer efficacement vos candidatures RAG + LLM

अपने आरएजी + एलएलएम अनुप्रयोगों का प्रभावी ढंग से मूल्यांकन कैसे करें

RAG + LLM アプリケーションを効果的に評価する方法

RAG + LLM 지원서를 효과적으로 평가하는 방법

Como avaliar efetivamente suas inscrições RAG + LLM

Как эффективно оценить ваши заявки на RAG + LLM

RAG + LLM Başvurularınızı Etkin Bir Şekilde Nasıl Değerlendirebilirsiniz?

Cách đánh giá hiệu quả các ứng dụng RAG + LLM của bạn

如何有效评估您的 RAG + LLM 申请

Data-driven decision-making is a culture that should be adopted from day one. In this article, I'll explain in simple terms how to measure five key metrics for B2B SaaS startups — CAC, CLV, MRR, CCR, and NPS — and how to use the insights for making well-informed decisions. CAC: Track It to Allocate Your Budget Wisely or CAC, shows how much money a business spends to get a new customer. It is calculated by dividing all the costs spent on acquiring customers by the number of new customers. Customer Acquisition Cost, Customer Acquisition Cost (CAC) = Total Acquisition Costs / Number of New Customers If a company spends $12,000 per month on customer acquisition and brings in 40 new customers, its average CAC is $12,000 / 40 = $300. Tracking this metric helps a company pick effective marketing and sales channels, set the right product prices, and grow the business seamlessly. Also, the CAC helps to identify areas where money is not effectively used. The average CAC for a B2B SaaS startup is about $ . In some industries, like insurance and medtech, the number can range from $400 to $500. If the CAC is high, acquiring customers is more costly than the revenue they generate. The business may need to: 250 test other marketing and sales channels; adjust pricing plans; target other audience segments. In this regard, I like the Dropbox story. In its early days, the startup relied on search engine ads to get new users, but it was too expensive. Later on, the company’s user data showed that their best customers were coming from referrals, so the team created an easy-to-use and beneficial referral program. This was a pivotal decision: Within 15 months, the startup user base grew from 100,000 to 4 million people. CLV: Track It to Remain Profitable and Be №1 For Your Customers or CLV/CLTV (alternatively termed Lifetime Value, or LTV), represents the total revenue a customer is supposed to bring to the business. It is calculated by multiplying the average amount a customer spends in each transaction by the number of times they make a transaction and then multiplying that by the average customer lifespan. Customer Lifetime Value, Customer Lifetime Value (CLV) = Average Purchase Value × Average Purchase Frequency × Average Customer Lifespan If a customer typically spends $20 per purchase, makes three purchases a year, and stays with the company for two years, their CLV is 20 × 3 × 2 = $120. CLV will show how much your customers are worth overall. Like a litmus test, this metric reveals if they are loyal to your brand and happy with your product. If not, it will get harder to retain them. CLV also reveals which customers bring in the most revenue and which offerings they enjoy. To achieve a healthy business, B2B SaaS companies aim for a CLV to CAC ratio of or higher. This means that for every $1 spent on customer acquisition, the company generates at least $3 in revenue. A lower ratio, like 2:1, indicates that the business may need to reduce customer acquisition spending while increasing customer retention and the average revenue per user. 3:1 Sometimes, businesses may find that their cost of acquiring customers (CAC) exceeds the revenue generated from those customers over time (CLV). In this case, or if you just want to increase CLV, consider these options: look for cost-efficient marketing channels (test SMM, e-mail marketing, or partnerships); find ways to retain existing customers (through loyalty programs, better service, product improvements, and other tactics); review the pricing strategy to avoid underpricing and ensure generated revenue aligns with acquisition cost; ensure effective targeting to reach the right audience for your product; explore ways to upsell additional products or services to your existing customers. MRR: Track It to Know When It’s Time to Approach Investors or MRR, reflects the predictable and regular income a business expects to receive each month from its subscription-based customers. It is calculated by summing up the subscription fees generated from all active customers within a specific month. Monthly Recurring Revenue, Monthly Recurring Revenue (MRR) = ∑ (Subscription Fees from Active Customers) For example, if a business has 100 customers paying $50 per month, its MRR is 100 × 50 = $5,000. Then, if case you need, you can calculate Annual Recurring Revenue (ARR) by multiplying MRR by 12. MRR is a steady income stream that helps cover essential operational costs at a startup. By tracking this metric, founders can manage ongoing expenses effectively and assess the overall financial performance of their company. A decrease in MRR may indicate customer churn, downgrades (when users switch to a lower-priced plan), or loss of subscriptions. Investors and potential acquirers often review this metric when evaluating SaaS startups. A strong MRR can make the company more attractive for VCs and potentially increase its valuation. MRR benchmarks vary based on product and pricing, so each startup should set its own targets. When it comes to MRR growth rates for B2B SaaS startups, some industry experts, including SaaStr community's founder , suggest aiming for an MRR growth of 10-20% month over month. Jason M. Lemkin An important milestone for an early-stage startup is $1 million in ARR. A recent shows that the main growth driver for most B2B SaaS startups, reaching $1M to $10M in ARR, is the expansion of their customer base — not just increasing their current average revenue per user. achieving study CCR: Track It to Prevent Revenue and Reputation Losses or CCR, shows the percentage of customers who cancel their subscriptions or stop using a service within a given time. It is calculated by dividing the number of customers lost during a specific period by the initial number. Customer Churn Rate, Customer Churn Rate (CCR) = (Number of customers lost for the period / Total number of customers at the beginning of the period) × 100 For example, if a startup starts the month with 500 customers and loses 50 customers by the end of it, its CCR is 50 / 500 × 100 = 10%. According to the (KBCM) 2022 SaaS Survey, the median annual churn for SaaS companies is 13%. KeyBanc Capital Markets If the CCR is higher or growing, it could damage a business. In this case, a company should aim to reduce it fast and increase customer retention by: improving the product based on customer feedback, surveys, focus groups, and market trends; launching loyalty programs or offering personalized customer support; offering incentives for upsells, such as discounts or personalized benefits; providing users with educational materials to ensure they know how to use the product; conducting promo campaigns to re-engage customers; ensuring competitive pricing and adding new pricing plans if needed. NPS: Track It to Improve Your Product and Customer Service or NPS, shows customer satisfaction and loyalty based on their likelihood to recommend a company's product. It is calculated by subtracting the percentage of detractors (customers who would not recommend) from the percentage of promoters (customers who would recommend). The result ranges from -100 to +100. Net Promoter Score, Net Promoter Score (NPS) = Percentage of Promoters - Percentage of Detractors NPS data is collected through customer surveys, usually with a single question: "On a scale of 0 to 10, how likely are you to recommend our product/service to a friend or colleague?" The responses categorize customers into three groups: Promoters (score 9-10), Passives (score 7-8), and Detractors (score 0-6). For example, if a company surveys 1,000 customers and 700 give a score of 9 or 10 (Promoters), while 300 give a score of 0 to 6 (Detractors), the NPS calculation is 70 − 30 = 40. Correct me if I’m wrong. According to the latest , the average NPS in the computer software industry is 36 or higher. As noted by Bain & Company, the of the NPS system, an NPS above 20 is good, 50 is outstanding, and 80 is considered world-class. CustomerGauge’s B2B NPS & CX Benchmarks Report creator However, when a startup launches NPS surveys, it's not just about the numbers. To know what customers like or don't like, the team should also ask which improvements the customers would like to see in the product and customer experience.

Attention B2B SaaS Founders: Start Tracking These Metrics From Day One

Today's business environment is defined by speed, which leaves little room for error in decision-making. This is why a data-driven approach is critical for developing viable business strategies. One of the most reliable indicators of success is a consistent increase in user base, with new users beginning to use your product while existing ones continue to do so. In this article, we'll look at key marketing metrics that can help you measure the effectiveness of your marketing campaigns and strategies in terms of user acquisition, conversion, engagement, and retention. Acquisition User acquisition is the lifeblood of any digital venture. It's not just about increasing numbers; it's about expanding your customer base and driving revenue. Effective user acquisition strategies not only bring in new customers but also create brand awareness and loyalty. Without a robust acquisition plan, growth becomes stagnant, and the digital product's long-term viability is at risk. In today's competitive landscape, mastering user acquisition is vital for staying relevant, scaling, and achieving sustained success. Acquisition Metrics CPA is a digital marketing metric that measures the cost incurred to acquire a new customer or lead through a specific advertising or marketing campaign. It is calculated by dividing the total cost of the campaign by the number of acquired customers or conversions. Cost per Acquisition (CPA) CAC represents the total cost associated with acquiring a new customer for a business. It encompasses all marketing and sales expenses, including advertising, marketing campaigns, and any related personnel or operational costs, divided by the number of new customers gained within a defined time frame. Customer Acquisition Cost (CAC) Return on Advertising Spend (ROAS) ROAS is a metric used in digital advertising to evaluate the effectiveness of a specific campaign. It measures the revenue generated from the campaign in relation to the advertising costs. ROAS is typically expressed as a ratio, with a value of 1 indicating that the campaign broke even, and values above 1 signifying a positive return on investment. Return on Investment (ROI) ROI is a comprehensive financial metric that assesses the profitability of an investment. In the context of digital marketing, it evaluates the overall return on the money invested in marketing and advertising efforts. ROI considers both the initial investment and the subsequent revenue generated and is expressed as a percentage or ratio. A positive ROI indicates that the investment has generated more revenue than its cost. Acquisition Funnel An "Acquisition Funnel" is a marketing and sales model used to visualize and analyze the stages that potential customers go through in their journey from initial awareness of a product or service to becoming paying customers. The funnel typically consists of several stages, which can vary depending on the specific context, but commonly include stages like awareness, interest, consideration, and conversion. At each stage of the acquisition funnel, the number of potential customers may decrease as some individuals drop out of the process, which is why it's often represented as a funnel shape. The goal of businesses is to optimize each stage of the funnel to maximize conversions and acquire more customers. By tracking and analyzing the progression of individuals through the acquisition funnel, businesses can identify where potential customers are dropping off and take action to improve their marketing and sales strategies to increase the overall conversion rate and acquire more customers. User Funnel Conversion Rate The User Funnel Conversion Rate is a metric that measures the percentage of users who successfully progress from one stage to the next within an acquisition funnel. It indicates the efficiency of your funnel in guiding potential customers through the desired journey. Example: If you have 1,000 users who visit your website, and 200 of them sign up for your newsletter, the User Funnel Conversion Rate from visitors to newsletter subscribers is 20% (200/1,000). Funnel Drop-Off Rates Funnel Drop-Off Rates, also known as Dropout Rates, refer to the percentage of users who abandon the acquisition funnel at various stages without completing the desired action. It helps identify points of friction or issues in the user journey. Example: If 1,000 users start the sign-up process for your app but only 600 complete the registration, the Funnel Drop-Off Rate at the registration stage is 40% (100% - 60% who completed the registration). This metric highlights that 40% of users abandoned the process before finishing it. Conversion The term "conversion" stands as a pivotal metric, tracking the effectiveness of a digital product or campaign. Conversion, in its simplest form, signifies the act of a user taking a desired action, thereby transitioning from a passive observer to an active participant. It can encompass a range of activities, from making a purchase, signing up for a newsletter, downloading an app, or any other action a business aims to elicit from its audience. This metric holds immense importance as it serves as a barometer for evaluating the performance of digital endeavors and provides valuable insights into user behavior and the success of a product or campaign. Conversion is usually expressed as a percentage and calculated by dividing the number of users who completed the desired action by the total number of users who had the opportunity to do so. The formula is: Conversion Rate = (Number of Conversions/Total Users)×100 Why Conversion Is a Critical Metric in the Digital Landscape: Measure of Effectiveness Conversion metrics help businesses gauge the effectiveness of their digital strategies. Whether it's a website, an e-commerce platform, a mobile app, or an advertising campaign, the conversion rate provides a clear indication of how well these initiatives are at persuading users to take the desired action. By tracking conversion rates over time, organizations can assess the impact of changes and optimizations they make. Optimization Tool Understanding where users drop off or fail to convert is essential for making improvements. Conversion data can highlight specific bottlenecks in the user journey or barriers to entry, allowing businesses to optimize their digital products or marketing campaigns accordingly. By reducing friction points, enhancing user experience, and refining calls to action, conversion rates can be improved, leading to more successful outcomes. ROI Assessment For businesses, achieving a positive return on investment (ROI) is paramount. Conversion metrics are closely linked to ROI as they directly indicate how effectively a digital product or marketing campaign is at generating revenue or desired outcomes. By comparing the cost of acquiring a user or running a campaign to the revenue generated from conversions, businesses can calculate their ROI and make data-driven decisions on resource allocation. Targeted Decision-Making Conversion rates can be broken down into various segments, such as demographics, traffic sources, or device types. This segmentation allows businesses to make informed, data-driven decisions. For example, if a particular marketing channel has a higher conversion rate compared to others, a business can allocate more resources to that channel to maximize its ROI. User Behavior Insights Conversion metrics offer valuable insights into user behavior. They can reveal not only whether users are converting but also when they're converting, which actions they take before converting, and what may hinder them from converting. This understanding helps in tailoring marketing strategies and user experiences to align with user preferences and needs. Continuous Improvement Digital products and marketing campaigns are not static; they evolve over time. Conversion rates act as a compass for continuous improvement. By A/B testing, experimenting with different elements, and adapting strategies based on conversion insights, businesses can refine their approach and remain competitive in an ever-changing digital landscape. To sum it up, conversion is the heartbeat of the digital realm. It provides a tangible measure of success, guides optimizations, aids in ROI assessment, and empowers businesses to make informed decisions. The ability to convert users from mere visitors to active participants is a testament to the effectiveness of digital products and marketing efforts, making it an indispensable metric in the pursuit of digital success. Engagement Engagement is a fundamental metric in the digital product landscape, serving as a key indicator of how actively and effectively users interact with a product. It measures the depth and frequency of user interactions, reflecting their level of involvement and satisfaction. Engagement goes beyond mere usage statistics, delving into the quality of the user experience and the value provided by the product. In this article, we will explore the concept of engagement, how it is calculated, and why it is of paramount importance in the digital realm. Understanding Engagement Metrics: Engagement metrics encompass a wide array of data points, often specific to the type of digital product or platform. Here are some common engagement metrics: DAU represents the number of unique users who interact with a digital product within a single day. It is a critical metric for measuring daily engagement and assessing the product's relevance. Daily Active Users (DAU): WAU tracks the number of unique users who engage with the product within a one-week period. It provides a broader view of user engagement and consistency. Weekly Active Users (WAU): : MAU measures the number of unique users who interact with the product over a one-month period. It offers insights into long-term engagement and user retention. Monthly Active Users (MAU) Session length indicates how long, on average, a user remains active within a single session or visit to the product. It reflects user involvement and interest in the content or features. Session Length: This metric quantifies the number of screens or pages a user views during a single session. It reveals the depth of exploration within the product. Screen Views per Session: : In-App Interactions encompass actions taken by users while using the product, such as clicks, likes, shares, comments, or purchases. They provide insights into user behavior and preferences. In-App Interactions : For mobile apps, this metric evaluates the effectiveness of push notifications. It measures the percentage of users who click on a notification after receiving it, indicating how well these messages engage users. Push Notification Click-Through Rate : Gathering user feedback and ratings, often through reviews and surveys, can gauge user satisfaction and provide insights into areas for improvement. Positive ratings and constructive feedback are indicators of user engagement. User Feedback and Ratings Why Engagement Is Important: Engagement is a critical metric for several reasons: : High levels of engagement are often indicative of satisfied users. Engaged users are more likely to have positive experiences with the product and become loyal customers or advocates. User Satisfaction : Engaged users tend to stick around longer, reducing churn rates and improving user retention. Loyal users are valuable, as they are more likely to generate repeat business and word-of-mouth recommendations. Retention and Loyalty : Engaged users are more receptive to monetization strategies, such as in-app purchases, subscriptions, or advertising. This can significantly impact the product's revenue. Monetization Opportunities : Engagement metrics offer insights into user behavior, allowing businesses to make data-driven improvements. Identifying which features or content resonate with users and which do not helps in refining the product. Data-Driven Improvements : In a competitive digital landscape, products with high engagement levels often outperform their counterparts. They can adapt to changing market dynamics and maintain their market share. Competitive Advantage By understanding user engagement, product developers can align their efforts with user preferences, leading to a more user-centric and successful product. User-Centric Development: : Engaged users are more likely to participate in a product's community, provide valuable feedback, and advocate for it, leading to organic growth. Community and Advocacy Engagement is the pulse of digital products, reflecting user involvement, satisfaction, and product effectiveness. It plays a central role in user retention, monetization, and ongoing product development. By actively monitoring and improving engagement metrics, businesses can build lasting relationships with their user base, ensuring the continued success of their digital products. Retention In the world of digital products, "retention" stands as one of the most critical metrics, serving as a key indicator of a product's long-term viability and success. Retention refers to the ability of a digital product to keep users engaged and returning over an extended period. It measures the proportion of users who continue to use the product or engage with it after an initial interaction or sign-up. This metric plays a pivotal role in understanding user satisfaction, product stickiness, and the overall health of a digital venture. Understanding Retention Metrics: Retention metrics are typically expressed as percentages and can be measured over various time frames, such as daily, weekly, or monthly. There are three common retention metrics: This metric calculates the percentage of users who return to the product on the day following their initial interaction or sign-up. Daily Retention Rate: It measures the percentage of users who engage with the product in the week following their initial interaction. Weekly Retention Rate: : This metric tracks the percentage of users who continue to use the product in the month following their initial interaction. Monthly Retention Rate The formula for calculating retention rate is as follows: Retention Rate = (Number of Users at the End of a Period/Number of Users at the Start of the Period) × 100 Why Retention Is Important: Retention is not merely a metric; it is a reflection of the value and satisfaction a digital product provides to its users. Here's why retention is so important: : A high retention rate signifies that a digital product is effectively meeting user needs and expectations. Retained users are more likely to become loyal customers, making a product's future revenue streams more predictable and sustainable. Long-Term Sustainability Retention is the most effective weapon against churn, which is the loss of users over time. A low retention rate can lead to higher churn, making it essential for businesses to retain users to maintain their customer base. Reduced Churn: Retained users are not only more likely to make repeat purchases but also to engage with the product, provide feedback, and advocate for it. A product with engaged users can benefit from word-of-mouth marketing and continuous improvement through user insights. User Engagement: : Acquiring new users is often more expensive than retaining existing ones. A strong focus on retention can reduce customer acquisition costs and improve the overall return on investment (ROI). Cost Efficiency : In a crowded digital marketplace, products that excel in retention have a competitive edge. They are more likely to outlast competitors, adapt to changing trends, and retain their market share. Competitive Edge : Retention metrics can help identify which product features or aspects drive user engagement and which ones lead to drop-offs. This data is invaluable for iterative product development, ensuring that a product remains relevant and user-friendly. User Feedback and Iteration : Retained users are more receptive to monetization strategies, such as premium subscriptions, in-app purchases, or advertising. This opens up additional revenue opportunities for digital product owners. Monetization Opportunities Retention is a litmus test for the health and longevity of digital products. It not only reflects user satisfaction but also influences a product's sustainability, growth, and profitability. By actively monitoring retention rates, businesses can adapt, innovate, and build lasting relationships with their user base, ultimately achieving enduring success in the digital landscape. Conclusion We looked into key performance indicators that provide critical insights into a brand's digital strategy for acquiring and retaining users and customers. They provide a comprehensive view of the user journey, from initial interaction and acquisition to ongoing engagement and eventual conversion, allowing businesses to make data-driven decisions that impact both short-term gains and long-term sustainability. These indicators are critical for marketers in allocating resources, fine-tuning campaigns, and ultimately building a thriving, customer-centric enterprise in today's dynamic business environment.

Acquisition, Conversion, Engagement, and Retention: Essential Metrics to Track Business Growth

Hi All! Here is my weekly email discussing mental models, performance, business and entrepreneurship. What’s in today’s newsletter? We're bad at prioritization because we spread efforts uniformly rather than embracing non-uniformity. This leads to wasted time and missed opportunities. Using the 80/20 principle helps optimize productivity by quantifying contribution skews. Measuring to find your vital 20% inputs generating 80% outcomes guides strategic resource allocation. Ruthlessly focusing time and money on high-impact 20% activities accelerates business growth and life fulfillment. Say no to equality obsession. Embrace natural patterns guiding efficiency to transform your future. The Almighty Power of the Few This idea stemmed from a trip to a friend’s house on a cold January morning back when I was still living in Toronto. I came across a passage by Steve Jobs that got my mind buzzing: “People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully.” I sat staring at those words trying to really digest them, when my friend’s 6-year-old son came running into the room... “Scott, Scott! Wanna see me count to 100?” My initial gut reaction was irritation at having my deep contemplation interrupted and fear that I wouldn’t get another quiet moment all morning. But suddenly it hit me— I should focus on what really matters. I eagerly smiled, “I’d LOVE to see you count! Show me!” I could tell my enthusiasm made his day. He counted proudly all the way to 100. It was pure magic and reminded me that some of life’s most glorious moments require little effort. The seeds for today’s article were planted in that moment. I couldn’t shake the lingering question: How do you determine what to focus on and what to say no to? It’s funny how you can read as much as you want, but when you experience the insight first hand, in your own life - it imprints on your mind in a fascinating way. I went home later that afternoon with a burning drive to study the world’s greatest creative geniuses to uncover their secrets. What hidden laws of the universe did they tap into to achieve such monumental success? HOW do they know what really requires your focus vs. what is wasting your time (and your life). Over the following months, I discovered a fascinating pattern that traces back over 100 years. This pattern is a powerful tool you can apply to optimize EVERY area of life and work. The Almighty Power of the Few In the early 1900s, Italian economist Vilfredo Pareto stumbled upon a peculiar trend... He noticed that 80% of Italy’s land belonged to just 20% of the population. He found similar skewed patterns with wealth distribution—a wealthy few always rise to the top. This trend was quickly observed in other domains: 80% of pea plants came from 20% of pea pods 80% of sales came from 20% of clients 80% of errors came from 20% of bugs in software programs 80% of decisions are made in 20% of meeting times The implications were clear... Results don’t come evenly spread—they come in chunks—massive chunks. The majority of the effects come from a tiny slice of the causes. Pareto’s Principle: The 80/20 Rule The pattern Pareto spotted became known as the Pareto Principle, or more commonly, the 80/20 Rule: 80% of results come from 20% of causes. Of course, the ratio doesn’t have to be strict 80/20 across every case—it can be 70/30 or even 90/10—the core relationship remains the same... The majority of outcomes are produced by the vital few inputs. Let’s look at a classic example... If you make a ranked list of all your Instagram friends based on the number of likes and comments when you post, you’ll find a very skewed pattern. Your top 10 or 20 closest friends will generate 80%+ of all engagement on your posts, while the other few hundred hardly engage at all. A few hyper-engaged friends drive the majority of results. These types of insanely skewed, “long-tailed” distributions with power law properties are EVERYWHERE. The implications of this are profound... Effort is Grossly Unequal to Results If results stem from very few vital causes, two critical insights emerge: You should devote the bulk of your time/resources to the vital few high-impact items. Go where the “results rich” hang out. It takes tremendous patience and persistence because it can be a long journey to find that pocket of high-impact causes. Many novice content creators/bloggers/writers/podcasters/influencers get demotivated when they spend hundreds of hours producing content, but get little traction for months. Then suddenly, one post goes viral and brings in more traffic than all previous posts combined! Rather than see this as luck or randomness, it reflects the Pareto principle’s “long-tail” effect—results come in concentrated chunks. This pattern appears in all creative domains: 20% of customers drive 80%+ of Apple’s iPhone sales 20% of bugs cause 80%+ of software crashes 20% of marketing campaigns drive 80%+ of leads The choice is evident—go where the results rich hangout. But this isn’t always intuitive... For example, I recently helped my friend strategize how to grow his channel. YouTube He was creating 2 detailed videos per week and struggling to gain any traction after months of effort. I studied his data and noticed one shorter, simpler video was massively outperforming the others, generating 80% of his total channel views. We determined he should shift his focus to creating more of that specific, high-performing content. By doubling down on what worked, his views skyrocketed 10X in three months! This story isn’t unique. The most successful YouTubers, bloggers, and entrepreneurs all heavily leverage the Pareto principle... They aren’t continuously trying new things. They double, triple, and quadruple down on their few vital areas generating the best results. Impact Blockers It would make sense to wonder why we don’t naturally optimize for these high-output tasks. Well, we’re only human and we fall into traps. Two tendency traps, in particular, that hamper 80/20 progress - stubbornness and fear. Stubbornness convinces us that even after trying something 1000 times with little results, maybe attempt #1001 will prove the breakthrough. So we persist in wasting energy banging our heads against the same approach because it feels safe and familiar. Fear also sabotages doing the vital work accounting for 80% of our goals. We clearly see different strategies would create exponentially bigger results. But those superior paths intimidate feeling outside our comfort zones. So we settle for incremental gains from easier tactics, afraid to level up. Both stubbornness and fear blind us from honestly assessing what 20% of work truly moves the needles that matter most. We avoid staring down the fact that much of our busyness is simply rearranging deck chairs on the Titanic, not fundamentally shifting outcomes. When Inputs Don’t Match Outputs Now you may be thinking... Does this mean all the effort I put in is pointless if it doesn’t produce a visible, immediate result? Not at all! This principle doesn’t imply wasted effort—it demonstrates that input effort doesn’t linearly map to output results. There are many invisible benefits gained from sustained effort that don’t immediately generate measurable gains like money or recognition. Here are a few examples: Knowledge and Skill Development Learning complex material heavily taxes your mental abilities at first even though you don’t have visible skills to show for it. Like muscle memory, knowledge, and skill grow slowly through sustained practice. Increasing Luck Surface Area Effort over many months lowers the activation energy needed to catalyze a breakthrough. You can’t get lucky if you don’t sustain the effort to place yourself in the opportunity’s way. Stoking Motivation and Momentum Small daily progress triggers vital neurochemicals to sustain motivation. Progress momentum snowballs over time until you cross an impact threshold. In short, it takes tremendous patience and grit to find and penetrate that 20% “impact zone”. Sustained effort doesn’t ensure an immediate breakthrough, but it prepares the soil for the seeds of opportunity. This brings us to an important question... When Do I Pivot vs Persevere? Let’s say you identified writing as a creative strength and have been writing consistently with no monetary results for a year. At what point do you determine writing isn't a high-impact activity for you and pivot to something else? Or perhaps the type of content you’re writing on isn’t a niche that’s really growing quickly. When do you throw in the towel? This is tricky. Premature pivoting can rob you of potential hidden long-term gains whereas persevering down an unfruitful path breeds frustration (and will at times, lead to a Sunk Cost Fallacy). Here is a litmus test I use with entrepreneurs I’m advising to assess if an area has high-impact for them: potential Am I energized by the ACTIVITY itself or just the expected RESULT it will bring? Writing brings me great joy regardless of external measures of success. The process energizes me. If monetary rewards never come, I’d still benefit from the challenge, flow, and sense of progress it provides. However, I despise manually inputting spreadsheet data. Even if it brought great rewards, I'd dread that activity. So, assess if your effort stems from intrinsic enjoyment or purely extrinsic motivations. Sustained effort requires deep engagement in the process. Sustained effort + feedback loops + execution of learnings are required to uncover these high-impact opportunities. Additionally, you should constantly be running small experiments to validate your direction. See if you can monetize your writing in simple ways like freelancing, paid guest posts, or affiliate commissions. Micro-wins sustain motivation even if you haven't had the big breakthrough yet. So in summary: Deeply examine if the ACTIVITY brings intrinsic rewards regardless of the external RESULT it produces. Run small experiments to get empirical validation that confirms you’re on a promising track. You’re going to need to stick it out to get to those big breaks. They rarely come early. Micro-wins stoke motivation while also gathering data to support perseverance. Now that we covered WHEN to persevere, let’s examine WHERE to devote focus... 80/20 Prioritization The Pareto principle isn’t just a descriptive model explaining cause and effect skews—it’s also a prescriptive tool to optimize how we spend time and resources. Track quantitative data to benchmark performance. Identify your 20% power inputs across categories: What % of sales come from top 20% customers? - Customers: What's the split of revenue per product? - Products: Which pages or posts generate most traffic? - Web Pages: Which app features drive engagement? - Features: Who are your top 20% email contacts or callers? - Emails/Calls: Get granular with metrics to surface concentration patterns. The 20% will vary per business - data reveals where yours hide. Here’s an example of how to apply a simple 3-step process to achieve 80/20 prioritization: The example will be re. website traffic sources, but also understand this framework and exercise can be applied to anything in your personal or professional life. Website Traffic Sources The 80/20 principle states 80% of traffic comes from 20% of sources. Let's optimize productivity for traffic: one site's Step 1: Measure To Find Vital 20% Breakdown traffic sources and tally % of total visits per source: Google and Email drive 70% of total traffic - the vital 20% sources. Step 2: Rank Sources By Traffic Prioritize sources by traffic %, highest at top: Google Search - 40% Email - 30% Social Media - 20% Direct - 10% Step 3: Proportion Traffic Building Effort Spend time improving sources aligned to traffic ranking: 40% on SEO to boost Google rankings 30% on optimizing Email captures 20% on Social strategy 10% on Direct channels This example optimizes website productivity. But the - substitute "Sales Revenue", "App Engagement" etc to focus your vital 20% inputs. framework can guide other business functions Obsess over site visitors, customers and activities generating the most impact.  Say no to 'equal attention fallacy'. 80/20 prioritization allows you to maximize outcome impact from your limited input effort. Make the vital few your obsessive focus. Apply 80/20 Analysis To Business & Life Now you've seen how 80/20 prioritization works - go run this analysis on your business and also your life. In business, dig into data and metrics to find: Your 20% power customers Your 20% high-sales products Your 20% most engaged users Your 20% traffic-driving marketing channels In life, tally and rank to uncover: Your 20% activities generating 80% of joy Your 20% friends/family providing 80% of support Your 20% habits driving 80% of health outcomes Find your vital 20% across ALL categories. Those are your priorities for ruthless focus. Whether growing a business or living a rewarding life, 80/20 analysis spots high-impact areas for optimization. Stop spreading yourself thin trying to make everything uniform. Embrace non-uniformity like nature does. Create your vital few game changers in business and life realms. When you match effort to impact, the magic happens. Work with natural efficiency patterns rather than against them. So go analyze now. Discover and create your vital 20% and transform your future. The leverage and fulfillment awaiting you are endless. Please subscribe to my or newsletter. Or, email me at scott@scottdclary.com or at me and I’ll do my best to get back to everyone! If you enjoyed this article, I’d love to hear from you. weekly daily tweet @ScottDClary Also published here. Lead image by Austin Distel on Unsplash

The Few Will Rule Over the Many: How the 80/20 Rule Can Transform Your Life

অল্প কয়েকজন অনেকের উপর শাসন করবে: কীভাবে 80/20 নিয়ম আপনার জীবনকে পরিবর্তন করতে পারে

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BOILER FEED WATER

What is the Case of #Binance and #CZ with the U.S. Department of Justice, and How Does It Affect Cryptocurrencies Including Bitcoin? In-Depth Analysis: Unraveling the Binance Saga – Impact on Crypto Dynamics, CZ's Exodus, and the Ripple Effect on Bitcoin The Binance saga, marked by legal tumult, hefty fines, and leadership upheaval, sends shockwaves through the crypto industry, emphasizing the imperative for robust regulatory compliance and sparking debates on the delicate balance between innovation and accountability in the evolving digital asset landscape. In-Depth Analysis: Unraveling the Binance Saga – Impact on Crypto Dynamics, CZ's Exodus, and the Ripple Effect on Bitcoin Prepare for a deep dive into the labyrinth of legal woes ensnaring Binance, the crypto behemoth, as it faces off with the formidable U.S. Department of Justice. This exposé will unravel the intricacies of the case, dissecting its far-reaching implications on the broader crypto landscape, with Bitcoin caught in the crossfire. Prelude to the Legal Quagmire Binance, once the unrivaled champion in cryptocurrency exchanges, finds itself thrust into the limelight for all the wrong reasons. Forget the bullish market moves; the headlines now scream allegations of illicit financial activities. The U.S. Department of Justice has trained its legal crosshairs on Binance, accusing it of a litany of offenses, ranging from a lack of proper anti-money laundering (AML) protocols to turning a blind eye to its role as an unwitting conduit for nefarious actors. What transpired is nothing short of a legal spectacle, painting a grim tableau for Changpeng Zhao, the charismatic face of Binance, known simply as "CZ." The allegations span a spectrum of financial transgressions, from failure to implement robust AML practices to serving as an unwitting accomplice in funneling billions for terrorists and hackers. The gravity of these accusations has prompted a seismic response from U.S. regulators, leading to a watershed moment for both Binance and its once-revered leader. Binance's Compliance Quandary Binance's meteoric rise in the crypto sphere has been eclipsed by its glaring lapses in regulatory compliance, particularly in the AML domain. The U.S. prosecutors' spotlight exposed how Binance's lax AML measures morphed it into a haven for shadowy financial dealings. The glaring lack of regulatory adherence facilitated users to traverse its platform with minimal scrutiny, inadvertently fostering a breeding ground for criminal exploits. Of particular concern was Binance's unwitting role in aiding and abetting money laundering for terrorist outfits. Shockingly, the U.S. Treasury revealed instances where Binance became a conduit for funds directed towards groups like Hamas, leveraging crypto transactions to fund activities jeopardizing U.S. national security. The litany of Binance's transgressions extended to violating sanctions, with the exchange admitting to facilitating transactions worth approximately $900 million for individuals in sanctioned regions like Iran, Syria, Cuba, and conflict zones in Ukraine. The U.S. Department of Justice minced no words in condemning Binance's negligence, emphasizing the potential threats posed to national security. The fallout from these revelations resulted not only in hefty fines but also cast a pall over the entire crypto community, subjecting it to intensified regulatory scrutiny globally. Admission, Penalties, and the Resignation of CZ In a dramatic turn of events, Binance and CZ found themselves at the mercy of U.S. prosecutors, admitting to criminal charges. The admission exposed the chinks in Binance's armor, laying bare its failure to establish and maintain an effective AML program. The consequences were severe – a staggering $4.3 billion fine for Binance, etching its name in the annals of U.S. legal history, and a personal fine of $50 million for CZ, coupled with his enforced resignation. This seismic shift in Binance's trajectory signals a turning point, underscoring the stark repercussions of flouting regulations in the digital asset realm. The penalties levied against Binance and CZ send an unequivocal message to the industry – non-compliance with U.S. laws carries a hefty financial toll. The Fallout on Binance's Operations The aftershocks of Binance's legal maelstrom reverberated swiftly through its operations and market standing. The trust quotient among its user base experienced a seismic tremor, triggering a reevaluation of loyalties. While it's noteworthy that, as of the current revelations, user funds remain secure, the exodus of approximately $805 million from Binance within 24 hours paints a picture of caution among investors. The baton of leadership has now passed to Richard Teng, Binance's new CEO. Tasked with navigating the tempest, Teng faces the uphill battle of restoring the exchange's tarnished image. Binance's redemption plan encompasses a meticulous overhaul of internal procedures, fortification of transaction monitoring systems, and a commitment to erecting an impregnable AML infrastructure. Binance's pledge to collaborate closely with regulatory bodies in a bid to rectify past lapses forms a linchpin of its rehabilitation strategy. The path ahead demands not only the implementation of corrective measures but also a concerted effort to rebuild global customer trust. As the crypto market convalesces from recent upheavals, Binance's ability to align with regulatory expectations will be closely scrutinized. The saga unfolds as a litmus test, shaping Binance's trajectory in the evolving landscape. The Ripple Effect on the Crypto Cosmos The Binance conundrum injects fresh vigor into global debates on crypto regulations, triggering reverberations across the crypto cosmos. The meticulous dissection of Binance's transgressions and the subsequent punitive measures underscore an imperative need for a robust regulatory framework in the crypto sector. Regulators, armed with newfound assertiveness, are poised to demand heightened accountability, transparency, and adherence to traditional financial security norms. The surge in regulatory scrutiny signals an end to the laissez-faire ethos, positioning regulators as custodians holding sway over exchanges and crypto entities. The overarching theme is a call for more stringent AML and KYC policies, heralding a regulatory landscape characterized by increased oversight. The timeframe of 2024-2025 emerges as a potential juncture for heightened regulatory interventions. The hitherto celebrated autonomy and decentralization intrinsic to cryptocurrencies now stand at a crossroads, subject to reevaluation within the confines of legal frameworks and consumer safeguarding. The Binance saga amplifies the delicate balance between nurturing innovation in the digital asset space and the imperative for regulators to shield the financial system from illicit machinations. Denouement – Navigating the Crossroads Under the stewardship of Richard Teng, Binance's future navigates the waters of cautious optimism. Teng, armed with regulatory acumen, positions Binance to respond adeptly to compliance imperatives. The company's willingness to align with regulatory mandates and foster collaboration forms the linchpin for regaining its foothold in the financial arena. As Binance charts its course through choppy regulatory waters, the precedent set by this saga casts a long shadow over the crypto industry's governance. The heightened regulatory scrutiny, while injecting short-term uncertainties, could metamorphose into a market where investor protection is paramount, and institutional participation is incentivized. The silver lining in Binance's loss of market share could potentially be a boon for other exchanges and their tokens. The evolving dynamics prompt a strategic reevaluation, with the possibility of creating a basket of these exchange tokens gaining traction. This announcement underscores not investment advice but a window into my decision-making process, emphasizing the cardinal rule of conducting individual research. As the crypto landscape matures, the symbiotic relationship between regulatory compliance and innovation becomes increasingly evident. The industry's trajectory hinges on its adaptability to regulations without stifling the pioneering spirit that fueled its inception. In Conclusion: The Binance saga unravels as a saga of reckoning, marking a paradigm shift in the crypto narrative. Richard Teng holds the reins in steering Binance's course, with the specter of regulatory scrutiny shaping the industry's future. The intricate dance between compliance and innovation, epitomized by Binance's tribulations, underscores a pivotal chapter in the evolution of digital assets. As the dust settles, the crypto cosmos awaits its fate, oscillating between regulatory conformity and the enduring quest for technological progress.

In-Depth Analysis: Unraveling the Binance Saga

Scientific American Supplement, No. 392, July 7, 1883 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . VINEGAR. here VINEGAR. Hermann Kratzer, of Leipsic, communicates the following practical information on the clarification and purification of vinegar to the Neueste Erfindungen und Erfahrungen: If vinegar has an unpleasant odor, which is rarer now that the vinegar manufacture has reached such a state of perfection, it may be removed as follows: Well burned and finely pulverized wood charcoal is put into the bottles containing the vinegar, the proportions being 8 grammes of charcoal to a liter of vinegar, or one ounce to the gallon. It is shaken several times very thoroughly, then left standing three or four days, and the vinegar filtered through a linen cloth. Vinegar treated in this manner will be found to have completely lost its unpleasant odor. I have found that when I used blood charcoal or bone coal in place of wood coal it was still more efficient; but it must be mentioned that when they are used they must be purified as follows before using: Charcoal from blood contains potash and hence it is necessary to wash it with distilled water and dry it before using it. Bone coal (also called bone black, animal charcoal, etc.) contains on an average 10 per cent. of nitrogenous and hydrogenated carbon, 8 per cent. of carbonate of lime, 78 per cent. of phosphate of lime, besides phosphate of magnesia, sulphate of lime, soluble salts, etc. Before using, it should be treated with dilute hydrochloric acid until it does not effervesce any more. The bone coal is then left to stand for 24 or 30 hours and at the end of this time is washed with distilled water until the wash water no longer reddens a blue piece of litmus paper, i.e., until every trace of hydrochloric acid has been removed from the bone coal. Wood charcoal may be treated in like manner. When this coal is perfectly dry it is employed in the same proportions as the other, 8 to 1,000, the operation being exactly the same. He turns next to the clarification of the vinegar. It happens everywhere that vinegar instead of being clear is sometimes turbid. This is due to particles of yeast dissolved in the vinegar that have not yet settled. To remove this kind of turbidity it is customary to use oak or beech shavings that have been washed in hot water and then dried. These shavings, which must be very long and extremely thin, are put in a barrel with a second and perforated bottom, to a depth of 12 to 34 inches. The vinegar that runs through them deposits its slimy constituents on the shavings and becomes perfectly clear, and presents to the eye a pleasing appearance. To this generally known method I would add a few more: I take a ½ kilo of well pulverized animal charcoal (black burned bones) to 7/8 of a hectoliter of vinegar (1 lb. to 20 gallons), and stir it well with a wooden rod; or, if the vinegar is in bottles, I shake it a long time after putting the animal charcoal in the bottle, and repeat it several times. After three or four days I finally filter the vinegar through linen, when the filtrate will exhibit the desired clearness. The best way to clarify vinegar is with isinglass. It is first broken up, then swelled for a day in vinegar (17 or 18 grammes to the liter), then 2 liters of vinegar are added and the mass boiled until the isinglass is completely dissolved. Such a solution as this (½ ounce to 3 quarts) is mixed with 10¼ hectoliters (250 gallons) of turbid vinegar and well stirred through it. After the expiration of five or six weeks vinegar treated in this way has a beautifully clear appearance. Albumen can likewise be used to clarify it. The vinegar is boiled with the albumen until the latter is completely coagulated, and then the vinegar is filtered. And finally milk may be employed. For this purpose the milk is skimmed, and 1 quart of milk added for every 68 quarts of vinegar, the mixture well stirred and shaken. After the caseous portion has coagulated (curdled) it is filtered as before, and in this case, too, the product is a fine, clear vinegar. We believe that these few experiments, so easily performed, and at so small an expense, will prove useful to our readers in enabling them to put their product in the market in an excellent condition and nicely clarified. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2005). Scientific American Supplement, No. 392, July 7, 1883. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/8742/pg8742-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

The following practical information on the clarification and purification of vinegar

Web3 builders are only starting to realize the importance of sustainable and meaningful web3 marketing. There are web3 marketing companies and tools that are now helping web3 projects achieve traction. Another aspect of web3 that’s growing rapidly is the involvement of more women in this space. To discuss all of this, I had the opportunity to interview Victoria Vaughan, the co-founder of a marketing and PR firm InCryptoLand and the former CEO of Cointelegraph. Let’s dive in. Q. Hello Victoria, it’s great to be talking with you. Can you please introduce yourself, and share your professional journey with our readers? Hello, and thank you for having me! I'm Victoria Vaughan, and I am a co-founder of , a premier PR and marketing agency for the Web3 and tech sectors. InCryptoland My journey in Web3 started about nine years ago when I dived into the digital asset and blockchain world. I joined the Cointelegraph team as a project manager. Later, I was promoted to CEO and successfully grew the company to over nine million monthly readers across 10 languages. Impressive, right? But it's a team effort, trust me! Along the way, I've collaborated with some of the industry's most influential brands like Coinmarketcap, Etoro, Moonpay, and OKX. These collaborations expanded my expertise in growth hacking, marketing, and business development. Before all this blockchain excitement, I was deeply rooted in the tech scene, working for a tech startup as a product manager. So, you can say I've seen the industry from various angles, which has been super helpful in my current role as a tech PR agency co-founder. Q. Before we talk about InCryptoland, tell us how Web3 marketing agencies can solve the problems that Web3 companies face. Are PR firms an essential component of the Web3 ecosystem? If so, why? Yes, I think PR firms are absolutely essential in Web3. In a highly competitive blockchain ecosystem, you need a specialized marketing strategy. A tech-savvy PR agency can connect you with the right partners and investors while providing you with crucial media coverage. This makes the path to deal-closing and client acquisition much smoother. But it’s more than just PR. Crypto marketing agencies bring in a whole arsenal of growth hacking techniques. We're talking Twitter spaces, Discord AMAs, and some strategic Twitter shilling to grow your followers with minimum spend. Plus, a robust content marketing campaign can kill two birds with one stone: it boosts your SEO ranking and educates potential clients, essentially greasing the wheels for your business development. And let's not overlook the value of expertise. An experienced crypto marketing team brings a wealth of knowledge to your project, helps you sidestep common pitfalls, and executes effective campaigns. They've got connections too; a trusted network of influencers and partners that can take your project visibility to another level. Working directly with influencers can be a hit or miss, but agencies can pick the right ones to amplify your message. So, all in all, it's a win-win. Q. The volatile crypto market makes it difficult to run any Web3 company. How should someone build a team, develop a strategy, and make a Web3 marketing company successful? I totally get what you're saying about the rollercoaster ride that is the crypto market. So, first and foremost, you've got to be nimble with your financial planning. The ups and downs are wild; some companies go on a hiring spree in a bull market and then, bam, they're toast in a bear market. The key is to stay agile and adjust your strategy in real-time based on market conditions. On the subject of teams — I think a strong team is non-negotiable. You want a mix of people who are deep into Web3 but also some who come from more traditional sectors. That blend can help you craft a balanced strategy that's got both innovation and tested wisdom. Partnerships are the cherry on top; they bring cross-marketing opportunities and long-term support, which are gold in this fast-paced landscape. Now, the bear market isn't just about surviving; it's a land of opportunity. Companies that stay transparent and keep the conversation going with their community during the rough patches end up building trust and credibility. Not to mention, PR and marketing opportunities actually multiply. News outlets are more receptive, influencers are keen to partner, and the advertising costs are generally lower. So, it's all about turning challenges into stepping stones, really. Q. Tell us about InCryptoland and how it helps Web3 businesses. What are the fundamental working principles of your marketing agency? InCryptoland focuses on organic PR campaigns, social media management, and community growth. Our agency also developed a wide network of selected channels for media buy campaigns. What really excites us is collaborating with founders with a burning passion for meaningful causes and advanced technology products. For their PR campaigns, the strategy leans heavily into authentic storytelling that resonates with the audience and highlights the expertise of the team. ICL's guiding principles are Drive, Excellence, and Commitment. These principles really shape the way we approach each project. From crafting the ideal PR pitch to building up a strong community around a client's vision, our aim is to give it our all. We're continually seeking the best opportunities for reaching audiences and driving engagement in this fast-paced Web3 landscape. And speaking of capturing attention, our clients have been featured in the most recognized high-profile publications, like the New York Times, WSJ, Associated Press, USA Today, Cointelegraph, and Coindesk. So, we know a thing or two about getting a story out there in a way that strikes. Our experience spans different verticals of Web3 from DeFi to NFTs, infrastructural protocols to AI, and general tech. This helps us to know what works and what doesn’t. We use these insights to help clients avoid common mistakes in their communications and focus on effective strategies instead. Q. You’ve been working in the Web3 space for almost a decade. What has been your experience as a woman in Web3? Do you have any suggestions and advice for budding women entrepreneurs in the Web3 domain? There is no doubt that navigating the Web3 space as a woman has its own unique challenges. While the industry is generally welcoming, the large networking events can sometimes feel like "boy's clubs." You often have to break the ice yourself, put your expertise on display, and then—finally—you get taken seriously. I've had my fair share of awkward moments where people thought I was there to just hand out flyers. But the silver lining? As you broaden your network, each event becomes easier. The faces get familiar, introductions happen more naturally, and the atmosphere becomes genuinely inviting. The evolving role of women in Web3 is so exciting to watch. There's more to this space than just crypto and blockchain; we're seeing women lead the charge in areas like digital art, fashion, and health. For instance, the rise of NFTs has been a game-changer, especially for female artists. They're not just participating; they're shaping the narrative, moving the industry beyond just financial applications. Advice for budding women entrepreneurs? First, find your tribe—initiatives like WOW, Mybff, and Boy's Club are doing awesome work in enhancing women's awareness of the industry. Second, don't be discouraged by the technical jargon and male-centric vibes; there's room for everyone's talent here. Organizations like UnicornDAO and AthenaDAO are setting brilliant examples by focusing on inclusivity and women's health. Lastly, for the industry itself, the roadmap to diversity is clear: more shared stories, women-centric educational platforms, and an unequivocal commitment to diversify from the top down. Let's keep that conversation going. Q. Do you have any last comments on the current state of the Web3 industry? Where do you see it in the next three to five years? What will be the role of Web3 marketing firms in the coming years in shaping the overall industry? Honestly, the bear market often acts like a litmus test. It separates those who are genuinely committed to building something meaningful from the ones who are just riding the hype train. Remember, some of the most groundbreaking companies were born during downturns. Looking forward, regulation is inevitably coming down the pipeline. And while some might see that as a damper, I think it'll actually make the industry less of a wild west, which could attract more serious investment and innovation. We're already seeing AI making inroads into Web3, and that's a trend I only expect to accelerate. I also believe the infrastructural projects will grow a lot during the next several years. They're the bedrock that'll support the flashy apps and services everyone loves. So, where do Web3 marketing firms fit into all of this? As the industry matures, the role of specialized marketing agencies will only become more crucial. They'll help navigate the regulatory landscape, tap into AI's potential, and spotlight those infrastructural gems. Essentially, we'll be the architects of perception, shaping how the world views and engages with Web3.

Importance of Web3 Marketing and Women in Web3: An Interview With Victoria Vaughan

Web3 মার্কেটিং এবং Web3 তে নারীর গুরুত্ব: ভিক্টোরিয়া ভনের সাথে একটি সাক্ষাৎকার

Bedeutung von Web3-Marketing und Frauen in Web3: Ein Interview mit Victoria Vaughan

Importancia del marketing Web3 y las mujeres en Web3: una entrevista con Victoria Vaughan

Importance du marketing Web3 et des femmes dans le Web3 : une entrevue avec Victoria Vaughan

वेब3 मार्केटिंग का महत्व और वेब3 में महिलाएं: विक्टोरिया वॉन के साथ एक साक्षात्कार

Web3 マーケティングと Web3 における女性の重要性: Victoria Vaughan へのインタビュー

Web3 마케팅의 중요성과 Web3에서의 여성: Victoria Vaughan과의 인터뷰

Importância do marketing da Web3 e das mulheres na Web3: uma entrevista com Victoria Vaughan

Важность маркетинга Web3 и женщины в Web3: интервью с Викторией Вон

Web3 Pazarlamanın Önemi ve Web3'te Kadın: Victoria Vaughan ile Bir Röportaj

Tầm quan trọng của tiếp thị Web3 và phụ nữ trong Web3: Cuộc phỏng vấn với Victoria Vaughan

Web3 营销和 Web3 中的女性的重要性：维多利亚·沃恩 (Victoria Vaughan) 访谈

One of my favorite interview prompts is, "In as much detail as you can, tell me what happens when you hit enter after typing a domain in the URL bar?" This seemingly basic question is a litmus test. It reveals the depth and breadth of a candidate's understanding of our digital ecosystem. From DNS lookups to the TLS handshake, from CDN optimizations to browser rendering - this prompt touches multiple domains (pun intended) of web technology. It's a probe into the unseen layers beneath our digital interactions. It allows the candidate to dive as deep as they want in areas they understand and skim over others that remain, to them, opaque. But more importantly, it sparks a conversation about something in which we (hopefully) both have an interest. The Gap in Our Magic It's always intriguing, and sometimes a bit alarming, to witness seasoned developers stumble over this question. They find themselves on uncertain ground, hesitating as they try to piece together the puzzle. They might wonder, "What exactly does the interviewer want to hear?" Developers have been hard at work, crafting tons of code, meticulously refining solutions, and making sure that systems scale seamlessly. However, there seems to be a mysterious oversight. Their expertise has burrowed so profoundly into a single domain they unintentionally overlook the multitude of other cogs in the machine that transform an ordinary URL into a beautifully rendered webpage. So, why is there such a chasm? Why do so many overlook the magic happening outside their specialized sandbox? The Pitfalls of Not Knowing Our industry has become increasingly complex. And with complexity comes the need for compartmentalization, especially as organizations scale. Developers often rely on other departments, third-party tools, automated processes, or platforms to handle tasks outside their core expertise. This reliance breeds a certain level of ignorance. But there are dangers in not understanding the broader landscape: When developers lack insight into how the entire system interacts, it can lead to unexpected performance bottlenecks. Understanding the journey from server to browser can lead to more informed decisions about optimization. Performance Woes: Every interaction, from the DNS lookup to the TLS handshake, can be a potential vulnerability. Not understanding these processes can inadvertently expose applications to threats. Security Gaps: A developer who understands only their piece of the puzzle might struggle when trying to integrate their work into a larger system or when collaborating with other teams. Integration Challenges: Bridging the Knowledge Gap While it's unrealistic to expect every developer to become an expert in every facet of technology, there's a middle ground. Developers can strive to: Taking the time to understand the basics of areas outside one's specialty can be immensely beneficial. This doesn't mean becoming an expert but rather gaining a holistic view of the system. Educate Themselves Broadly: Actively seeking input from colleagues in different roles can provide fresh insights and uncover potential challenges before they escalate. Engage in Cross-functional Collaboration: The tech world is ever-evolving. Regularly revisiting foundational concepts and updating knowledge ensures that a developer doesn't get left behind. Continuously Learn: Wrapping Up Our technological world thrives on a balance of specialization and holistic understanding. As developers, while it's essential to deep-dive into specific areas, it's equally crucial to surface now and then to see the bigger picture. The true magic isn't just in the code we write or the systems we design but in understanding the interconnection that brings a digital idea to life. Embrace that magic, and you'll find yourself better equipped to navigate the multifaceted universe behind every press of the "Enter" key. Also published . here

Navigating the Unknown: What Happens After You Hit 'Enter'

105 Stories To Learn About K8s

Investors see thousands of business plans each year, even in this down market. Apart from a referral from a trusted source, the business plan is the only basis they have for deciding whether or not to invite an entrepreneur to their offices for an initial meeting. With so many opportunities, most investors simply focus on finding reasons to say no. They reason that entrepreneurs who know what they are doing will not make fundamental mistakes. Every mistake counts against you. This article shows you how to avoid the most common errors found in business plans. Content Mistakes Failing to relate to a true pain Pain comes in many flavors: my computer network keeps crashing; my accounts receivable cycle is too long; existing treatments for a medical condition are ineffective; my tax returns are too hard to prepare. Businesses and consumers pay good money to make the pain go away. You are in business to get paid for making pain go away. Pain, in this setting, is synonymous with market opportunity. The greater the pain, the more widespread the pain, and the better your product is at alleviating the pain, the greater your market potential. A well written business plan for a startup places the solution firmly in the context of the problem being solved. Value inflation Phrases like “unparalleled in the industry;” “unique and limited opportunity;” or “superb returns with limited capital investment” – taken from actual documents – are nothing but assertions and hype. Investors will judge these factors for themselves. Lay out the facts – the problem, your solution, the market size, how you will sell it, and how you will stay ahead of competitors – and lay off the hype. Trying to be all things to all people Many early-stage companies believe that more is better. They explain how their product can be applied to multiple, very different markets, or they devise a complex suite of products to bring to a market. Most investors prefer to see a more focused strategy, especially for very early-stage companies: a single, superior product that solves a troublesome problem in a single, large market that will be sold through a single, proven distribution strategy. That is not to say that additional products, applications, markets, and distribution channels should be discarded – instead, they should be used to enrich and support the highly focused core strategy. You need to hold the story together with a strong, compelling core thread. Identify that, and let the rest be supporting characters. No go-to-market strategy Business plans that fail to explain the sales, marketing, and distribution strategy are doomed. The key questions that must be answered are: who will buy it, why, and most importantly, how will you get it to them? You must explain how you have already generated customer interest, obtained pre-orders, or better yet, made actual sales – and describe how you will leverage this experience through a cost-effective go-to-market strategy. “We have no competition” No matter what you may think, you have competitors. Maybe not a direct competitor – in the sense of a company offering an identical solution – but at least a substitute. Fingers are a substitute for a spoon. First-class mail is a substitute for e-mail. A coronary bypass is a substitute for an angioplasty. Competitors, simply stated, consist of everybody pursuing the same customer dollars. To say that you have no competition is one of the fastest ways you can get your plan tossed – investors will conclude that you do not have a full understanding of your market. The “Competition” section of your business plan is your opportunity to showcase your relative strengths against direct competitors, indirect competitors, and substitutes. Besides, having competitors is a good thing. It shows investors that a real market exists. Too long Investors are very busy and do not have the time to read long business plans. They also favor entrepreneurs who demonstrate the ability to convey the most important elements of a complex idea with an economy of words. An ideal executive summary is no more than 1-3 pages. An ideal business plan is 20-30 pages (and most investors prefer the lower end of this range). Remember, the primary purpose of a fund-raising business plan is to motivate the investor to pick up the phone and invite you to an in-person meeting. It is not intended to describe every last detail. Document the details elsewhere: in your operating plan, R&D plan, marketing plan, white papers, etc. Too technical Business plans – especially those authored by people with scientific backgrounds – are often packed with too many technical details and scientific jargon. Initially, investors are interested in your technology only in terms of how it: Solves a really big problem that people will pay for; Is significantly better than competing solutions; Can be protected through patents or other means; and Can be implemented on a reasonable budget. All of these questions can be answered without a highly technical discussion of how your product works. The details will be reviewed by experts during the due diligence process. Keep the business plan simple. Document the technical details in separate white papers. No risk analysis Investors are in the business of balancing risks versus rewards. Some of the first things they want to know are what are the risks inherent in your business, and what has been done to mitigate these risks. The key risks of entrepreneurial ventures include: Will people actually buy what you have to sell? Will you need to create a major change in consumer behavior? Market risks: Can you actually deliver what you say you can? On budget and on time? Technology risks: What can go wrong in the day-to-day operations of the company? What can go wrong with manufacturing and customer support? Operational risks: Can you attract and retain the right team? Can your team actually pull this off? Are you prepared to step aside and let somebody else take over if necessary? Management risks: Is your intellectual property truly protected? Are you infringing on another company’s patents? If your solution does not work, can you limit your liability? Legal risks: This is, of course, just a partial list of risks. Even though you may feel that the risks are negligible, potential investors will feel otherwise unless you demonstrate that you have given a lot of thought to what can go wrong and have taken prudent steps to mitigate these risks. Poorly organized Your plan should flow in a nice, organized fashion. Each section should build logically on the previous section, without requiring the reader to know something that is presented later in the plan. Although there is no single “correct” business plan structure, one successful structure is as follows: This is the first thing the reader will see, so keep it simple and professional, and be sure to include your contact information so the reader can reach you easily. Cover Page: This is a brief, 1 to 3 page summary of everything that follows in the plan. It should be a stand-alone document, as many readers will make their initial decision based on the executive summary alone. Executive Summary: If you are in a highly specialized field, you should provide some background in layman terms since most investors will not have advanced degrees in your field. Background: Describe how businesses and consumers are suffering, and how much they are willing to pay for a solution. Market Opportunity: Describe what you do, and how your solution fits into the market opportunity. Products or Services: Describe how you have succeeded in attracting customers, marketing and distribution partnerships, and other alliances that demonstrate that experts in your market are betting on your solution. Market Traction: Identify your direct and indirect competitors, and describe how your solution is better. Competitive Analysis: Describe how you will go to market, how you will price your products, etc. Distribution and Marketing Strategy: Identify major sources of risks, and describe how you are mitigating them. Risk Analysis: Showcase a strong past track record, and describe key checkpoints for the future. Milestones: Provide the basic facts about your company – where and when you incorporated, where you are located, and brief biographies of your core team. Company and Management: Provide summaries of your P&L and cash flows, and the assumptions used to come up with these. Also describe your funding needs, how you will use the proceeds, and possible exit strategies for investors. Financials: As stated earlier, there is no “right” structure – you will need to experiment to find the one that best suits your business. Financial Model Mistakes Forgetting Cash Revenues are not cash. Gross margins are not cash. Profits are not cash. Only cash is cash. For example, suppose you sell something this month for $100, and it cost you $60 to make it. But you have to pay your suppliers within 30 days, while the buyer probably won’t pay you for at least 60 days. In this case, your revenue for the month was $100, your profit for the month was $40, and your cash flow for the month was zero. Your cash flow for the transaction will be negative $60 next month when you pay your suppliers. Although this example may seem trivial, very slight changes in the timing difference between cash receipt and disbursement – just a couple of weeks – can bankrupt your business. When you build your financial model, make sure that your assumptions are realistic so that you raise sufficient capital. Lack of Detail Your financials should be constructed from the bottom-up, and then validated from the top-down. A bottom-up model starts with details such as when you expect to make certain sales, or when you expect to hire specific employees. Top-down validation means that you examine your overall market potential and compare that to the bottom-up revenue projections. Round numbers – like one million in R&D expenses in Year 2, and two million in Year 3 – are a sure sign that you do not have a bottom-up model. Unrealistic financials Only a very small handful of companies achieve $100 million or more in sales only five years after founding. Projecting much more than that will not be credible, and will get your business plan canned faster than almost anything else. On the other hand, a business with only $25 million in revenues after five years will be too small to interest serious investors. Financial forecasts are a litmus test of your understanding of how venture capitalists think. If you have a realistic basis for projecting $50-100 million in Year 5, you are probably a good candidate for venture financing. Otherwise, you should probably look elsewhere. Insufficient financial projections Basic financial projections consist of three fundamental elements: Income Statements, Balance Sheets, and Cash Flow Statements. All of these must conform to Generally Accepted Accounting Principles, or GAAP. Investors generally expect to see five years of projections. Of course, nobody can see five years into the future. Investors primarily want to see the thought process you employ to create long-term projections. A good financial model will also include sensitivity analyses, showing how your projected results will change if your assumptions turn out to be incorrect. This allows both you and the investor to identify the assumptions that can have a material effect on your future performance so that you can focus your energies on validating those assumptions. They should also include benchmark comparisons to other companies in your industry – things like revenues per employee, gross margin per employee, gross margin as a percentage of revenues, and various expense ratios (general and administrative, sales and marketing, research and development, and operations as a percentage of total operating expenses). Conservative assumptions Nobody ever believes that assumptions are conservative, even if they truly are. Develop realistic assumptions that you can support, refrain from using the words “conservative” or “aggressive” in your plan, and leave it at that. Offering a valuation Many business plans err by stating that their company is worth a certain amount. How do you know? The value of a company is determined by the market – by what others are willing to pay – and unless you are in the business of buying, selling, or investing in companies, you probably don’t have an acute sense of what the market will bear. If you name a price, one of two things can happen: (a) your price is too high, and investors will toss your plan; or (b) your price is too low, and investors will take advantage of you. Both are bad. The purpose of the business plan is to tell your story in the most compelling manner possible so that investors will want to go to the next step. You can always negotiate the price later. Stylistic Mistakes Poor spelling and grammar If you make silly mistakes in your business plan, what does that say about how you run your business? Use your spelling and grammar checkers, get other people to edit the plan, do whatever it takes to purge embarrassing errors. Too repetitive All too often, a plan covers the same points over and over. A well-written plan should cover key points only twice: once, briefly, in the executive summary, and again, in greater detail, in the body of the plan. Appearance matters At any point in time, an investor has dozens if not hundreds of plans waiting to be read. Get to the top of the pile by making sure that the cover is attractive, the binding is professional, the pages are well laid out, and the fonts are large enough to be easily read. On the other hand, don’t go too far – you don’t want to give the impression that you are all style and no substance. Execution Mistakes Waiting until too late The capital formation process takes a long time. In general, count on 6 months to a year from the time you start writing the plan until the time the money is in the bank. Don’t put it off. Your management team should be prepared to invest about 500 hours into the plan. If you are too busy building your product, company, or customers (which is arguably a better use of your time), consider outsourcing the development of the business plan. Failing to seek outside review Make sure that you have at least a few people review your plan before you send it out – preferably people who understand your market, sales and distribution strategies, the VC market, etc. Your plan may look perfect to you and your team, but that’s probably because you’ve been staring at it for months. Good, objective reviews from outsiders with a fresh perspective can save you from myopia. Overtweaking You could spend countless hours tweaking your plan in the pursuit of perfection. A lot of this time would be better spent working on your product, company, and customers. At some point, you need to pull the trigger and get the plan out in front of a few investors. If the reaction is positive, and they want to move forward, great. If the reaction is negative (assuming that the investor was a good fit to begin with), then you may have been heading down the wrong path. Get feedback from a couple of investors, and if a general consensus emerges, go back and refine your plan. Conclusion It’s a tough investment climate, but good ideas backed by good teams and good business plans are still getting funded. Give yourself the best possible chance by avoiding these simple mistakes.

Why Business Plans Don't Get Funded: Avoid These Business Plan Errors

Por qué los planes comerciales no se financian: evite estos errores del plan comercial

Pourquoi les plans d'affaires ne sont pas financés : évitez ces erreurs de plan d'affaires

व्यावसायिक योजनाओं को वित्त पोषित क्यों नहीं किया जाता: इन व्यावसायिक योजना त्रुटियों से बचें

事業計画が資金調達できない理由: これらの事業計画のエラーを回避する

Por que os planos de negócios não são financiados: evite esses erros no plano de negócios

Tại sao các kế hoạch kinh doanh không được tài trợ: Tránh các lỗi kế hoạch kinh doanh này

为什么商业计划得不到资助：避免这些商业计划错误

You might have already been using some AI writing detectors, but now you wanna know how AI detection works, right? I’m by no means an AI research expert. But let me put my data science experience to go use. I’ll go over the following: What AI detection is What are the techniques involved in training these models Who uses them Other important FAQs What Is AI Detection? AI detection is using sophisticated machine learning and models to help differentiate between human-generated and computer-generated texts. It involves using AI detection software that is trained on established libraries of pre-existing texts to develop predictive algorithms that recognize patterns within new testing data. You’ll then get a probability score indicating whether the assessed material was created manually or through automated means. natural language processing Why Is AI Text Detection Important? AI text detection is important to ensure that information remains reliable, and it’s critical in areas like search engine optimization (SEO), academia, and law. AI content generators are undoubtedly helpful and a must-use to be competitive. But they are also notoriously unreliable. So Google, schools, and clients want to ensure you aren’t just publishing raw content without using your brain. Like can you imagine if people were allowed to: Write about (YMYL) topics without fact-checking. Your Money or Your Life Publish journal articles where the term “peer-reviewed” no longer holds any value. Give generic AI-generated legal advice. There won’t be any more trust. That’s why you need to use these tools because people can’t tell the difference most of the time. How AI Writing Detection Works Alright, let’s dive a little deeper to see what’s really going on under the hood. In a nutshell, there are many different ways these tools work. But here are the 2 main concepts: Examining sentence structure to look for semantic meaning or repetition Linguistic Analysis: Comparison with the training dataset, which looks for similarities with previously identified instances. Comparative Analysis: And these are some of the more common techniques used in training a model to detect AI content using the two concepts above. Classifiers: The Sorting Hat of AI Detection Classifiers kinda operate like Harry Potter’s Sorting Hat, sorting data into predetermined classes. Using machine or deep learning models, these classifiers examine various features like word usage, grammar, style, and tone to differentiate between AI-generated and human-written texts. Picture a scatter plot where each data point is a text entry, and the features will form the axes. Then let’s say we have 2 classes: AI Text Human Text Whatever text you are testing will fall into one of these two clusters. Below is a graphic I made so you can visualize it. The classifier’s job is to form a boundary to separate the 2. Depending on what classifier model was used, some examples include: Logistic Regression Decision Trees Random Forest Support Vector Machines (SVM) K-Nearest Neighbors (KNN) You don’t need to know what these are, but just know they are algorithms that sort data in different ways. Note: That boundary might be a line, curve, or some other random shape. And when you test a new text (data point), the classifier will simply put them in either one of those classes. Embeddings: The DNA of Words What if every word had its own covert code, as though we were watching some exciting spy flick? In (AI) and language comprehension, this is precisely what happens. artificial intelligence These codes are known as embeddings. . Essentially unique DNA for individual words By capturing the core meaning behind each term and understanding how each relates to others in context, these embeddings form a of meaning. semantic web This is done by in an Nth dimensional space and running some fancy computation. It can be 2D, 3D, or 302934809D. representing each word as a vector A vector is a quantity with both magnitude and direction. But for this explanation, just think of it as coordinates on a graph. Note: But why a vector? Because computers don’t understand words. SHOCKING. No serious. That’s why it has to be converted into numbers first through vectorization. Here’s an example of what it might look like in a table. Vectorized text numerical values can take on a wide range of values, not just binary ones (1 or 0). I just made it easier to visualize. Note: And here’s another 2D example of plotting vectors on a graph. I’m sure you can imagine what 3D will look like but don’t ask me to illustrate 4D. No human can tell you, but a computer can do it with the magic of MATH. This is also exactly how Google operates. How do you think you can type something in the search bar and get scarily related results? But what about telling apart text produced by humans versus that generated using AI? We transform all text into their respective embeddings before feeding them to a machine-learning model to be trained. Then without even knowing any actual verbiage itself, it will form all these connections and figure out all the “codes” common with AI-generated text. Cool huh? Perplexity: The Litmus Test for AI-Generated Text Perplexity is a measure of how well a probability distribution or a language model can predict a sample. In the context of AI-generated content detection, perplexity acts as a litmus test for AI-generated text. The lower the perplexity, the more likely the text is AI-generated. It’s like a detective using a fingerprint match to identify a suspect. Here’s a table breaking it down: Perplexity Level Interpretation Example Low (close to 1) The language model is highly confident in its predictions. It’s like a well-read book critic accurately predicting the next word in a novel. A language model trained on medical literature predicting terms in a medical textbook. Medium The language model is somewhat confident in its predictions. It’s like a casual reader making some accurate and some inaccurate predictions about the next word in a novel. A language model trained on general English literature predicting terms in a science fiction novel. High The language model is not confident in its predictions. It’s like a beginner reader trying to predict the next word in a complex philosophical text. A language model trained on sports articles trying to predict terms in a legal document. Burstiness: The Telltale Sign of AI-Generated Text Burstiness is the variation in the length and complexity of sentences generated by an AI model. Picture yourself at a restaurant. The place is filled with various conversations, some loud and boisterous, others quiet and intimate. Just like those conversations, sentences written by humans tend to be unpredictable due to many nuances. But AI models usually produce output that is more uniform in length and complexity, while human writing typically shows more significant variability or ‘burstiness’. AI detectors can flag a text as potentially AI if it notices low variance in sentences: their lengths, structures, and tempos. Here’s a table with some examples. Text Type Example Burstiness Human-written “I love going to the park. The fresh air, the sound of birds chirping, and the sight of children playing always lift my spirits. It’s a place where I can relax and unwind, away from the hustle and bustle of city life.” High (Variation in sentence length and complexity) AI-generated “I like the park. It is nice. The air is fresh. There are birds. Children play there. It is relaxing.” Low (Sentences are similar in length and complexity) Is AI Detection Accurate? I’ll straight up tell you that it’s never 100% accurate, even if the score turns out to be 100%. That’s just the model’s . CONFIDENCE When an AI detector analyzes text, instead of simply deciding between human-written or AI-generated content, it typically calculates scores or probabilities for each based on particular features within said material. classification For instance, let us assume we analyzed some text with our AI detector. It gave us scores of 0.7 for “AI” and 0.3 for “human.” These numbers indicate that our detector has determined roughly a seventy-to-thirty chance (70% vs 30%) that our material falls under one category versus another. Thus deciding ultimately whether one category does or doesn’t apply becomes quite easy. Assigning probability measures rather than leaving things binary offers numerous benefits since it provides insight into how much trust you can place in predictions. There’s more to determining whether a text was written by humans or artificially intelligent tools than just separating them into two categories: “human” and “AI.” If the assessment method used involves calculating probability scores, then how close or far apart these scores are can impact an AI model’s certainty in making predictions. For instance, if there isn’t much difference between the score assigned to an AI-generated piece and one written by humans (like getting scores of 0.51 and 0.49, respectively), then detecting their source will be more challenging compared to cases where their probabilities vary widely (e.g. getting probabilities of 0.9 versus 0.1). So, despite yielding binary results, this decision involves detailed analysis relying heavily on the difference in probability scores. You might see other articles discussing how AI detectors work by calculating the likelihood of each word being the next predicted word or temperature. They got the search intent completely off. Note: That refers to how AI writers work, not AI detectors. That was quite a long paragraph, but that’s the best I can explain it. What Is the Future of AI Content Detection? As we witness further evolution within artificial intelligence comes with an increased level of sophistication within machine-generated content, which presents a distinctive challenge towards detecting such content effectively. Therefore all involved in its development process need to work on creating even more cutting-edge and accurate tools that can keep up. Detecting false information created by AI accurately is vital for maintaining online information credibility, which will be the only way to counter these threats effectively. Moreover, it is important that we pay close attention to ethical considerations surrounding privacy encroachment, consent violations, and the potential for misuse of this powerful technology. Who Uses AI Detection? Here are some groups that stand to benefit the most from using AI detection: : Prevent students from abusing AI writing software. Schools : Get rid of spam, fake reviews, or fake news. Businesses : Eliminate criminal activities such as impersonation, identity fraud, and cyberbullying. Law Enforcement Agencies : Remove bots and fake accounts that spread misinformation and propaganda. Social Media Platforms : Identify false news and propaganda or even replace writers who rely on AI too much. Media and Journalism Organizations : Eradicate disinformation campaigns and propaganda. Government Organizations Frequently Asked Questions Do AI Content Detection Tools Have Any Limitations or Shortcomings? AI content detection tools do have some shortcomings and limitations. Their accuracy is not always perfect, as AI-generated content improves and becomes more indistinguishable from human-generated text. Additionally, AI detectors may struggle to identify . Future developments in both AI-generated and detection technologies will determine the extent of these limitations. AI-generated content designed to be undetectable Why Use AI Detection in SEO? There is still an ongoing debate on with despite having said in their most recent update that they no longer consider AI content spammy if it’s valuable. However, you never really know when or if they will actually penalize you. So most SEOs will still use AI detection to be safe. Google can detect AI-generated content How Accurate Is AI Detection? AI detection is only accurate at predicting how similar the text in question is to its training data. It’s a confidence score and not a binary yes or no result. To Sum Up So I’ve covered everything you need to know about AI detection. From why you need it, what really goes behind the scenes of training such a model, its accuracy, and the future of it. I hope this helps you understand this topic slightly better. If you liked it, please share this article and leave a comment below! Also published here.

A Detailed Overview of How AI Detectors Work

How do people feel about you? really Do you ever wonder if the people around you like and respect you? You and everyone else. Being a human is hectic. We’re born with this primal capability to stand in people’s shoes and see the world from their perspective. And because we’re all searching for our identity, we often try to look at ourselves through their eyes to understand what’s valuable about us. After all, it would be nice if the people around us gave a shit. What more is there to life? And, why do we care? Well, despite all the chaos in the universe, we exist. We want to know that we matter somehow. We need to know that something about us is worth recognizing & supporting. Whatever you decide to become in this life, whatever paths of self-expression you choose to explore, a good sign that you’re making progress is when your ideas meet resistance. But don’t be so quick to turn this natural phenomenon into your trophy, resistance is only a litmus test on your way to building a brand. Here's what I've learned about branding since 2015 1. Vive la Résistance! 🤬 If you’ve read my viral articles on , & the , you’d have noticed a pattern of non-conformity and an embrace of the unorthodox. This is deliberate, and I’ll explain. web3 eCommerce metaverse Whenever you try to convince people about something, the direct route is often the most energy-intensive one and yields the highest number of short-term failures. The truth is that humans don’t like change all that much, completely disregarding the fact that we live on a planet that spins—on two axes—and has no pause button. When your new reaches people for the first time, their reactions will vary depending on their relationship with risk. thing For a few, they’re eager to try you out. You’ll probably know them as first/early adopters. In many cases, people are even strategically placed in such positions to cause a domino effect, because humans are largely social creatures. In the 1830s, opera houses in France were said to spike their audience with calqueurs; performers paid to sit with the audience and encore, give standing ovations or even weep after performances to get the crowd going. Once they began, the results were undeniable. Watching people around you stand up in applause after a performance would surely nudge you to stand too, even if it was meh. We are, after all, social creatures that learn from mimicking others. In a bunch of your favorite sitcoms, you laugh when the show tells you to laugh. You know, the background laughter that follows each joke, whether it’s funny or not. You thought you were in control? I’ve studied dictators, influencers, icons, celebrities, and the world’s most powerful leaders. I’ve also interviewed executives of some of the biggest brands in the world today to learn from them and one thing they shy away from is the direct route. never But if you tried to build your brand and influence today by taking people’s worldviews head-on, you will likely fail terribly. So what’s their secret? Well, keep reading to find out. A lot of the people you know personally won’t admit your influence in their lives, especially not to your face. If anything, they might want to downplay your achievements so that you reside comfortably beside their ego. Consider such a side quest. With business, you have some wiggle room. Because a brand/business is not an entity, we can’t really project our emotions to it. It’s not alive; it doesn’t breathe, it doesn’t shit, it doesn’t fuck, it doesn’t bleed. But it lives in you and everyone like you. 2. What a Brand Is 😂 Exactly A brand is a buzzword in every market today. People want to build a brand out of everything possible, from personalities to dog food, because they know its impact on sales. The brand is a gift that keeps on giving. The first time I saw the word “brand”, it was used to describe the markings made on livestock and slaves to show ownership. Drawing a parallel to how we use the word (brand) today, what used to be a mark to show ownership of is now focused on the impression people get from interacting with your business. property What that means, is that the brand is fluid. People may hate you today, but with a few PR tweaks, people could love you to death tomorrow. The interaction is not over till it’s over. The world’s leading brands take over the market share by sinking their teeth deep into society and human thinking. somewhat These businesses may already have “pioneer privilege” by existing for longer than you ever lived. They’ve become household names and are now pillars of contemporary society. They might even spend heavily on campaigns to keep themselves on everyone’s mind. They’ll gladly distribute their swag anywhere eyes might be. But if you can’t beat them, should you join them? That depends on the game you’re ready to play. In a world of competition, it’s likely you’re not the only one in your niche, and even if you’re better than everyone else, they’ll just steal your ideas. Snapchat CEO Evan Spiegel refused to sell to Mark Zuckerberg and now almost every social app has stories. In order to find your own space in the mind of your market, you can only stand out by taking risks. By mixing trusted strategies with fresh perspectives, you take up virgin land in your audience’s mind. People want something fresh and new to excite them. Take risks, like Harry Houdini. 3. The Business of Risk 😬 Your branding strategy has to include the measure of your appetite for risk, not just for you, but for the team backing you up. They need to know how much room they have to experiment in order to grow your brand. I’ve worked as a Creative Director (marketing) since 2019, and the only thing that ever gets people’s attention is in the high-emotion spectrum. The bizarre, the outrageous, the offensive, the adorable, the exciting, the popular. You know, stuff like that. When doom-scrolling online, people will take an instant to decide if they will give your content their attention. They’re looking for an emotional and psychological reward. From the reward, you make an impression. If it meets them exactly where they need you, sharing your brand is the least they’ll do for you. And so it spreads, like a virus. There’s no profit in being typical or following other people’s footsteps. You will find your footing by extracting the context of worthy experiences and turning them into critical wisdom for yourself. There are core aspects of your brand that you may never realize or benefit from without taking risks to reach people’s subconscious. You live in a world with 8 billion individual minds experiencing life differently. Your market is only a portion of these people, and the one thing they have in common is that they respond to your brand. Your job is to keep learning WHY people find value in your brand through neverending testing, feedback, and learning—separate from your own biases. There are no rules. To reach the people who unknowingly want to connect with your brand, you’re going to have to be honest. As fuck. If you’re not taking risks, you have nothing to gain. Even in human relationships, we don’t create meaningful connections if we don’t take risks. Everyone has a story. I found massive engagement from telling my most remarkable ones. The ones that mattered deeply to me. People can smell that authenticity. What if people get offended? They’ll be fine. Your job is not to pacify the emotions of the hypothetical haters. You can also win the real ones over with a few tricks. More on that later. Your job is to stand strong and do good work for the people who see your relevance. And when you see that something’s definitely not working, pivot quickly. The brand is also agile, even if it’s steadfast. 4. The Psychology of Persuasion 😵‍💫 I said I’d tell you the secret of the people who wield mass influence. Robert Cialdini, an Italian-American behavioral psychologist with a niche in Persuasion Science published his research in a book titled . The things I read there cracked my brain open. Influence: The Psychology of Persuasion In summary, your approach is literally everything. People are in their own heads, thinking about their own lives, problems, goals, and wishes. The only way they’ll let you in is if they see your brand as a means to their success/happiness, or see themselves in it. When I was first learning copywriting, every course I took kept emphasizing, “Nobody cares.” That’s good news. If nobody cares about your brand, then your marketing problem is already solved. You just have to find a way to them care. make The only way you can get through to them is to know what THEY care about and align your brand to it. That’s why the approach is everything. Depending on how you’re approached, you react differently. Everyone has a spectrum of behaviors, perspectives, and traits that hide or show themselves depending on the situation. You don’t know who I am, but you love me-hee-hee! Approach triggers subconscious emotional reactions in all of us. Humans are not creatures you approach rationally. Believe me, I’ve tried. I’ve even lost a lot of relationships with people as a result. It’s not convincing enough. Even in conflict between children, the one who makes a case of it first tends to get the adult’s favor. Fuck ethics, fuck rationality. Who made their story matter first? That tends to set the precedence for how the situation is handled and could even reduce the offenses of the reporting kid. From Cialdini’s book, you can influence anyone to do anything by using reciprocation, proving commitment & consistency, providing social proof, being likable, showing authority, highlighting scarcity, and establishing unity. But what matters most is the approach. Design how you want people to feel in every interaction with your brand. 5. No Authority Without Risk 🐐 Humans wonder who to trust when there are stakes involved. Historically, authority has been useful in establishing order and civilization in human society. We trusted figures of authority to guide us because we didn’t know enough to make critical decisions. Now that the internet is mainstream, authority is no longer about who knows the most, but about who speaks up first and speaks loudest. It's only after the noise and turbulence that the strongest brands shine. Establish your brand as an authority in today’s day and age requires the courage to step on some toes and ruffle some feathers. When Einstein began publishing his papers, he first received a lot of skepticism from his peers. Scientists who had invented spectacular things wondered who the fuck this guy thought he was with his theory of relativity. After a while, their skepticism turned to intrigue, and the rest they say, is history. Deciding to risk publishing the heart of your brand with honesty and confidence sets you up to be tested. If you’re battle-ready, you’ll win everyone’s hearts. Being disliked means you stand out. It’s good for your brand. It also means you’re authentic, because you refuse to settle. It means you’re loyal, to your cause. It means you’re passionate and your views influence how people think. Above all, it means you’re selective. Not everyone must understand your views, but the ones that do see your brand clearly and form around it. 6. Piracy is a Gift, Use It 🔥 I’ve told a part of this story before in my , but I published a book in 2019 to help students improve their performance in school using specific habits. Long story short, not only did it go viral on , but it also got pirated in my school. eCommerce article Twitter That’s the most flattering thing that had ever happened to me at that time in my life. I became curious and did research to find out if I should be worried about it. I was pleased to learn and discover that piracy is the best way to build your brand for free. Kanye leaked his tapes. Game of Thrones took over the planet because it was available everywhere. Not all value from your business is money. Companies like & have brand value in hundreds of billions of dollars that they can’t cash on demand. Apple Microsoft But because they know their audience, they can build their products and put that billion-dollar stamp on it and it will sell. Even bootlegs help to spread the word. Don’t be so stuck up. I’m a pirate myself, and I support piracy. Without piracy, I’d never be where I am now. Russians understand this, so they try to give everyone that opportunity. I got ebooks, research papers, software, courses, mobile games, name it. I could never have afforded those as a kid. I found ways to utilize my findings on piracy for my eCommerce business by understanding why people pirate stuff and taking control of the situation to turn most of it in our favor. If you want the research, let me know in the comments. Check out how we serve customers who can’t pay for whatever reason . I’ve learned that everyone in my community is my business and I should try to reach them somehow. here 7. We Need An Image 🗿 I was curious and asked about the difference between a brand following and a mob. The answer is leadership. ChatGPT Your brand will not build itself, it needs a champion. Apple has Steve Jobs and his transcendent ideals. Microsoft has Bill Gates and all his contributions to humanity. Amazon has Jeff Bezos, Twitter has Jack Dorsey, and Tesla has Elon Musk. Recess has Walo Olapoju; walo, the underscore. 🙈 https://youtu.be/HWeVlb4djig?embedable=true Musicians, authors, and actors use their faces too. A mob is a mindless rave of madness and chaos. A brand following conforms to order and can be used to make the world a much better place. Look at Patagonia. People who lead their brands relentlessly promote them for years, being the face of criticism and congratulations. Without criticism, you can't stand firm. Without congratulations, it's harder to keep going too, anyway. If you really want your brand to be accepted, it needs a symbol. It doesn’t even need a face. Sometimes, a mask will do (I use one, tee-hee). For a business, its logo might be the visual anchor. It could even be an animation style, a look and feel. If people can’t identify you on sight, you have a big problem. So give them an image they’ll never forget. 8. Bad Publicity Is Still Publicity 😏 Pablo Picasso and Kanye West have a couple of things in common. Apart from their obvious —which is actually a necessity (take that with a bucket of salt) for carving out huge success in society, they understand that one failure is not the end. In fact, Pablo Picasso would actually paint ugly stuff just to get people’s hate. sociopathy If they hate you, it’s still attention. The opposite of love is not hate, it’s indifference. So don’t be afraid to make mistakes, just keep your community in the loop always. They want to trust you, so make it easy for them. And if your brand is ever misrepresented by malice, you might be better off ignoring that shit than getting baited into a public debate. Also, when you interact with unhappy customers, take the chance to pay close attention and learn from your mistakes. Your job is not to be perfect, your job is to be dedicated to reaching your business goals. Money is a symbol of trust, but trust itself is priceless. You can only influence people in trust, and if you mislead them, you’re the boy who cried wolf. So it’s always important to set expectations properly, under-promising and over-delivering; giving enough room for you to fail woefully and get back up quickly. Hope you enjoyed my article! I'm also a musician, and you'd absolutely make my day if you listened to my EP . 🙏🏿 here Thank you! It's 13 minutes only, just plug and play. If you hate it, I'll send you a letter of apology. 😂 personally

8 Bizarre Lessons from 8 Years of Branding

8 বছরের ব্র্যান্ডিং থেকে 8টি উদ্ভট পাঠ

8 bizarre Lektionen aus 8 Jahren Branding

8 lecciones extrañas de 8 años de branding

8 leçons bizarres de 8 ans de branding

ब्रांडिंग के 8 वर्षों के 8 विचित्र पाठ

Stories, News & Mentions about LITMUS

Litmus’s Stories on HackerNoon