Even as the venture market continues to meander, October saw a lot of big rounds. To make October’s list, you had to raise a nine-figure round, and to come out on top you had to raise more than $1 billion.

The 10 Biggest Rounds Of October: Metropolis Tops List With $1.1B Raise

Shield AI, the defense and aerospace startup creating AI pilots, raised a $200 million Series F at a $2.7 billion valuation.

Defense Tech Startup Shield AI Raises $200M At $2.7B Valuation

The Biden administration on Monday released an executive order laying out a broad range of  safety and security requirements around the use of artificial intelligence technology. We take a look.

Biden’s AI Order May Have Wide Impact For Startups

This week saw a nice pickup thanks again to AI. Four companies raised nine-figure rounds and there were several other big rounds just under that. Of course, Anthropic’s round late in the week was the top raise,

The Week’s 10 Biggest Funding Rounds: Anthropic Rules With $500M Round; Aiolos Bio Nabs Large Raise

After a slow week last week — where the top raise was only $57 million — this week saw a little pick up. Three companies raised nine-figure rounds and there were several other big rounds just under that. Biotech seemed to be the big winner this week, taking three of the top five spots.

The Week’s 10 Biggest Funding Rounds: Aiolos Bio, Island And Pony.ai Nab Large Raises

One in five of the new billion-dollar startups to join The Crunchbase Unicorn Board this year were artificial intelligence companies, an analysis of the board shows.

Meet The New AI Unicorns Of 2023

In May, net new SaaS sales came down from a spike in Q1 while churn worsened, spurred by reduced business-to-business budgets and higher borrowing costs. At the same time, extension rounds — an important indicator of a sector’s overall health — declined.

SaaS follow-on rounds see a slowdown, but it won’t last forever

Judging by its 2023 reported investment activity, it seems Andreessen Horowitz is a lot less bullish than in recent past years.

Andreessen Horowitz May Be Optimistic About Tech, But It’s Still Slowing Its Deal Pace

Global patterns appear to suggest that investors are no longer intent on supplying capital to supply chain startups. In a report on Wednesday (Oct 25), Crunchbase, which tracks trends, investments and news of global companies from startups to the Fortune 1000,

Global funding into supply chain startups on the decline — data

San Francisco- and London-based Aiolos Bio, a newly launched startup with an asthma drug in clinical trials, announced that it raised $245 million in Series A funding.

Aiolos Bio Launches With $245M As Asthma-Focused Funding Accelerates

Crunchbase

crunchbase

If you think that a small story can't make a big splash, then, good luck with that! It All Began With The Pretty Obvious Prediction Back in August of 2019, I published a story on Hacker Noon with - Upwork Q2 financial results. Yeah, I know. Boring! an attractive title about an unattractive topic For what is worth, I did notice something highly unusual about (now, a former) Upwork's CEO - Stephane Kasriel. Here's the picture that's not worth only a million words, but also millions of dollars, literally: Source: Tech Know Bits And, here's me stating the obvious: I did my very best to pinpoint the exact moment on the attached illustration. Someone may say, the timing was perfect. This transaction took place "in the middle of fall" of Upwork's stocks before they hit the record low on June 5th. Stephane Kasriel sold the jaw-dropping number of 280,000 shares Then, two weeks later, as soon as Upwork's stocks slightly recovered, . This time the timing wasn't perfect, but from a broker's point of view, it was still good enough to get the most out of your stocks. Stephane Kasriel sold another quantity of shares (120,000) With one of my article's subheadings, I predicted the inevitable: O Captain! My Captain! Why Are You Leaving Your Ship That Still Floats? On the exact same day, the 9th of August, that this article was published, but a few months later, the 9th of December, . Stephane Kasriel stepped down as Upwork's CEO So, I asked myself, what would happen if I do a few more of these pinpointing activities, but with a different protagonist and parameters? And voila, my extremely controversial theory was born. If I can predict, can I actually impact Upwork's business with my stories? Let's see. My Stories Go Up - Upwork Stock Prices Come Down! Here's my starting point - Upwork's NASDAQ chart. Now, let's choose a story or two, and pinpoint their publishing dates on this chart. I would like to begin with . On May 20th, Upwork decided that these Connects are no longer free. Now, I don't expect and neither should you, hopefully and understandably, that my story impacts the stock market, the same day it gets published. Is it OK and fair to give a story some reasonable amount of time to "kick in?" Let it be the story #1, we're going to evaluate for the sake of my "experiment." my story about Upwork Connects I marked my story #1 with red color because it had no impact. Upwork stock prices were already on their way down before and after this story was published, so no link, no proof. But, then, during the last days of July, I published For this story #2, I would like to use green color because after it was published, Upwork stock prices slide down for the rest of the summer of 2019. a story about the so-called "inspirational Upwork stories." Then, on September 22nd, I published my , where I compared the fees of the top five freelance platforms. Unfortunately for me, and luckily for Upwork, this story hit the recovery period for Upwork stock prices that lasted throughout the end of October. So, it's red again, for my story #3. most viewed and shared Hacker Noon story Then, at the very beginning of November, I had ready for Upwork. Just a quick reminder. This was Upwork's first anniversary as a public company. So, we have story #4 in green because Upwork stock prices fell off a cliff at the end of 2019. a happy birthday story We will never know for sure, but during the last week of November, Upwork showed some willingness to stop the free fall of its stock prices. At least, according to the NASDAQ chart, I've been using a lot. At the same time, I published two of my most controversial stories in 2019. The first story was about The second story asked a legit question: ? the notorious Upwork fake review "farms." Is Upwork the next WeWork I mean, those stories were really good and eye-opening for Hacker Noon readers. I can't say the same for Upwork stock prices that probably made investors and clients feel bad. So, I believe that these stories #5 and #6 qualify for the green zone. My Research Was Systematic Even During The Pandemic At the beginning of April 2020, Upwork stock prices hit the all-time low value. In the weeks to follow, based on the information obtained from an Upwork's insider, I wrote a series of stories about the systematic and intentional posting of fake jobs. These stories proved to be true. So, Upwork admitted its "unintentional wrongdoing" and offered to refund freelancers. For the very first time in my Hacker Noon writing history, . my story had to have a disclaimer I just knew that I was on something big. I also documented . The third and dealt with the aftermath of my findings. the biggest "purge" of freelance accounts in Upwork's history with my story final story of my Upwork fake jobs "trilogy" I really thought that Upwork couldn't survive the perfect storm, which combined the poorest performance at the stock market and shocking discoveries of my Hacker Noon stories. It turned out that the COVID situation actually saved Upwork. So, my best stories ever marked the sharpest and most miraculous recovery of Upwork stock prices in 2020, instead. In 2020 Upwork Rocks - My Theory Sucks! What's fair is fair. I have proven that my stories have little or no effect at all when it comes to Upwork stock prices. In the meantime, I published two more stories. One was about the disturbing conspiracy theory about . The other one was deeply personal with the straight to the point title: . the "Golden Million" Upwork freelancers Upwork vs. Nebojsa Todorovic And, I was ready to let it go. I clearly bit off with my writing more than I could possibly chew. Upwork is just too big to fail. Time to move on. Then, I don't remember how and why, but I stumbled upon . So what? Upwork's profile on Crunchbase I Ain't No Forbes. I Ain't No Fortune. I'm Hacker Noon! Well, every company has the Recent News & Activity section on Crunchbase. Guess what I've found in Upwork's? Next to all those shiny Forbes, Bloomberg, Business Insider, Fortune stories about Upwork, you can see my raw Hacker Noon stories. So, how about that? Imagine all those wolves of Wall Street who are checking out this section in their fancy suits and on their fancy devices. It's all uber shiny and green about Upwork. And then, you see one of my Hacker Noon articles. How can you resist? Which one you're going to read first? All those polished, but boring and faceless articles, or the one you can't ignore because it looks as if it just crashed through like a meteorite from another planet. From the Moon. Hacker Noon. Ah, just one more thing. I'm this year's nominee for the most handsome Hacker Noon writer. Here's for those who appreciate controversy, and support writing without regrets and mercy. the voting link

How My Hacker Noon Stories Impacted Upwork Stock Prices

Authors:
(1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com);
(2) Andrey Chertok, (a.v.chertok@gmail.com);
(3) Konstantin Zorin, (berzqwer@gmail.com);
(4) Cyril Shtabtsovsky, (cyril@aloniq.com). Table of Links Abstract and 1. Introduction 2 Related works 3 Dataset Overview, Preprocessing, and Features 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.3 Features 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4.2 Backtest settings 4.3 Results 4.4 Capital Growth 5 Other approaches 5.1 Investors ranking model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 6 Conclusion 7 Further Research, References and Appendix 3 Dataset Overview, Preprocessing, and Features We used daily Crunchbase database export (Daily CSV Export) as the primary data source, which is also supported by a well-documented API. The main goal of this research was to collect a labeled dataset for training a deep learning model to classify companies as either successful or unsuccessful. The analysis was based on the Daily CSV Export from 2022-06-14, and only companies established on or after 2000-01-01 were taken into account. To refine the focus of the research, only companies within specific categories were included, such as Software, Internet Services, Hardware, Information Technology, Media and Entertainment, Commerce and Shopping, Mobile, Data and Analytics, Financial Services, Sales and Marketing, Apps, Advertising, Artificial Intelligence, Professional Services, Privacy and Security, Video, Content and Publishing, Design, Payments, Gaming, Messaging and Telecommunications, Music and Audio, Platforms, Education, and Lending and Investments. This research is focused on investment rounds occurring after round B. However, in the Crunchbase data glossary, rounds such as series_unknown, private_equity, and undisclosed, possess unclear characteristics. To incorporate them into the company’s funding round history, we only included these ambiguous rounds if they occurred after round B. This paper is available on arxiv under CC 4.0 license. Authors: (1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com); (2) Andrey Chertok, (a.v.chertok@gmail.com); (3) Konstantin Zorin, (berzqwer@gmail.com); (4) Cyril Shtabtsovsky, (cyril@aloniq.com). Authors: Authors: (1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com); (2) Andrey Chertok, (a.v.chertok@gmail.com); (3) Konstantin Zorin, (berzqwer@gmail.com); (4) Cyril Shtabtsovsky, (cyril@aloniq.com). Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Related works 2 Related works 3 Dataset Overview, Preprocessing, and Features 3 Dataset Overview, Preprocessing, and Features 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.3 Features 3.3 Features 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4.2 Backtest settings 4.2 Backtest settings 4.3 Results 4.3 Results 4.4 Capital Growth 4.4 Capital Growth 5 Other approaches 5.1 Investors ranking model 5.1 Investors ranking model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 6 Conclusion 6 Conclusion 7 Further Research, References and Appendix 7 Further Research, References and Appendix 3 Dataset Overview, Preprocessing, and Features We used daily Crunchbase database export (Daily CSV Export) as the primary data source, which is also supported by a well-documented API. The main goal of this research was to collect a labeled dataset for training a deep learning model to classify companies as either successful or unsuccessful. The analysis was based on the Daily CSV Export from 2022-06-14, and only companies established on or after 2000-01-01 were taken into account. To refine the focus of the research, only companies within specific categories were included, such as Software, Internet Services, Hardware, Information Technology, Media and Entertainment, Commerce and Shopping, Mobile, Data and Analytics, Financial Services, Sales and Marketing, Apps, Advertising, Artificial Intelligence, Professional Services, Privacy and Security, Video, Content and Publishing, Design, Payments, Gaming, Messaging and Telecommunications, Music and Audio, Platforms, Education, and Lending and Investments. This research is focused on investment rounds occurring after round B. However, in the Crunchbase data glossary, rounds such as series_unknown, private_equity, and undisclosed, possess unclear characteristics. To incorporate them into the company’s funding round history, we only included these ambiguous rounds if they occurred after round B. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

How We Used Crunchbase Data to Predict Startup Success

Authors:
(1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com);
(2) Andrey Chertok, (a.v.chertok@gmail.com);
(3) Konstantin Zorin, (berzqwer@gmail.com);
(4) Cyril Shtabtsovsky, (cyril@aloniq.com). Table of Links Abstract and 1. Introduction 2 Related works 3 Dataset Overview, Preprocessing, and Features 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.3 Features 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4.2 Backtest settings 4.3 Results 4.4 Capital Growth 5 Other approaches 5.1 Investors ranking model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 6 Conclusion 7 Further Research, References and Appendix ABSTRACT Predicting startup success presents a formidable challenge due to the inherently volatile landscape of the entrepreneurial ecosystem. The advent of extensive databases like Crunchbase jointly with available open data enables the application of machine learning and artificial intelligence for more accurate predictive analytics. This paper focuses on startups at their Series B and Series C investment stages, aiming to predict key success milestones such as achieving an Initial Public Offering (IPO), attaining unicorn status, or executing a successful Merger and Acquisition (M&A). We introduce novel deep learning model for predicting startup success, integrating a variety of factors such as funding metrics, founder features, industry category. A distinctive feature of our research is the use of a comprehensive backtesting algorithm designed to simulate the venture capital investment process. This simulation allows for a robust evaluation of our model’s performance against historical data, providing actionable insights into its practical utility in real-world investment contexts. Evaluating our model on Crunchbase’s, we achieved a 14 times capital growth and successfully identified on B round high-potential startups including Revolut, DigitalOcean, Klarna, Github and others. Our empirical findings illuminate the importance of incorporating diverse feature sets in enhancing the model’s predictive accuracy. In summary, our work demonstrates the considerable promise of deep learning models and alternative unstructured data in predicting startup success and sets the stage for future advancements in this research area. 1 Introduction The prediction of startup success is a crucial task for various stakeholders, including investors, entrepreneurs, and policymakers, as it has significant implications for resource allocation and decision-making. It is estimated that approximately 90% of startups fail within their first five years, a failure rate that has remained relatively constant over the past few decades, despite considerable advancements in technology and business practices. Consequently, the accurate prediction of startup success can assist investors in more effectively allocating their resources and enable entrepreneurs to make better-informed decisions. Recently, the proliferation of data from sources such as Crunchbase has intensified interest in the application of machine learning techniques for the prediction of startup success. Machine learning models can harness various types of data, encompassing funding history, market trends, team composition, and social media activity, to identify patterns and generate predictions. This study presents two distinct methodologies for predicting startup success: a supervised deep learning approach leveraging multiple data sources, and a ranking-based approach focusing on the identification of characteristics common to successful startups and investors. The supervised approach entails collecting and labeling data, constructing a prediction model, and evaluating its performance. In contrast, the ranking-based approach centers on identifying startups and investors that exhibit shared characteristics with successful ones. Our train dataset consists of 34,470 companies The primary novelty of this research lies in the application of deep learning techniques and the integration of heterogeneous input data types. A crucial feature of our research is the simulation of fund operations based on historical data, resulting in a projected 14x capital growth of the fund’s portfolio. As per machine learning metrics, our model exhibits a robust 86% ROC_AUC. The remainder of this paper is organized as follows: Section 2 reviews the related works in the area of startup success prediction and machine learning. Section 3 describes dataset collection, preprocessing, and feature selection. Section 4 presents the experimental results of the supervised approach. Section 5 describes some other ideas about company and investor scoring. Finally, Sections 6 and 7 provide the conclusion of the study and discuss prospective research avenues in this domain. This paper is available on arxiv under CC 4.0 license. Authors: (1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com); (2) Andrey Chertok, (a.v.chertok@gmail.com); (3) Konstantin Zorin, (berzqwer@gmail.com); (4) Cyril Shtabtsovsky, (cyril@aloniq.com). Authors: Authors: (1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com); (2) Andrey Chertok, (a.v.chertok@gmail.com); (3) Konstantin Zorin, (berzqwer@gmail.com); (4) Cyril Shtabtsovsky, (cyril@aloniq.com). Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Related works 2 Related works 3 Dataset Overview, Preprocessing, and Features 3 Dataset Overview, Preprocessing, and Features 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.3 Features 3.3 Features 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4.2 Backtest settings 4.2 Backtest settings 4.3 Results 4.3 Results 4.4 Capital Growth 4.4 Capital Growth 5 Other approaches 5.1 Investors ranking model 5.1 Investors ranking model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 6 Conclusion 6 Conclusion 7 Further Research, References and Appendix 7 Further Research, References and Appendix ABSTRACT Predicting startup success presents a formidable challenge due to the inherently volatile landscape of the entrepreneurial ecosystem. The advent of extensive databases like Crunchbase jointly with available open data enables the application of machine learning and artificial intelligence for more accurate predictive analytics. This paper focuses on startups at their Series B and Series C investment stages, aiming to predict key success milestones such as achieving an Initial Public Offering (IPO), attaining unicorn status, or executing a successful Merger and Acquisition (M&A). We introduce novel deep learning model for predicting startup success, integrating a variety of factors such as funding metrics, founder features, industry category. A distinctive feature of our research is the use of a comprehensive backtesting algorithm designed to simulate the venture capital investment process. This simulation allows for a robust evaluation of our model’s performance against historical data, providing actionable insights into its practical utility in real-world investment contexts. Evaluating our model on Crunchbase’s, we achieved a 14 times capital growth and successfully identified on B round high-potential startups including Revolut, DigitalOcean, Klarna, Github and others. Our empirical findings illuminate the importance of incorporating diverse feature sets in enhancing the model’s predictive accuracy. In summary, our work demonstrates the considerable promise of deep learning models and alternative unstructured data in predicting startup success and sets the stage for future advancements in this research area. 1 Introduction The prediction of startup success is a crucial task for various stakeholders, including investors, entrepreneurs, and policymakers, as it has significant implications for resource allocation and decision-making. It is estimated that approximately 90% of startups fail within their first five years, a failure rate that has remained relatively constant over the past few decades, despite considerable advancements in technology and business practices. Consequently, the accurate prediction of startup success can assist investors in more effectively allocating their resources and enable entrepreneurs to make better-informed decisions. Recently, the proliferation of data from sources such as Crunchbase has intensified interest in the application of machine learning techniques for the prediction of startup success. Machine learning models can harness various types of data, encompassing funding history, market trends, team composition, and social media activity, to identify patterns and generate predictions. This study presents two distinct methodologies for predicting startup success: a supervised deep learning approach leveraging multiple data sources, and a ranking-based approach focusing on the identification of characteristics common to successful startups and investors. The supervised approach entails collecting and labeling data, constructing a prediction model, and evaluating its performance. In contrast, the ranking-based approach centers on identifying startups and investors that exhibit shared characteristics with successful ones. Our train dataset consists of 34,470 companies The primary novelty of this research lies in the application of deep learning techniques and the integration of heterogeneous input data types. A crucial feature of our research is the simulation of fund operations based on historical data, resulting in a projected 14x capital growth of the fund’s portfolio. As per machine learning metrics, our model exhibits a robust 86% ROC_AUC. The remainder of this paper is organized as follows: Section 2 reviews the related works in the area of startup success prediction and machine learning. Section 3 describes dataset collection, preprocessing, and feature selection. Section 4 presents the experimental results of the supervised approach. Section 5 describes some other ideas about company and investor scoring. Finally, Sections 6 and 7 provide the conclusion of the study and discuss prospective research avenues in this domain. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Startup Success Prediction and VC Portfolio Simulation Using CrunchBase Data

How to Use Intuition to Succeed in Business As entrepreneurs, there are many different skills we have to constantly be developing. But what if there’s one that you can’t touch, can’t see, can’t really measure, but it turns out to be one of the most valuable tools in your arsenal? We’re talking about intuition. Intuition can be hard to define, but it’s that general feeling you get that something is right or wrong without necessarily being able to explain why. It’s your gut feeling, that sense of ‘knowing’. We’ve all felt it before, when we suddenly get an inkling about what’s about to happen, or about the outcome of a decision that was just made, without necessarily knowing why we feel that way. It’s true that intuition isn’t always reliable, and it can be wrong sometimes. But it’s also true that it can be incredibly helpful in making decisions and succeeding in business. In my , CEO of Crunchbase, we dove deep into his history of entrepreneurship. recent conversation with Jager McConnell We also talked about how he has used his intuition to navigate his career and the value of developing this skill. This inspired me to do a deep dive into this topic, as intuition has played a crucial role in my career as well. I believe it’s incredibly valuable to learn what this skill is, how to develop it, and how to use it properly. So, buckle up, today’s going to be a fun ride! What Is Intuition? First things first, let’s try to define intuition. Intuition is the ability to understand something instinctively, without conscious thought. It’s the immediate understanding of something without any logical explanation. It is often seen as a sixth sense, and it can be a powerful tool for entrepreneurs. For example, you might walk into a room and get a feeling that something is wrong without any tangible reason. Or you might face a problem, and immediately know the solution without thinking it through logically. That’s intuition. And it can be a superpower in business. In the business world, intuition is often overlooked, but in reality, it is a vital skill to have. In our fast-paced world, intuition can help us make quick decisions, identify opportunities, and anticipate problems. Why Intuition Is Important for Entrepreneurs As entrepreneurs, we are often pushed to the edge of our comfort zone and have to make judgments quickly and confidently. We don’t have the luxury of spending weeks analyzing all of the information. We need to be on our toes, ready to tackle any problem that arises, without delay. That’s where intuition comes in. Intuition can help us get in touch with , and it can help us gain a new perspective. Of course, intuition is not a substitute for research and analysis. another source of knowledge within us But it can be a valuable tool to have in your arsenal. There are four key reasons why intuition is such a valuable skill for entrepreneurs to develop. Making Decisions If your business is anything like mine, it’s likely you often have to make decisions with incomplete information and under extreme time pressure. This is a skill that is difficult to develop, as there’s no textbook you can learn it from. It relies on your accumulation of knowledge and internal compass to guide you. Intuition can be a valuable asset in these situations, as it allows you to rely on your gut feelings and experience to make decisions. For example, if you have a strong gut feeling that a particular business opportunity is a good one, you might decide to invest in it despite not having all the information you need. Or vice versa. Developing a strong intuition is one of those intangible skill sets that could potentially save you millions of dollars in bad business deals. Or make you millions on good ones. Identifying Opportunities Intuition can also help you to identify opportunities that others may not see. By paying attention to your gut feelings, you may be able to spot trends or patterns in the market that others miss. For example, I know of several entrepreneurs who use this for investing (although I don’t recommend this strategy). When they have a strong gut feeling that a particular technology is about to take off, they might decide to invest in it before others catch on. They let their intuition guide them, and then they pounce on the opportunity. This ability to anticipate changes in the market and act on them quickly can give you a competitive edge. Developing a strong intuition also allows you to think outside the box and consider new possibilities. You might start to get a feeling that a particular product or service is needed in the market but is not yet being offered, and you can use this intuition to develop a new business idea. Creative Solutions Intuition can also help you to create a unique vision for your business. Rather than being constrained by preconceived notions and established ways of thinking, a strong intuition allows you to connect seemingly unrelated concepts and come up with unique solutions to problems. Entrepreneurs who rely on intuition are and unique ideas for their businesses. more likely to come up with creative solutions This is because they are not limited by conventional thinking, and can tap into their unconscious mind to generate new and innovative ideas. Developing this power can help you to differentiate your business from others, and create a unique value proposition for your customers. When you can tap into your intuition, you are able to identify patterns and trends that others may not see and are better equipped to adapt your business strategies accordingly. Anticipating Problems From managing finances to managing personnel, we are constantly faced with a variety of problems on a daily basis. There is an ever-present pressure to make decisions and anticipate potential problems. While experience and knowledge can help you anticipate some problems, intuition plays an important role in helping you anticipate and address issues before they arise. Having a strong intuition can help identify patterns and trends that may not be obvious with traditional analysis. It can also help you to anticipate potential problems and come up with solutions. For example, you may wake up one morning and feel that strong gut feeling that a particular marketing strategy isn’t working, and you may decide to change course before it’s too late. By developing and trusting your intuition, you can gain a competitive edge in the business world. But it is important to mention that intuition should not always be used in isolation; it should be combined with data, logic, and reason to make well-rounded decisions. How to Develop Your Intuition As an entrepreneur, developing your intuition can be a crucial step in achieving success. Intuition can provide valuable insights and lead to great decision-making, which can be especially important in the fast-paced and ever-changing business world. To develop and trust your intuition, there are a few key practices you must take. I know, I’m always preaching the importance of these, but I always will, as they have had such a profound impact on me. Practice Mindfulness and Meditation. These practices will help you clear your mind and focus on the present moment, which can lead to increased self-awareness and a deeper understanding of your gut feelings. The more you are able to be in the moment with your thoughts and feelings, the more you are able to listen to them when it matters. One of the best ways to access your intuition is to pay attention to your gut instinct. Gather Your Intuition. When you’re faced with a difficult decision or a complex problem, take a few minutes to sit with it and see what comes up for you. You’ll be surprised how often your “gut feeling” is the best advice. You can also use your intuition to gather information from your environment. Look for clues that can help you make the best decision. For example, if you’re considering a business partnership, pay attention to the body language of the people you’re talking to. Do they seem interested and engaged, or are they distracted and disinterested? Your intuition can help you pick up on subtle cues that can inform your decision. Your body often knows more than your mind. If you feel a knot in your stomach or a tingle in your spine, it could be a sign that something is wrong. Pay Attention to Your Body. Pay attention to those physical sensations. Seeking out diverse perspectives can also help you to develop your intuition and trust it more. Seek Out Diverse Perspectives: By exposing yourself to different ways of thinking and problem-solving, you can broaden your understanding and enhance your intuition. The more experience you have, the more you learn to rely on your gut feelings and make quick decisions based on them. Gain More Experience in Your Field: As you gather an accumulation of life and business experience, your intuition will grow sharper and sharper. Trusting Your Intuition In order to make the most of your intuition, you have to trust it. Intuition is a powerful tool, but it can be hard to trust something that’s not backed up with data or research. The best way to start trusting your intuition is to take time to reflect on it. After you’ve made a decision or taken an action, take some time to reflect on the results. Did it work out as you expected? If so, you can start to trust your intuition more. This practice will give you some valuable feedback on whether or not your intuition was guiding you in the right direction. You can begin to dissect what parts of your intuition were right, or whether there were feelings you had that you didn’t act on that then turned out to be true. Trusting your intuition also means being willing to act on it, even when you can’t fully explain why you feel a certain way. By taking action based on your intuition, you will develop more confidence in it and be able to rely on it more in the future. Wrap-Up As you can see, intuition is a wildly underrated skill that you must begin to develop and nurture in your entrepreneurial journey. It can help you make quick decisions, identify opportunities, and anticipate problems. But here’s the thing, intuition is not a substitute for research and analysis, it’s a supplement. So, pay attention to your gut feelings, trust your instincts, and use it to your advantage. But continue to do your research and logically plan for your business as well. Remember, a strong intuition can potentially save you millions in bad business deals, help you find the next big product your company needs, or help you rebrand successfully. Don’t overlook it, develop it. If you want to hear more about this, check out my full conversation with Jager. That’s it for now, thanks for reading. I’ll see you next week with more success stories! If you enjoyed this article, I’d love to hear from you. Reply to this or tweet at me and I’ll do my best to get back to everyone! email @ScottDClary

Talking With Jager McConnell, CEO of Crunchbase - Using Intuition To Succeed In Business

ক্রাঞ্চবেসের সিইও জেগার ম্যাককনেলের সাথে কথা বলা - ব্যবসায় সফল হওয়ার জন্য অন্তর্দৃষ্টি ব্যবহার করা

Im Gespräch mit Jager McConnell, CEO von Crunchbase – Mit Intuition im Geschäft erfolgreich sein

Hablando con Jager McConnell, director ejecutivo de Crunchbase: usar la intuición para tener éxito en los negocios

Parler avec Jager McConnell, PDG de Crunchbase - Utiliser l'intuition pour réussir en affaires

क्रंचबेस के सीईओ जैगर मैककोनेल के साथ बात करना - व्यवसाय में सफल होने के लिए अंतर्ज्ञान का उपयोग करना

Crunchbase の CEO である Jager McConnell との対話 - 直感を使ってビジネスで成功する

Crunchbase의 CEO인 Jager McConnell과의 대화 - 직관을 사용하여 비즈니스 성공하기

Conversando com Jager McConnell, CEO da Crunchbase - Usando a intuição para ter sucesso nos negócios

Crunchbase CEO'su Jager McConnell ile Konuşmak - İş Hayatında Başarılı Olmak İçin Sezgiyi Kullanmak

Nói chuyện với Jager McConnell, CEO của Crunchbase - Sử dụng trực giác để thành công trong kinh doanh

与 Crunchbase 首席执行官 Jager McConnell 对话——用直觉在商业上取得成功

There is a popular saying that: Data is the new gold, and the web (internet) is the biggest gold mine. As a business owner, student, drop shipper, or corporate worker, you must have faced the risk of going out of business if you lack access to some (if not the most) crucial piece of data. But fear not; there is a solution that helps you unlock the full potential of web data scraping/collection, which I will show you in this article. Why Do We Collect Data: The Essence of Data Scraping/Collection Before I dive into the challenges faced with data scraping/collection and the wonders of Bright Data solutions, it is important to understand the essence of data scraping in this digital age that we are in. Data scraping is a powerful technique that efficiently navigates the internet to extract specific valuable informations, acting like a personal assistant for data retrieval. Whether you seek to analyze market trends and performance, track competitor prices, or simply satisfy your thirst for knowledge, data scraping is the key to making your life easier. Challenges With Data Scraping: The Limitations Before Bright Data Solutions Like an adventure, data scraping comes with its share of challenges and obstacles. One significant hurdle is the risk of websites feeling under attack when excessive data is scraped too quickly. To counter such attempts, websites deploy defensive measures, such as CAPTCHAs, to determine whether the user is a human or a computer. If the volume of requests persists, the website may resort to blocking users, hindering or halting data scraping altogether. To avoid such unfavorable situations, a more versatile and intelligent solution is required. Bright Data: The Ultimate Solution for Web Data Collection Bright Data comes as the ultimate solution for web data collection tailored specifically for businesses. With its automated online data collection platform, Bright Data offers unlimited access to the vast wisdom of the web without exposing you to any risks. How Bright Data Works The magic behind Bright Data lies in its web unlocker: a unique P2P network composed of millions of genuine residential and mobile IPs from across the globe. These IPs serve as secret identities, making your data requests appear as if they come from real people, making it highly unlikely for websites to block them. Why I Am Using Bright Data: The Power of Using Bright Data 1. Versatility and Ease of Use Bright Data shines with its user-friendly approach. To start scraping vast amounts of data, all you need is a scraping browser — an automated browser that allows you to interact with websites just like a human user. It efficiently handles challenges such as CAPTCHAs, fingerprints, and retries while mimicking the behavior of a regular user. Compatible with popular automation tools like Puppeteer and Playwright and programming languages like Python and Node.js, the scraping browser makes data collection seamless and efficient. 2. Ready-to-Use Data Sets If you ever need ready-to-use data, Bright Data’s data sets tool provides pre-collected and structured data from various domains, including popular platforms like LinkedIn, Amazon, Crunchbase, Indeed, and Twitter. Regularly updated, these comprehensive data sets offer you a treasure trove of information at your fingertips. Practical Examples of What I Have Used Bright Data for 1. E-Commerce: Monitoring Competitor Prices and Enriching Product Catalogs In the world of e-commerce, web data plays a crucial role in monitoring competitor prices, ensuring product availability, and understanding customer reviews. For instance, a global Beauty and Personal Care Marketplace efficiently uses web data to check competitor prices in real-time, enabling them to adjust pricing strategies and optimize promotions on the fly, enhancing their market competitiveness. 2. Social Media: Analyzing Consumer Sentiment and Trends Social media platforms offer a gold mine of user-generated content, providing valuable insights into consumer behavior, trends, and sentiment. A global digital marketing agency effectively analyzes consumer sentiment towards their client’s brands using web data from various social media platforms. This deeper understanding empowers them to refine marketing strategies and achieve better results. In Conclusion: The Bright Future of Data Collection As I conclude with Bright Data's powerful web data collection solutions, one thing becomes very clear; data scraping is a game-changer in today’s digital landscape. Whether you are a business owner, entrepreneur, or data professional, harnessing the power of web data can unlock countless opportunities for growth and success. Traditional manual data collection methods are slow, labor-intensive, and error-prone, rendering them ineffective and inefficient in the face of today’s data-driven world. By automating the process with Bright Data, you can extract specific and relevant information from web pages effortlessly, propelling your business to new heights. So, if you find yourself in need of vast amounts of data, fast and easy, look no further than Bright Data. Embrace the power of web data, and let it guide you to new horizons of success in this ever-evolving digital landscape. There is a popular saying that: Data is the new gold, and the web (internet) is the biggest gold mine. Data is the new gold, and the web (internet) is the biggest gold mine. Data is the new gold, and the web (internet) is the biggest gold mine. As a business owner, student, drop shipper, or corporate worker, you must have faced the risk of going out of business if you lack access to some (if not the most) crucial piece of data. But fear not; there is a solution that helps you unlock the full potential of web data scraping/collection, which I will show you in this article. (if not the most) Why Do We Collect Data: The Essence of Data Scraping/Collection Before I dive into the challenges faced with data scraping/collection and the wonders of Bright Data solutions, it is important to understand the essence of data scraping in this digital age that we are in. Bright Data Data scraping is a powerful technique that efficiently navigates the internet to extract specific valuable informations, acting like a personal assistant for data retrieval. Data scraping is a powerful technique that efficiently navigates the internet to extract specific valuable informations, acting like a personal assistant for data retrieval. Whether you seek to analyze market trends and performance, track competitor prices, or simply satisfy your thirst for knowledge, data scraping is the key to making your life easier. Challenges With Data Scraping: The Limitations Before Bright Data Solutions Bright Data Like an adventure, data scraping comes with its share of challenges and obstacles. One significant hurdle is the risk of websites feeling under attack when excessive data is scraped too quickly. To counter such attempts, websites deploy defensive measures, such as CAPTCHAs, to determine whether the user is a human or a computer. If the volume of requests persists, the website may resort to blocking users, hindering or halting data scraping altogether. To avoid such unfavorable situations, a more versatile and intelligent solution is required. Bright Data: The Ultimate Solution for Web Data Collection Bright Data comes as the ultimate solution for web data collection tailored specifically for businesses. With its automated online data collection platform, Bright Data offers unlimited access to the vast wisdom of the web without exposing you to any risks. Bright Data How Bright Data Works How Bright Data Works The magic behind Bright Data lies in its web unlocker: a unique P2P network composed of millions of genuine residential and mobile IPs from across the globe. These IPs serve as secret identities, making your data requests appear as if they come from real people, making it highly unlikely for websites to block them. Why I Am Using Bright Data: The Power of Using Bright Data 1. Versatility and Ease of Use 1. Versatility and Ease of Use Bright Data shines with its user-friendly approach. To start scraping vast amounts of data, all you need is a scraping browser — an automated browser that allows you to interact with websites just like a human user. It efficiently handles challenges such as CAPTCHAs, fingerprints, and retries while mimicking the behavior of a regular user. Compatible with popular automation tools like Puppeteer and Playwright and programming languages like Python and Node.js, the scraping browser makes data collection seamless and efficient. 2. Ready-to-Use Data Sets 2. Ready-to-Use Data Sets If you ever need ready-to-use data, Bright Data’s data sets tool provides pre-collected and structured data from various domains, including popular platforms like LinkedIn, Amazon, Crunchbase, Indeed, and Twitter. Regularly updated, these comprehensive data sets offer you a treasure trove of information at your fingertips. Practical Examples of What I Have Used Bright Data for 1. E-Commerce: Monitoring Competitor Prices and Enriching Product Catalogs 1. E-Commerce: Monitoring Competitor Prices and Enriching Product Catalogs In the world of e-commerce, web data plays a crucial role in monitoring competitor prices, ensuring product availability, and understanding customer reviews. For instance, a global Beauty and Personal Care Marketplace efficiently uses web data to check competitor prices in real-time, enabling them to adjust pricing strategies and optimize promotions on the fly, enhancing their market competitiveness. 2. Social Media: Analyzing Consumer Sentiment and Trends 2. Social Media: Analyzing Consumer Sentiment and Trends Social media platforms offer a gold mine of user-generated content, providing valuable insights into consumer behavior, trends, and sentiment. A global digital marketing agency effectively analyzes consumer sentiment towards their client’s brands using web data from various social media platforms. This deeper understanding empowers them to refine marketing strategies and achieve better results. In Conclusion: The Bright Future of Data Collection As I conclude with Bright Data's powerful web data collection solutions, one thing becomes very clear; data scraping is a game-changer in today’s digital landscape. Whether you are a business owner, entrepreneur, or data professional, harnessing the power of web data can unlock countless opportunities for growth and success. Traditional manual data collection methods are slow, labor-intensive, and error-prone, rendering them ineffective and inefficient in the face of today’s data-driven world. By automating the process with Bright Data, you can extract specific and relevant information from web pages effortlessly, propelling your business to new heights. So, if you find yourself in need of vast amounts of data, fast and easy, look no further than Bright Data. Embrace the power of web data, and let it guide you to new horizons of success in this ever-evolving digital landscape.

How Bright Data AI Made Web Data Scraping/Collection Effortless: The Challenges Before Bright Data AI Solutions

Як AI Bright Data зрабіў скрабаванне/збор вэб-даных простым: праблемы перад рашэннямі AI Bright Data

Com Bright Data AI va fer que el raspat/recollida de dades web sigui sense esforç: els reptes abans de les solucions Bright Data AI

Cómo Bright Data AI hizo que la recopilación y el raspado de datos web fueran sencillos: los desafíos que enfrentaban las soluciones de Bright Data AI

Kako je Bright Data AI skrapiranje/prikupljanje web podataka učinio jednostavnim: Izazovi pred Bright Data AI rješenjima

Bright Data AI が Web データのスクレイピング/収集をいかに簡単にしたか: Bright Data AI ソリューションの課題

Cara AI Data Cerah Menjadikan Pengikisan/Pengumpulan Data Web Mudah: Cabaran Sebelum Penyelesaian AI Data Cerah

څنګه روښانه ډیټا AI د ویب ډیټا سکریپینګ/راټولول بې ځایه کړي: د روښانه ډیټا AI حلونو دمخه ننګونې

Bright Data AI විසින් Web Data Scraping/එකතු කිරීම වෙහෙසකින් තොරව සිදු කළේ කෙසේද: Bright Data AI විසඳුම් ඉදිරියේ ඇති අභියෝග

Jinsi Data Angavu AI Ilivyofanya Uchakachuaji/Ukusanyaji wa Data ya Wavuti Bila Jitihada: Changamoto Kabla ya Suluhisho Mkali za Data AI

எப்படி பிரைட் டேட்டா AI இணையத் தரவை ஸ்கிராப்பிங்/சேகரிப்பதை சிரமமின்றி உருவாக்கியது: பிரைட் டேட்டா AI தீர்வுகளுக்கு முன் உள்ள சவால்கள்

کس طرح برائٹ ڈیٹا اے آئی نے ویب ڈیٹا کو اسکریپنگ/جمع کرنے کو آسان بنایا: برائٹ ڈیٹا اے آئی کے حل کے سامنے چیلنجز

Bright Data AI đã giúp việc thu thập/sao chép dữ liệu web trở nên dễ dàng như thế nào: Những thách thức trước khi có giải pháp Bright Data AI

What is a Directory and Why Do You Need One? Owning a directory = owning a free infinite marketing channel. I build at least 1 new directory per month. It is my investment in the future 😊 In this inspiring article, let me explain what is a directory and why you need one too. What is a Directory? A directory is a website with a list of useful links. An owner of a directory has experience in the niche, so the items' set is better than you would find on Google. Let's take a look at one of mine's as an example: https://stripealternatives.com/ I gathered all alternatives to Stripe in one place. Why my directory is better than any of the top pages from Google? Because in the SERP, you will only see articles written by SEO experts. They have no idea about billing systems. They never managed a SaaS. Their set of links is 15 random items from Crunchbase or Product Hunt. Their article has near 0 value for the reader because the only purpose of the article is to bring traffic to the company's blog. What about mine? I tried a bunch of Stripe alternatives myself. Not just signed up, but earned thousands of real cash through them. I also read 100s of tweets about the experiences of others. I'm an expert now. I can even recognize good ones without trying them. The set of items I published is WAY better than any of the SEO-optimized articles you will ever find on Google. That is the value of a directory. Fun fact: Do you know what is the most popular product ever launched on Product Hunt? A directory! 🙂 Why Should You Care as a Maker? A directory brings free traffic!!!! 😎 You can use it to boost your main projects' sales. Imagine you have 10 directories, and each brings you 2k visitors per month. That is 20k/m. Assume that 5% will click the banner, and 5% of those will buy your SaaS. That is 50 sales every month with zero effort. If your SaaS is $50/m, that is +$2,500 MRR per month. The sweetest part is that if you start a new SaaS you will already have that marketing machine ready to be used 😎 Not only that. The swarm of directories gives you flexibility: You can boost the DR of your projects by linking them from your directories.
You can sell ads on directories and get passive income.
You can sell a directory and get quick cash.
You can turn a directory into a SaaS if you see it is getting good traction. My Directory Portfolio I've created 10 directories in 2024: https://launching.pro/ - all Product Hunt clones in one place.
https://stripealternatives.com/ - all Stripe alternatives in one place (for the folks who do not have access to Stripe).
https://acquire.website/ - a marketplace of small projects (you can sell your directory here btw!).
https://isora.me/tools/ - the list of tools I use to build startups.
https://cmscrawler.com/ - a directory of all CMS and website builders.
http://aivideo.tools/ - AI video tools, self-explanatory 😁
https://seoai.tools/ - AI tools for SEO (not only text generators!).
https://screencapturetools.com/ - WIP, the tools are picked by AI for now. This one is gonna go well with my video-related SaaS @paracast_io
https://startupideaspodcast.com/show/the-indie-startup-podcast/ - I needed a site for my podcast. So, I did not miss the chance to make yet another directory of all startup podcasts 😁
https://opensourceai.software/ - open-source AI projects (not only LLMs) The Plan My next step will be SEO optimizing the directories. That'd include cross-linking, keyword research+optimization, and writing blog posts. Then I plan to create 25 more! 😎 Follow my directory saga on 𝕏 👉 https://x.com/alexanderisorax What is a Directory and Why Do You Need One? Owning a directory = owning a free infinite marketing channel. I build at least 1 new directory per month. It is my investment in the future 😊 In this inspiring article, let me explain what is a directory and why you need one too. What is a Directory? A directory is a website with a list of useful links. An owner of a directory has experience in the niche, so the items' set is better than you would find on Google. Let's take a look at one of mine's as an example: https://stripealternatives.com/ https://stripealternatives.com/ I gathered all alternatives to Stripe in one place. Why my directory is better than any of the top pages from Google? Because in the SERP, you will only see articles written by SEO experts. They have no idea about billing systems. They never managed a SaaS. Their set of links is 15 random items from Crunchbase or Product Hunt. Their article has near 0 value for the reader because the only purpose of the article is to bring traffic to the company's blog. What about mine? I tried a bunch of Stripe alternatives myself. Not just signed up, but earned thousands of real cash through them. I also read 100s of tweets about the experiences of others. I'm an expert now. I can even recognize good ones without trying them. The set of items I published is WAY better than any of the SEO-optimized articles you will ever find on Google. That is the value of a directory. Fun fact: Do you know what is the most popular product ever launched on Product Hunt? A directory! 🙂 Why Should You Care as a Maker? A directory brings free traffic!!!! 😎 You can use it to boost your main projects' sales. Imagine you have 10 directories, and each brings you 2k visitors per month. That is 20k/m. Assume that 5% will click the banner, and 5% of those will buy your SaaS. That is 50 sales every month with zero effort. If your SaaS is $50/m, that is +$2,500 MRR per month. The sweetest part is that if you start a new SaaS you will already have that marketing machine ready to be used 😎 Not only that. The swarm of directories gives you flexibility: You can boost the DR of your projects by linking them from your directories. You can sell ads on directories and get passive income. You can sell a directory and get quick cash. You can turn a directory into a SaaS if you see it is getting good traction. You can boost the DR of your projects by linking them from your directories. You can sell ads on directories and get passive income. You can sell a directory and get quick cash. You can turn a directory into a SaaS if you see it is getting good traction. My Directory Portfolio I've created 10 directories in 2024: https://launching.pro/ - all Product Hunt clones in one place. https://stripealternatives.com/ - all Stripe alternatives in one place (for the folks who do not have access to Stripe). https://acquire.website/ - a marketplace of small projects (you can sell your directory here btw!). https://isora.me/tools/ - the list of tools I use to build startups. https://cmscrawler.com/ - a directory of all CMS and website builders. http://aivideo.tools/ - AI video tools, self-explanatory 😁 https://seoai.tools/ - AI tools for SEO (not only text generators!). https://screencapturetools.com/ - WIP, the tools are picked by AI for now. This one is gonna go well with my video-related SaaS @paracast_io https://startupideaspodcast.com/show/the-indie-startup-podcast/ - I needed a site for my podcast. So, I did not miss the chance to make yet another directory of all startup podcasts 😁 https://opensourceai.software/ - open-source AI projects (not only LLMs) https://launching.pro/ - all Product Hunt clones in one place. https://launching.pro/ https://stripealternatives.com/ - all Stripe alternatives in one place (for the folks who do not have access to Stripe). https://stripealternatives.com/ https://acquire.website/ - a marketplace of small projects (you can sell your directory here btw!). https://acquire.website/ https://isora.me/tools/ - the list of tools I use to build startups. https://isora.me/tools/ https://cmscrawler.com/ - a directory of all CMS and website builders. https://cmscrawler.com/ http://aivideo.tools/ - AI video tools, self-explanatory 😁 http://aivideo.tools/ https://seoai.tools/ - AI tools for SEO (not only text generators!). https://seoai.tools/ https://screencapturetools.com/ - WIP, the tools are picked by AI for now. This one is gonna go well with my video-related SaaS @paracast_io https://screencapturetools.com/ @paracast_io https://startupideaspodcast.com/show/the-indie-startup-podcast/ - I needed a site for my podcast. So, I did not miss the chance to make yet another directory of all startup podcasts 😁 https://startupideaspodcast.com/show/the-indie-startup-podcast/ https://opensourceai.software/ - open-source AI projects (not only LLMs) https://opensourceai.software/ The Plan My next step will be SEO optimizing the directories. That'd include cross-linking, keyword research+optimization, and writing blog posts. Then I plan to create 25 more! 😎 Follow my directory saga on 𝕏 👉 https://x.com/alexanderisorax https://x.com/alexanderisorax

Here's Why Owning a Directory = Owning a Free Infinite Marketing Channel

Ето защо да притежавате директория = да притежавате безплатен безкраен маркетингов канал

Δείτε γιατί να κατέχετε έναν κατάλογο = να κατέχετε ένα δωρεάν απεριόριστο κανάλι μάρκετινγκ

Por qué tener un directorio equivale a tener un canal de marketing infinito y gratuito

Tässä on miksi hakemiston omistaminen = ilmaisen äärettömän markkinointikanavan omistaminen

Evo zašto posjedovati imenik = posjedovati besplatni beskonačni marketinški kanal

ディレクトリを所有することは、無料の無限のマーケティングチャネルを所有することと同じである理由

នេះ​ជា​មូល​ហេតុ​ដែល​ធ្វើ​ឱ្យ​មាន​បញ្ជី​ឈ្មោះ = ការ​ធ្វើ​ជា​ម្ចាស់​ឆានែល​ទីផ្សារ​គ្មាន​កំណត់​ដោយ​ឥត​គិត​ថ្លៃ

Бул жерде эмне үчүн каталогго ээ болуу = Акысыз чексиз маркетинг каналына ээ болуу

Ity ny antony hananana lahatahiry = fananana fantsona ara-barotra tsy manam-petra maimaim-poana

Еве зошто да поседувате директориум = да имате бесплатен бесконечен маркетинг канал

Лавлах эзэмших нь = Чөлөөт хязгааргүй маркетингийн суваг эзэмшихийн учрыг эндээс харж болно

Вот почему владение каталогом = владение бесплатным бесконечным маркетинговым каналом

 Passes VS Patreon: A User's Review

In recent years, the venture capital (VC) industry has witnessed significant disruptions, spurred by new technologies and innovative business models. Among these disruptors is LemonRocks, a platform that is redefining how investments are made through a community-centric, data-driven approach. Unlike traditional VC models, which often rely on closed-door decision-making and a limited set of inputs, LemonRocks leverages the collective intelligence of its community, underpinned by robust data analytics, to democratize the investment process. The Shortcomings of Traditional Venture Capital Traditional venture capital has long been criticized for its exclusivity and lack of transparency. A small number of individuals—typically partners at VC firms—make high-stakes investment decisions based on personal networks and subjective judgment. This model not only limits access to capital for many promising startups but also leads to inefficiencies, such as overlooking viable businesses that fall outside of established networks. Moreover, the process is often opaque, with little visibility into how decisions are made and what data informs them. The lack of inclusivity and transparency has created barriers for both entrepreneurs and potential investors who are outside of this elite circle. A New Paradigm: LemonRocks’ Data-Driven, Community-Centric Model LemonRocks introduces a new paradigm by integrating data analytics and community participation into the venture capital process. At the core of this model is the belief that the collective intelligence of a diverse group can provide more accurate, comprehensive insights than the intuition of a few individuals. The platform allows community members to participate in the evaluation of startups, contribute data, and vote on investment opportunities, all facilitated through LemonRocks’ proprietary token system. The platform’s approach to leveraging community input is grounded in the theory of crowdsourced intelligence, which suggests that a large, diverse group is often better at predicting outcomes and making decisions than individual experts. This concept is not merely theoretical; it is backed by research in fields ranging from economics to behavioral science. Insights from the Founder: A Data-Driven Vision Shared at TEDx Berkan Y. Altun, the co-founder of LemonRocks, has been a vocal advocate for data-driven decision-making and the power of community engagement. In his TEDx talk, “How Data Rewrote My Life,” Altun shared his personal journey and the pivotal role data has played in his entrepreneurial success. Drawing on his experiences from previous ventures and extensive work in the tech industry, Altun highlighted how data can unlock new opportunities and drive innovation when used effectively. Altun’s vision for LemonRocks is rooted in the idea that data, when combined with community participation, can create a more equitable and efficient investment ecosystem. His insights into the limitations of traditional models and the potential of data-driven approaches have resonated widely, positioning LemonRocks as a forward-thinking player in the venture capital space. The technical backbone of LemonRocks is provided by its Chief Technology Officer (CTO), an ex-Head of Engineering at NEAR Protocol. With a strong background in blockchain technology and a deep understanding of decentralized systems, the CTO has been instrumental in building LemonRocks’ platform. His experience at NEAR, a leading blockchain protocol known for its high throughput and low latency, has influenced LemonRocks’ architecture, enabling it to handle complex data analytics and community interactions seamlessly. Under his leadership, LemonRocks has developed advanced tools for data collection, analysis, and visualization. These tools allow the platform to aggregate and interpret data from various sources, including community input, market trends, and startup performance metrics. The result is a dynamic, data-rich environment where investment decisions are driven by empirical evidence rather than gut instinct. Expert Guidance: A Network of Influential Advisors from Crunchbase and Credit Suisse LemonRocks’ innovative approach is further strengthened by its impressive advisory board, which includes industry leaders from some of the most influential companies in the tech and finance sectors. Advisors from Crunchbase, Dropbox, Credit Suisse, and Apple bring a wealth of experience and insights, providing strategic guidance to the LemonRocks team. These advisors contribute their expertise in areas such as data analytics, product development, and financial strategy, helping LemonRocks refine its platform and expand its reach. Their involvement not only validates the company’s vision but also ensures that LemonRocks remains at the cutting edge of technological and financial innovation. Leveraging AI: Training the Community-Driven LLM with Verify-to-Earn One of LemonRocks’ most innovative features is its use of large language models (LLM) and artificial intelligence to enhance community-driven decision-making. Through a unique verify-to-earn model, community members can contribute to the training of these AI models by verifying data, providing feedback, and participating in the evaluation of startups. This not only enriches the AI’s ability to provide nuanced, context-aware insights but also rewards community members for their contributions. The verify-to-earn model is a cornerstone of LemonRocks’ community-centric approach. By incentivizing data verification and contribution, the platform ensures that its AI models are continually updated with high-quality, verified data from a diverse range of sources. This process significantly enhances the accuracy and relevance of the platform’s investment recommendations, making it a powerful tool for community members and investors alike. Additionally, a significant portion of LemonRocks’ revenue is allocated to the buyback of $LEMON, the platform’s native token. This not only supports the token’s value but also aligns the platform’s success with the financial well-being of its community members. By reinvesting in its ecosystem, LemonRocks creates a virtuous cycle where the benefits of its growth are shared among all participants. Democratizing Access to Capital One of the most significant impacts of LemonRocks’ model is its potential to democratize access to capital. In traditional venture capital, funding is often concentrated in a few geographical regions and among a select group of entrepreneurs. LemonRocks, by contrast, opens up opportunities to a global community of investors and startups. This not only diversifies the pool of available capital but also brings new perspectives and ideas into the investment process. The platform’s use of tokenized participation allows anyone with an internet connection to contribute to and benefit from the venture capital ecosystem. This has the potential to unlock significant economic value, particularly in emerging markets where access to capital is often limited. Conclusion: A Data-Driven Future for Venture Capital As LemonRocks continues to grow, it is clear that its data-driven, community-centric approach represents a significant evolution in the venture capital model. By combining the power of data analytics, community participation, advanced AI, and strategic guidance from advisors at Crunchbase, Dropbox, Credit Suisse, and Apple, LemonRocks is creating a more inclusive, transparent, and effective way to fund innovation. For those who believe in the transformative potential of data and community, LemonRocks offers a glimpse into the future of venture capital—one that is smarter, fairer, and more accessible than ever before. In recent years, the venture capital (VC) industry has witnessed significant disruptions, spurred by new technologies and innovative business models. Among these disruptors is LemonRocks , a platform that is redefining how investments are made through a community-centric, data-driven approach. Unlike traditional VC models, which often rely on closed-door decision-making and a limited set of inputs, LemonRocks leverages the collective intelligence of its community, underpinned by robust data analytics, to democratize the investment process. LemonRocks LemonRocks The Shortcomings of Traditional Venture Capital The Shortcomings of Traditional Venture Capital Traditional venture capital has long been criticized for its exclusivity and lack of transparency. A small number of individuals—typically partners at VC firms—make high-stakes investment decisions based on personal networks and subjective judgment. This model not only limits access to capital for many promising startups but also leads to inefficiencies, such as overlooking viable businesses that fall outside of established networks. Moreover, the process is often opaque, with little visibility into how decisions are made and what data informs them. The lack of inclusivity and transparency has created barriers for both entrepreneurs and potential investors who are outside of this elite circle. A New Paradigm: LemonRocks’ Data-Driven, Community-Centric Model A New Paradigm: LemonRocks’ Data-Driven, Community-Centric Model LemonRocks introduces a new paradigm by integrating data analytics and community participation into the venture capital process. At the core of this model is the belief that the collective intelligence of a diverse group can provide more accurate, comprehensive insights than the intuition of a few individuals. The platform allows community members to participate in the evaluation of startups, contribute data, and vote on investment opportunities, all facilitated through LemonRocks’ proprietary token system. The platform’s approach to leveraging community input is grounded in the theory of crowdsourced intelligence, which suggests that a large, diverse group is often better at predicting outcomes and making decisions than individual experts. This concept is not merely theoretical; it is backed by research in fields ranging from economics to behavioral science. Insights from the Founder: A Data-Driven Vision Shared at TEDx Insights from the Founder: A Data-Driven Vision Shared at TEDx Berkan Y. Altun, the co-founder of LemonRocks, has been a vocal advocate for data-driven decision-making and the power of community engagement. In his TEDx talk, “How Data Rewrote My Life,” Altun shared his personal journey and the pivotal role data has played in his entrepreneurial success. Drawing on his experiences from previous ventures and extensive work in the tech industry, Altun highlighted how data can unlock new opportunities and drive innovation when used effectively. Altun’s vision for LemonRocks is rooted in the idea that data, when combined with community participation, can create a more equitable and efficient investment ecosystem. His insights into the limitations of traditional models and the potential of data-driven approaches have resonated widely, positioning LemonRocks as a forward-thinking player in the venture capital space. The technical backbone of LemonRocks is provided by its Chief Technology Officer (CTO), an ex-Head of Engineering at NEAR Protocol. With a strong background in blockchain technology and a deep understanding of decentralized systems, the CTO has been instrumental in building LemonRocks’ platform. His experience at NEAR, a leading blockchain protocol known for its high throughput and low latency, has influenced LemonRocks’ architecture, enabling it to handle complex data analytics and community interactions seamlessly. Under his leadership, LemonRocks has developed advanced tools for data collection, analysis, and visualization. These tools allow the platform to aggregate and interpret data from various sources, including community input, market trends, and startup performance metrics. The result is a dynamic, data-rich environment where investment decisions are driven by empirical evidence rather than gut instinct. Expert Guidance: A Network of Influential Advisors from Crunchbase and Credit Suisse Expert Guidance: A Network of Influential Advisors from Crunchbase and Credit Suisse LemonRocks’ innovative approach is further strengthened by its impressive advisory board, which includes industry leaders from some of the most influential companies in the tech and finance sectors. Advisors from Crunchbase, Dropbox, Credit Suisse, and Apple bring a wealth of experience and insights, providing strategic guidance to the LemonRocks team. These advisors contribute their expertise in areas such as data analytics, product development, and financial strategy, helping LemonRocks refine its platform and expand its reach. Their involvement not only validates the company’s vision but also ensures that LemonRocks remains at the cutting edge of technological and financial innovation. Leveraging AI: Training the Community-Driven LLM with Verify-to-Earn Leveraging AI: Training the Community-Driven LLM with Verify-to-Earn One of LemonRocks’ most innovative features is its use of large language models (LLM) and artificial intelligence to enhance community-driven decision-making. Through a unique verify-to-earn model, community members can contribute to the training of these AI models by verifying data, providing feedback, and participating in the evaluation of startups. This not only enriches the AI’s ability to provide nuanced, context-aware insights but also rewards community members for their contributions. The verify-to-earn model is a cornerstone of LemonRocks’ community-centric approach. By incentivizing data verification and contribution, the platform ensures that its AI models are continually updated with high-quality, verified data from a diverse range of sources. This process significantly enhances the accuracy and relevance of the platform’s investment recommendations, making it a powerful tool for community members and investors alike. Additionally, a significant portion of LemonRocks’ revenue is allocated to the buyback of $LEMON, the platform’s native token. This not only supports the token’s value but also aligns the platform’s success with the financial well-being of its community members. By reinvesting in its ecosystem, LemonRocks creates a virtuous cycle where the benefits of its growth are shared among all participants. Democratizing Access to Capital Democratizing Access to Capital One of the most significant impacts of LemonRocks’ model is its potential to democratize access to capital. In traditional venture capital, funding is often concentrated in a few geographical regions and among a select group of entrepreneurs. LemonRocks, by contrast, opens up opportunities to a global community of investors and startups. This not only diversifies the pool of available capital but also brings new perspectives and ideas into the investment process. The platform’s use of tokenized participation allows anyone with an internet connection to contribute to and benefit from the venture capital ecosystem. This has the potential to unlock significant economic value, particularly in emerging markets where access to capital is often limited. Conclusion: A Data-Driven Future for Venture Capital Conclusion: A Data-Driven Future for Venture Capital As LemonRocks continues to grow, it is clear that its data-driven, community-centric approach represents a significant evolution in the venture capital model. By combining the power of data analytics, community participation, advanced AI, and strategic guidance from advisors at Crunchbase, Dropbox, Credit Suisse, and Apple, LemonRocks is creating a more inclusive, transparent, and effective way to fund innovation. For those who believe in the transformative potential of data and community, LemonRocks offers a glimpse into the future of venture capital—one that is smarter, fairer, and more accessible than ever before.

The Power of Data: How LemonRocks is Disrupting Venture Capital with a Community-Centric Approach

The Power of Data: Hvordan LemonRocks forstyrrer venturekapital med en fællesskabscentreret tilgang

El poder de los datos: cómo LemonRocks revoluciona el capital de riesgo con un enfoque centrado en la comunidad

Il potere dei dati: come LemonRocks sta rivoluzionando il capitale di rischio con un approccio incentrato sulla comunità

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د ډیټا ځواک: څنګه لیمون راکس د ټولنې متمرکز چلند سره د وینچر پلازمینه ګډوډوي

Сила данных: как LemonRocks меняет подход к венчурному капиталу, ориентируясь на сообщество

Моћ података: Како ЛемонРоцкс омета ризични капитал приступом усредсређеним на заједницу

Verinin Gücü: LemonRocks Topluluk Merkezli Bir Yaklaşımla Girişim Sermayesini Nasıl Sarsıyor?

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Sức mạnh của dữ liệu: LemonRocks đang làm gián đoạn hoạt động đầu tư mạo hiểm bằng cách tiếp cận lấy cộng đồng làm trung tâm

Amandla eDatha: Indlela i-LemonRocks ephazamisa ngayo i-Venture Capital kunye neNdlela ePhambili yoLuntu

Amandla Wedatha: I-LemonRocks Iphazamisa Kanjani I-Venture Capital nge-Community-Centric Approach

Learning Programming: Bewitched by Brilliant Gamification (A Sort of Product Review of Brilliant)

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Programmieren lernen: Verzaubert von Brilliant Gamification (Eine Art Produktrezension von Brilliant)

Aprendiendo a programar: fascinado por la gamificación de Brilliant (una especie de reseña de producto de Brilliant)

Apprendre la programmation : envoûté par la gamification brillante (une sorte de revue de produit de Brilliant)

प्रोग्रामिंग सीखना: ब्रिलियंट गेमिफिकेशन से मोहित (ब्रिलियंट की एक तरह की उत्पाद समीक्षा)

プログラミング学習: Brilliant のゲーミフィケーションに魅了される (Brilliant の製品レビューのようなもの)

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Aprendendo Programação: Enfeitiçado pela Gamificação Brilhante (Uma Espécie de Análise de Produto da Brilliant)

Обучение программированию: очарованные блестящей геймификацией (своего рода обзор продукта Brilliant)

Programlama Öğrenme: Brilliant Gamification'ın Büyüsü (Brilliant'ın Bir Tür Ürün İncelemesi)

Học lập trình: Mê mẩn với Gamification tuyệt vời (Một dạng đánh giá sản phẩm của Brilliant)

学习编程：着迷于 Brilliant 游戏化（Brilliant 的一种产品评论）

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