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Small is Beautiful — The Big Bang Launch Failure of Healthcare.gov

In light of the digitization happening now in the FinTech industry, it’s evident that operating in this space are trying their best to keep up with the pace. startups Compared to a few years ago, banks & fintech startups today are leveraging technology to improve how financial services are delivered. However, fintech marketers are finding it a bit complex to get rid of customer experience challenges and poor onboarding scenes. As a result, such shortcomings are costing them money in the form of users ditching their services and switching to competitors. To avoid such thousands of switches and help companies enhance their customer experience, animated FinTech videos are helping brands achieve their goals. But to give you a deeper perspective, here’s how videos are helping them solve their user experience and onboarding problems: Need help understanding how FinTech videos can help you strengthen your customer experience efforts? Enhancing User Experience for Better Customer Loyalty The digital transformation wave has to an extent, raised the expectation levels customers have from their favorite payment applications. It’s not at all surprising given the flexibility with which fintech companies are infusing creativity in creating a smooth navigational environment for their users. Here, when we talk about the role videos play in helping brands enhance the user experience, the mention of financial explainer videos is a must. The reason is that such videos can help you extend a positive user experience thus generating repeat business and solidifying customer loyalty. Moreover, a better customer experience will build user advocacy which will automatically make you stand out from your competitors in terms of customer service. Easing Customer Onboarding Journey for better Product Comprehension One of the biggest challenges fintech marketers and growth strategists face is providing their users with a hassle-free onboarding journey. The customer onboarding journey contains the successful implementation of various steps that lead to welcoming and activating new users, thus ensuring a transitional scene from a first-time user to a daily active user. To onboard customers smoothly in this highly competitive industry, brands need to identify all the customer experience parameters in advance. After identification, fintech videos can work as a one-stop solution to provide a crisp & guided explanation to users who have just signed up. Here’s an example video for better comprehension: How does PayPal work? In this tutorial video by , the digital payments giant walks its users through how they can set up their accounts, add card details, and begin shopping on millions of websites with secure & quick checkouts. PayPal By using quick representations of icons and illustrations, it crisply explains to users how they can seamlessly utilize the services of Paypal via any device. https://www.youtube.com/watch?v=WB370ewOklw&embedable=true As you already know, leading financial service platforms offer an array of services from digital banking & payments to investment and lending solutions. Now each service may come with a unique layer of user onboarding process which may make the process more complex to comprehend for the users. Exactly here is when website/app/portal walkthroughs come to the rescue of fintech marketers. To help you understand the significance and how walkthrough videos can help brands, check out the video example below: ICICI Bank - Animated Website Walkthrough Video Walkthrough videos are generally longer in nature, given the vast scope of activities they cover in a single shot. Similarly, with this video, introduces its customers to a completely fresh and revamped website using screen transitions and kinetic typography . ICICI animation style As a result, the video proves to be an excellent medium for ICICI to communicate its brand assets and raise awareness regarding the services it offers. https://youtu.be/OiwjhGVjPXg?embedable=true Now that you know animated videos can help you with solving the 2 core challenges, you must read the additional benefits that videos bring to your marketing efforts: 4 Ways in which FinTech startups can benefit from using Animated Videos for User Onboarding Considering the competitive fintech landscape of today, the importance of providing a smooth onboarding experience cannot be overstated. Since users have tons of options at their disposal, it’s important to provide them with quick access to all the features and benefits for frictionless onboarding. Here are the 5 benefits you must check out: 1. Simplifying Complex Concepts For obvious reasons, FinTech services often involve complicated concepts that may sound unfamiliar or confusing to users. However, with fintech videos, brands can break down these complexities into easily digestible chunks through the use of explainer characters and visual illustrations. Also by leveraging the art of , marketers can ensure the attention of viewers till the end of the video thus boosting the session duration on their platforms. brand storytelling 2. Building Trust and Transparency Everything aside, trust is the most important factor in the Fintech industry. Since brands deal with sensitive financial information day in and day out, explainer videos can play a vital role in building trust and credibility in the minds of users. By explaining security measures, data protection protocols, and regulatory compliance with the help of exciting visuals, such videos can strengthen a brand’s marketing efforts. 3. Enhancing Engagement & Retention Animated videos are engaging and visually appealing, thus making it easy for brands to capture users’ attention and keep them actively involved throughout the onboarding process. What makes this possible is the use of a compelling and rich infographics that easily produce engagement and help retain users on the application or platform. video script On top of that, when concepts are explained visually, the chances that users would remember and retain the information presented to them automatically increase, hence leading to higher conversion rates. 4. Accessibility and Convenience One of the biggest benefits of video explainers is their ability which lies in how easily they can be repurposed for distribution on various platforms. As a result, fintech startups can advertise their walkthrough and explainer videos on multiple channels where users can check out the videos at their convenience. Additionally, videos can be replayed and shared, allowing users to revisit important information whenever they require. Want to improve your Customers' Onboarding journey and increase the Retention Rate on your FinTech app/platform? Conclusion To say the least, if you wish to foster loyalty and better relationships, it’s necessary to provide industry-best service to avoid customer experience challenges. By ensuring your customers go through a hassle-free and quick onboarding, you can generate insane brand awareness and recognition from them. Also published here.

Strategies for Overcoming Customer Experience Challenges in the FinTech Startup Ecosystem

And I’ll tell you why. Naval Ravikant was probably the first person, if not the loudest, to declare “ideas” as the new oil. In his , he famously says: podcast The new oil is ideas. It’s all digital. All the new fortunes are being created in ideas space. At this point, you might be wondering: Naval has an answer to this: who the hell is making money by trading ideas? ..if you’re starting out today as a young, ambitious person, you don’t learn real estate; you don’t learn coal and oil mining; you don’t go into the extraction of physical resources to create wealth. You go into ideas space. You go into programming, books, movies, blogs, and podcasts and building robots, which are mostly intellectual property underneath. Before I dissect this, I’d like to define what “ideas” entail. Ideas are simply thoughts pregnant with action. So when Naval says fortune is in the ideas space, he’s hinting at the various mediums for knowledge transfer and inventions with tangible value. Or, put simply, "creations” you can monetize. Just look at Joe Rogan’s massively popular podcast, The Joe Rogan Experience. From Elon Musk to Quentin Tarantino, he got some of the most notable figures to engage in conversations with millions of listeners tuning in. The revenue from the podcast is also crazy good. He recently signed a $100 million deal with , giving up the show’s exclusive rights to the company. Spotify But unlike oil, ideas are not finite. They’re as diverse as the people who come up with them. Oil was valuable because it was scarce and expensive to dig. Then what about ideas? You have to attach a tangible value to ideas if you want them to work. Not every podcaster can get famous people like Elon Musk and Quentin Tarantino to share personal opinions, controversial or not. But Joe Rogan can, and that makes the entire difference. How Ideas Become Valuable Ideas we deem revolutionary today, for example, wheel, light bulb, mobile phone, or Internet — originated from a place of need. Can we say the same about the ideas of today? I believe we've now slowly moved on from ideating for “needs” to ideating for “convenience” and even for “nice to haves”. The technology space — a space brimming with ideas is a perfect example of this. If you look at the last couple of decades, most technological advancements like 5G, video calling, Learning Management Systems, eCommerce, AI, voice recognition, IoT, and cloud computing have only enhanced the connection and convenience in human life. But they’ve also made us lazier and fanatical in other respects. In his thought-provoking article on Rolling Stones, , Jonathan Taplin talks about the absurdity of investing “ ” How Elon Musk and Mark Zuckerberg Distort Reality to Sell Fantasy $20 trillion in fantasy worlds (missions to Mars, cryptocurrency, and the Metaverse) when real-world solutions to the critical problems of our planet are currently available? I mean, the goal of SpaceX is to “reduce space transportation costs and to colonize Mars.” It has definitely achieved the former, but the latter is a far cry for anyone, if at all achievable. In any case, the Tony Stark-like stature has surely raised the net worth of Elon Musk, earning him the interest and the finances from all around. That said, Musk’s idea with SpaceX took off because there was a real gap in the market that SpaceX filled with their inexpensive launches. But the thing is, most ideas don’t have any inherent value. It’s the execution, the making it happen part, that actually matters. How well the idea is shaped, developed, and monetized determines its true value. That’s why ideas that never take off are deemed fads, no matter how glamorously marketed. And the most glorious of them all? Metaverse, which was widely publicized with a lot of fanfare. But ever since ChatGPT set the stones of generative AI rolling, everybody seems to have declared the technology dead, if not downgrading its value. On a side note, tech journalists have been their sarcastic best, with some going as far as to call the technology a “low-quality, cartoon concert.” The Metaverse, the once-buzzy technology that promised to allow users to hang out awkwardly in a disorientating video-game-like world, has died after being abandoned by the business world. It was three years old. — , RIP Metaverse Ed Zitron Then again, if you’ve seen that video released, can you even blame them? Facebook Some final thoughts People who dug oil made fortunes like no other. But there were also people who tried and failed. And let’s not forget the widespread corruption and exploitation prevalent in the sector. I’m afraid similar violations are going to come up with generative AI on the scene. As you know, Generative AI doesn’t produce things out of ether. Already, AI tools like Midjourney and ChatGPT have unfairly stolen the hours of creative and mental labor put into creations by specialists across the fields. Yet there are no legal frameworks to protect the rights of the original creators. If what Naval claims is true and ideas are indeed the path to fortune, we’re at a tipping point in history with generative AI. Because now, machines will be ideating together with humans. This is going to complicate the legal setup for intellectual property and might even be exploitative to those standing on the lower rungs of the socioeconomic class. And I truly hope that’s never the case.

They Say “Ideas are the New Oil,” I Say Bullsh*t

তারা বলে "ধারণা হল নতুন তেল," আমি বলি বুলশ*টি

Sie sagen „Ideen sind das neue Öl“, ich sage Blödsinn

Dicen "Las ideas son el nuevo petróleo", yo digo tonterías

Ils disent "Les idées sont le nouveau pétrole", je dis des conneries

वे कहते हैं, "विचार ही नया तेल हैं," मैं कहता हूँ बकवास

彼らは「アイデアは新しい石油だ」と言うが、私はでたらめだと言う

그들은 "아이디어가 새로운 석유이다"라고 말하지만 나는 헛소리한다

Eles dizem que “as ideias são o novo petróleo”, eu digo besteira

Они говорят: «Идеи — это новая нефть», а я говорю чушь

Onlar “Fikirler Yeni Petroldür” Diyorlar Ben Saçmalık Diyorum

Họ Nói “Ý tưởng là loại dầu mới”, tôi nói nhảm nhí

他们说“想法是新石油”，我说废话*

Recently, while immersed in a game called "Factorio," I noticed striking parallels to the challenges encountered as the pioneer member of a data analytics team in a startup. In "Factorio," the game narrative revolves around an astronaut stranded on an alien planet with only raw materials at his disposal, tasked to build a spaceship for his escape. This scenario felt reminiscent of the real-world process of establishing an analytics team from scratch in a burgeoning startup. Let's visualize this scenario. You're just appointed the inaugural data and analytics team member in a fresh, promising startup. In your arsenal, you have an innovative product, abundant resources, and a horizon teeming with potential priorities. The questions then arise - where should you begin? What should be your initial thought process? How do you sequentially develop your strategy to construct an effective analytical team from scratch, which would eventually serve as a launchpad for the startup's trajectory? This article aims to delve into these intricate dynamics. : While this article draws parallels with the game Factorio, prior knowledge of the game isn't necessary to understand the insights shared; and for those familiar with Factorio, please pardon any oversimplification of the game mechanics for the sake of analogy. Disclaimer If you've ever wondered what it feels like to crash land on an alien planet with only your raw resources, congratulations – you're in a startup! Remember, a spaceship crash is just a pretty dramatic product pivot. Table of Contents Phase 1.  Manual/foundation Phase 2. Initiating automation Phase 3. Scaling Phase 4. Flight Conclusion As the inaugural member of the team in a startup, your journey is reminiscent of the first moments in "Factorio." Much like the astronaut, you're venturing into an alien planet, equipped with raw resources and the tools salvaged from your spaceship. These tools symbolize your wealth of knowledge, skills, and experience. Your mission? Transform these primary resources into a functioning rocket ship - a successful, scalable data analytics team. data analytics Phase 1. Manual/foundation In the initial phase of this mission, you're in exploration mode, much like the astronaut surveying his alien environment. You observe the data landscape, discover data sources (similar to mines of raw materials), and map out potential obstacles. This stage is all about understanding the topography of your new environment. It is a stage marked by high personal involvement, heightened curiosity, and hands-on work. You begin by manually gathering data from multiple sources, comparable to mining resources from different points in the game. You then create initial reports and analyses to better understand the product and business context. These reports serve as the first bricks in your rocket ship factory, offering valuable insights into your product's performance and customer behavior. Simultaneously, you forge relationships with various stakeholders in the startup - product managers, software engineers, marketers, and leadership. You communicate your findings, propose data-driven recommendations for product improvements, and even suggest simple A/B tests to validate your hypotheses. Your active involvement in these cross-functional dialogues enhances your understanding of the business and positions data as a crucial component in decision-making processes. Being the first data scientist in a startup is a bit like being the first one at the party - you're not quite sure where to put your coat, and you're a bit wary of double-dipping in the guacamole. However, this exploration and manual operation is challenging. This stage is labor-intensive and demands high levels of personal involvement. Analytics at this stage is manual, like a blacksmith forging tools by hand. Reporting involves connecting directly to data sources, stirring, and shaking data to understand what's happening. An ad-hoc analysis is frequent, which helps to understand unusual instances or random questions. Your nascent analytics infrastructure may also encounter hiccups that necessitate your manual intervention, sometimes leading to moments of realization about a forgotten piece that isn't working as it should. This stage can feel like a one-person show, where you're running around, juggling various tasks, and ensuring everything operate smoothly. While this phase may not be flexible or sustainable in the long run, it serves a vital purpose. It equips you with a deep understanding of the data landscape, the intricacies of the product, and the broader business context. You're intimately involved in shaping the foundation of your rocket ship factory, which imparts a rewarding sense of ownership and accomplishment. However, it's crucial to recognize when to transition from this manual, labor-intensive phase to a more automated, extendable model to avoid stagnation and burnout. This realization marks the end of stage one and the beginning of stage two: initiating automation. It's a vital turning point in your journey, keeping the evolution from a solitary explorer to a strategic architect aiming to build a robust, scalable data analytics team. Practical actions you can take at this stage Understand its sources, the relationships between different types of data, and the overall data architecture in your startup. Get to know your data. Start with developing essential reports that provide vital insights into your product or service. These can include user engagement metrics, performance metrics, sales, and revenue metrics, etc. Establish baseline reporting. These are custom, one-time pieces of research that are done on demand. Be prepared to perform ad-hoc analyses. Work closely with your colleagues, particularly those in product management and software engineering. Understand their needs, how they use data, and how you can help them make data-informed decisions. Collaborate with stakeholders. Phase 2. Initiating automation The initial stage's manual labor and high personal involvement serve a crucial purpose – they provide an intimate understanding of the data, business, and product context. This understanding is comparable to a detailed map of the alien planet in "Factorio," highlighting the rich mines of data, potential obstacles, and areas for exploration. However, a shift towards automation is necessary to ensure scalability and efficiency. As you transition into this phase, your role morphs from a hands-on miner to an architect. You begin to design processes that optimize the transformation of raw data into valuable insights, like setting up machines to automate the mining and refining of resources in the game. One of your primary tasks in this phase involves identifying bottlenecks in your processes – repeated frequently, essential for smooth operation, consuming a significant amount of your time, and, most importantly, can be automated. In the game of Factorio, it's akin to finding out which parts of the resource processing can be automated to free up time and boost efficiency. These tasks could range from ad-hoc analyses required for primary product metrics reporting, studies essential for A/B tests (such as power analysis for the new test and post-test analysis of the A/B test metrics), or even routine data gathering, joining, and transformation to answer recurring business questions. When setting up your initial data infrastructure, you'll often encounter a piece of code that no one dares to touch. It's like the support beam in a crumbling building - we don't know why it's holding everything up, but we're not about to pull it out to find out. As you identify these tasks, you adopt some of three primary strategies to streamline your workflow: : In "Factorio," a factory is an assembly line of automated machinery that takes in raw materials and churns out finished goods. In the world of data analytics, a 'factory' is a suite of tools and systems designed to automate your workflow. These may include workflow schedulers like Airflow, which automate regular tasks, dashboard systems such as Redash or Grafana, which automate reporting and foster a self-service environment for stakeholders; and ETL/ELT pipelines which automate data transportation and transformation. Building a factory : This is similar to inviting friends for a cooperative game in Factorio. Expanding your team involves hiring more data specialists. They bring diverse skill sets and perspectives, which accelerates progress and helps build robust analytics capabilities. Expanding your team : In Factorio, a technology tree represents all the possible upgrades and technological advancements. Similarly, in a startup, it refers to planning and implementing the necessary technology stack that supports your data needs, ensuring the scalable, long-term growth of your analytics operations. Developing a technology tree However, it's essential to maintain a balance during this phase. While it may be tempting to automate every process and hire extensively, ensuring these decisions align with the startup's financial resources and strategic goals is critical. Additionally, remember to design flexible systems that can adapt to evolving business needs – avoid creating a complicated, high-maintenance infrastructure that could become a burden in the future. The transition from stage one to stage two reminds me of evolving from an explorer to an architect in Factorio. It marks a significant shift in how you interact with data and sets the stage for your analytics team's scalable, efficient growth. The journey is far from over, and there are still stages to navigate, but the groundwork you've laid here will be instrumental in the coming stages. Practical actions you can take at this stage: This could include data cleaning tools, reporting software, dashboarding tools, etc. Look for tools that can help you automate your routine tasks. It can save you considerable time and increase efficiency. Identify tasks you perform frequently and look for ways to automate them. It involves setting up data pipelines, implementing a data warehouse, and setting up ETL processes. Start developing your data infrastructure. Look for individuals with skills that complement your own and can help you scale your operations. As you move to this stage, you may need to expand your team. Phase 3. Scaling In the previous stages, you've laid the foundation and initiated automation for your analytics operations, much like building a rudimentary factory on an alien planet in "Factorio." Now comes the time to scale, expand your operations, and prepare for growing demands. This phase is similar to increasing your factory, optimizing production lines, and preparing for larger, more complex challenges in the game. At this juncture, your analytics system is mainly automated, doing much of the routine work without your constant involvement. The system has morphed from a basic rocket ship factory into a more sophisticated operation. Yet, this is not the moment to rest but to gear up for more significant challenges. It's similar to the game scenario where resources become scarcer and demand multiplies - it calls for a strategic expansion. The scaling phase has three crucial components: : In "Factorio," as you exhaust local resources, you must build train networks to import materials from distant mines. Similarly, as your internal data resources need to be improved to drive deeper insights in a startup scenario, you might need to integrate third-party data or expertise. This could mean adopting external data APIs, forging partnerships for data sharing, or hiring external consultants or agencies with niche skills. External resource integration : Much like setting up dashboards to monitor your factory's efficiency in Factorio, it is crucial to establish robust performance tracking in a data analytics setup. Regularly monitoring your analytics system's performance, peak capacity, and identification of bottlenecks ensure its smooth operation. It also provides insights for future improvements and helps in proactive troubleshooting. Monitoring : In "Factorio," you often have to restructure your factory to accommodate new technologies or to make the production line more efficient. Similarly, in a data environment, refactoring or re-engineering your data pipelines, models, or reports might be necessary to improve efficiency, reduce computational costs, or incorporate changes in the business context. Refactoring Throughout this stage, the critical emphasis is on efficiency and optimization. While aiming for massive growth is tempting, the scale phase is more about 'smart' growth. It's about ensuring that your operations are extendable, maintainable, and flexible enough to adapt to the rapid changes characteristic of startup environments. Scaling up your processes is a bit like building your IKEA furniture - you start off with manual labor, realize you need some automation (or at least a power drill), and eventually, you’re standing back admiring your work, just to realize you’ve got some leftover parts. Did we really need that data pipeline, or was it just an optional extra? Scaling also includes planning for future growth. While you want to ensure that your current setup is efficient, you also want to anticipate the needs of your growing organization. This might mean investing in scalable technologies, planning for increased data storage and processing capabilities, or even initiating discussions about building a data warehouse. Much like the game "Factorio," the challenges are becoming more complex and demanding, but the opportunities for creativity and impact are also growing. As you navigate this stage, your role evolves from an architect to a city planner, meticulously planning and overseeing the growth and development of your analytics operations. And as you do so, you lay the groundwork for the final stage - the flight. Practical actions you can take at this stage Implement tools and processes to monitor the performance of your data infrastructure. Identify bottlenecks and areas for improvement. Continually look for ways to optimize your processes and data infrastructure. As your operations grow, you may find that specific processes or systems no longer meet your needs. Be prepared to refactor or redesign these as necessary. You may need to start integrating external data sources or systems. Establish new data pipelines or expand your data infrastructure. Phase 4. Flight Much like in "Factorio," where the ultimate goal is to build a rocket and escape the alien planet, in the context of a startup's analytics team, the 'flight' phase represents reaching a stage where your analytics operations are fully-functional, robust, flexible, and are driving strategic decisions and value creation. At this juncture, you're not just managing a data analytics operation; you're overseeing a well-oiled machine contributing significantly to the startup's trajectory. You have built a system that functions almost independently, only requiring your attention for high-level strategic decisions and occasional troubleshooting. However, just as in the game, reaching the final stage doesn't mean you're free from challenges. Even at this level, there are hurdles to overcome: : In "Factorio," the aliens evolve and become more of a threat as you progress. Similarly, competitors will continue to grow and innovate in a startup environment. You must ensure that your analytical capabilities continue to develop, staying ahead of the curve and providing the strategic edge your startup needs to thrive. Evolving competition : Time is a critical resource, especially for startups. Despite having a successful operation, you may need more help. It's essential to ensure that your analytics operation runs efficiently and that resources are allocated strategically to support continual growth and innovation. Resource constraints : Over time, some of your data processes and models may lose effectiveness or become outdated. Just as you would upgrade your factories and technologies in "Factorio," it's essential to regularly revisit and improve your analytics operations. Keeping your analytics tools and techniques up-to-date ensures you continue generating valuable insights. Decreasing marginal utility Therefore, the 'flight' phase is not about coasting but continual improvement, adaptation, and innovation. It's about maintaining the momentum built up and pushing for greater heights. Practical actions you can take at this stage Continually look for ways to improve your operations, whether through new tools, processes, or data analysis approaches. Don't rest on your laurels. This might involve learning new tools or techniques, attending conferences, or reading relevant publications. Keep up with developments in the field of data science. Use your data insights to inform these decisions and drive growth. You should contribute to your startup's strategic decisions at this stage. . Ensure that you are allocating your time, your team's time, and your budget to maximize return on investment. Be mindful of your resources Conclusion Establishing and growing an analytics team in a 0 → 1 startup environment can be an exciting, challenging, and rewarding journey - much like progressing through the stages of the game. Starting from basic manual work, you gradually build your operations, initiate automation, scale your capabilities, and finally reach the flight stage, where your analytics operations become vital to your startup's journey. However, each step requires different skills, strategies, and perspectives. Like in the game, you need to continually adapt, innovate, and strategize to ensure the success of your analytics operations and, consequently, your startup. By understanding and implementing this four-stage approach, you can survive and thrive in a 0 → 1 analytics team.

From Crashing to Lift-Off: How to Thrive as the First Data Scientist in a Startup

ক্র্যাশিং থেকে লিফ্ট-অফ পর্যন্ত: একটি স্টার্টআপে প্রথম ডেটা সায়েন্টিস্ট হিসাবে কীভাবে উন্নতি করবেন

Vom Absturz zum Start: Wie Sie als erster Datenwissenschaftler in einem Startup erfolgreich sind

충돌에서 이륙까지: 스타트업에서 최초의 데이터 과학자로 성공하는 방법

Çökmeden Kalkışa: Bir Startup'taki İlk Veri Bilimcisi Olarak Nasıl Başarılı Olunur?

Last week we rolled out some new branding for our website, replacing the hand-rolled branding which had previously been cobbled together by a team in which two of the three members were colorblind; it represents a massive improvement. How companies arrive at their branding is typically opaque to those outside the company (and often to some people within it!).  Prior to this exercise, nobody on our team had participated in a proper 0-1 branding exercise. Before we started, we weren’t able to identify many useful resources to help shape our expectations of what would be involved. That’s why we wanted to share our own process; hopefully it gives people a window-in and provides the reference point we wished we’d had. All the branding work for Speakeasy was done in partnership with our design partners, . Catalog What we were looking for Our design needs had three different aspects to it: Look & feel (color scheme, font, design elements, etc), logo, and mascot.  The need for look & feel, and a logo are pretty self-explanatory, but the desire for a mascot does require a brief explanation. We want Speakeasy to make API development a joyful activity. We believed that adding a mascot to serve as a companion for the journey through the product was something that could help bring delight to an otherwise utilitarian task. This is perhaps controversial, those old enough will still remember Clippy’s incessant and obtrusive bouncing.  But we think, when used sparingly and appropriately, a mascot can help bring personality to a user’s interactions with a new tool. Step 1: Defining Our Values For The Design Team Before the designers started, we needed to articulate what values were most important to our company, so they could be central to the design process.  During a couple of 1-hr sessions we focused on what is most important to our users, and therefore most important to us. We’re building the developer-first API platform; we make it easy for developers to ship quality APIs to their customers with confidence.  For developers, confidence in tooling comes from transparency and reliability. No snake oil, black boxes, or downtime. Our platform is honest with our users and consistent in its execution. As previously mentioned, we also believe that dev-first means building tools that are joyful for developers to use.  Too often, developer tooling means a product with a densely-technical website, a cryptic set of instructions, and no UX to speak of. Whatever we build, we want it to be approachable for users, and give them a direct path to unlocking value. These words: transparency, reliability, honesty, consistency, approachablilty, and directness were the ones we handed to our designers after our internal discussions. We then turned them loose to see what they could come up with. Iteration 1: Casting a wide net Our designers came back to us with four very different design styles for us to look through and give feedback on. The whole team individually recorded thoughts, before we collectively discussed them to provide condensed feedback. The main takeaway that emerged from the first iteration was that it was tricky to balance approachability with reliability. How do you project openness and friendliness without appearing too flippant? Designs #1 and #4, we thought both did a good job of projecting approachability but struggled to project reliability.  Meanwhile, Design #3 did the best job at projecting reliability, but wasn’t as friendly or approachable.  However, we felt sure that our future look & feel lay somewhere at the intersection of the three. In terms of logos, there was a strong preference for the logo designs in #1 and #3.  We did not want to have our mascot also serve as our logo. We felt that doing so would make them a static favicon, thus robbing them of the opportunity to have a personality. For iteration #2, we asked our designers to further refine the look & feel of the three options we had identified as having promise, with an eye toward cohesively integrating approachability and reliability. We also wanted to get more logo options and begin to think about how our mascot could sit comfortably within the larger branding. Iteration 2: Committing to a Look & Feel From the options we received, we were determined to select a single option to move forward with. We were therefore at a critical point in the branding cycle.  We decided to get opinions from the developer community.  We created a feedback survey which we sent out to all the developers who were signed up to trial our product to see what they thought. This feedback exercise was a great example of why it’s important to get quantitative and qualitative feedback.  We asked people to score each of the designs, then rank the three, and finally provide written commentary about each design: how would they describe each design? What words came to mind? Designs #1 (two cans of red bull) and #2 (Easy as A,P,I) scored significantly higher than design #3 (Smart and light at heart) with an edge going to design #2.  However, when we read through the responses, there was a much clearer alignment between design #1 and our team values.  Users responded with words like, “clean”, “reliable”, “to the point”, “approachable”. As for #2, people said it was professional, but they also said it, “popped”, was “bold” and “saturated”, reminded them of “Warby Parker”, or “modern 70s design”.  None of these are negative descriptions! Sentiment was overwhelmingly positive. They rated it very highly, but we felt that in some ways the design obscured the messaging we wanted to deliver. We therefore decided to go with design #1 as the basis for our look and feel. With that decided, we turned our attention to the logo and mascot. Iteration 2: Logo & Mascot Our user survey also gathered feedback on the mascot and logo choices.  The 16-bit pixelated mascot style had an overwhelmingly positive response, especially among the developers we interviewed (Stardew Valley has clearly left an impression on the community). However, this was slightly at odds with the most popular logo; #8 was a clear favorite.   We felt strongly about consistency in design style. If we had a pixelated mascot, then we wanted a pixelated logo (i.e. logos 1,2,3).  However we didn’t feel strongly about any of the logos presented, so we pushed our designers for some more options, specifically one with a more distinct ‘S’ shape as opposed to the stacked blocks motif. We also internally had a discussion about what animal best represented the company (Mr. Diggsworth the Mole was sadly destined to be a placeholder). We discussed which animals we felt were hard workers (something we all aspire to), and very quickly focused on the natural world’s best engineers: beavers, ants, and bees. After some back and forth, we landed on Beezy the Speakeasy bee. One of nature’s most common and cutest builders.  That they live in (api)aries was an added plus! With our look and feel & mascot both decided, we headed into another iteration to put it all together… Iteration 3: Bringing it all together We were overjoyed with the iteration and felt like the branding was now in a place where we were ready to begin to see things come to life on a live webpage. And in fact, the branding that we have live on our website today isn’t very different from this design iteration. While building the site, a few minor alterations to the design were made after seeing what it looked like on a live screen. We swapped pink and yellow in the color hierarchy (yellow to primary accent, pink to secondary accent), and added some dark blue to the otherwise plain background.  With that, we had the final design: And that was that! That is the full story of how we arrived at the branding we are using today. If you’ve made it this far down the article, I hope it was interesting, and that you find it useful if you ever find yourself in the midst of a design exercise. I’m sure that with time our product will expand and we will want to make updates to our design. When we do, I’ll be sure to follow up with more notes on our process. If you’re interested in what Speakeasy is building, don’t hesitate to reach out! This article was first published . here

Startup Branding Process: How we decided on Look & Feel, Logo, and a Mascot

Each year, about 400,000 new industrial and enterprise robots , with over 3 million robots operating globally (as of February 2022). As per , 88% of businesses worldwide plan to adopt robotic automation into their infrastructure in the coming months. While the stats look bright and promising, there’re still a lot of challenges and bumps in the road that robotic companies, and startups, in particular, should overcome to ensure their business sustainability, competitive advantage, and growth. hit the market McKinsey To better understand the current market for enterprise robotic solutions in Europe and explore a typical robotic startup journey, I’ve talked to , Founder and “Robot Spawner” at , and his colleagues and , Co-Founders and robotics engineers. Mihai Crăciunescu Adapta Robotics Diana Baicu Cristian Dobre Adapta Robotics is a unique example of how a corporate robotic department can spin off into a standalone robotic scale-up. Enjoy the conversation below! Hi guys. Let’s start with a general robotic industry trends discussion. What sectors and industries use enterprise robots most actively today? Mihai Crăciunescu: Though many different industries use enterprise robotic solutions, most use cases are basically the same. As such, robotic use cases in automotive can be replicated in other sectors, from manufacturing to aviation and beyond. The need is the same throughout industries. At Adapta, we’re working with the medical, manufacturing, R&D, aerospace, and automotive sectors. However, the retail industry badly needs robots today to ensure automated solutions and customer retention. The level of adoption is still low, as retail businesses mostly automate simple processes like check-out while keeping many critical operations unautomated. This can drastically affect their user retention, new user acquisition, and top-line growth. Speaking about the automotive industry, in particular, do you agree with a statement that robots will drive forward the E.V. revolution? What do you generally think about the current level of robotic adoption in automotive? Mihai C: If you look at electric cars, they have a lot of sensors and actuators to make intelligent, automated decisions. So, they're robots per se. The assembly of such vehicles and their testing and validation are highly automated with robots, too. I believe automotive is already the most robotized industry, so it’s an excellent example of a sector that actively uses robots to reduce costs and increase productivity and efficiency. From your personal perspective and experience, what factors or challenges prevent enterprise robots from going mainstream? Is it cost, interoperability and compliance issues, lack of industry standards, talent shortage, or anything else? Mihai C: First, it’s a lack of understanding and resistance to change. Usually, non-technical founders and leaders have little or poor understanding of robotic technology and how it works. They’re used to traditional approaches, have legacy systems that somehow work, and view robotic automation as a high-risk investment that may not pay off well. So, to improve productivity and increase bandwidth, they prefer to hire and put more people and resources instead of building custom robots. They’re afraid that new technologies will undermine their status quo and bring about new challenges they don’t want to cope with. As such, “unwillingness to take a risk and navigate uncharted waters of automation is another blocker of mass adoption of robots.” Thirdly, that’s the cost. Building prototypes and manufacturing robots is a complex and high-investment endeavor that not every company can afford. External factors like a global shortage of semiconductors we’re experiencing now make the process even more expensive. And when you source engineers for your projects, do you face a shortage of qualified talents specialized in robotics? Mihai C: I believe this is a general problem all tech companies are facing now, especially in Europe. Hiring robotics engineers here in Europe is tough, as some time ago, local companies started outsourcing their hardware manufacturing and software solutions development to Asia or other countries. This created a massive gap in the market for robotic engineers. The most qualified engineers from Europe are typically recruited by the U.S. companies, which makes the competition for specialists even more fierce. And how do you solve this issue? Our approach to solving this issue is to grow talents internally as much as possible. We start by hiring A.I., electronics, or hardware engineers and continue building new skill sets on top of their existing ones to turn them into robotic engineers. As more robots enter different industry sectors, what new skills should employees pursue to handle them properly? What’s the best way to educate staff on how to work with robots? Mihai C: Our job as robot creators is to build and deliver robots that can be used literally by anyone. We always keep in mind that people who’ll be operating our robots aren’t necessarily technical, so we aim to deliver user-friendly solutions. Of course, when we at Adapta Robotics deploy our robots on the client’s site, we need to do some training, demo the features and show how the whole system works. However, it’s not rocket science to use them. I believe everyone should be able to use robots without any special knowledge. That’s the point. Since you’ve mentioned your company name, can you tell us your brand story? How did Adapta emerge, and why? Mihai C: Our journey started many years ago. Cristian and I met and teamed up while studying at the university. Our goal was to build robots for the university competition. With high-performance robots designed and built by our university robotics team, we competed internationally and came first in numerous national and international contests. Diana joined our team a bit later, in 2015, and helped us improve the performance of our competition robots and win the biggest robotics competition in Europe at that time – Robotchallenge Vienna. We experimented a lot with robotic tech, built prototypes of self-driving cars and other projects, which eventually helped us gain indispensable experience and robust internal expertise. At the same time, we started thinking about building – our flagship robot and the ultimate solution for testing touchscreen devices. To attract external investments, we applied for and attracted E.U. Funding. MATT In 2017, our well-knit robotic team joined a custom software development company rinf.tech, as its Robotic division. Having received the funding, we managed to build our first full-fledged robot MATT. This allowed us to explore potential markets to tap into, identify the needs of diverse industries, and propose testing solutions for each of them. To give MATT all features and capabilities it has today, we worked continuously to improve it. We enhanced its software suite by adding a user-friendly GUI and used new computer vision methods to perform on a new use case basis. As we customized and expanded MATT, we went on a roadshow and had much success at the Embedded World Conference in 2019. In 2021, we made a decision to spin off a rinf.tech robotic division into a standalone robotic brand independent of rinf.tech. Why? Mihai C: There were several reasons for this. First, we gained recognition from our customers who got confused with rinf.tech being a software services company that builds robots. Second, this move was required by our potential investors. We realized that scaling up internally at rinf.tech would be more difficult than scaling up a startup, so we decided to separate. What does the process of making enterprise robots look like? Does it follow a traditional software development lifecycle or take a completely different path? Mihai C: Regarding the software side, we follow software engineering standards and methodologies: we develop custom U.I., modules, and add-ons like in any other software product. But besides that, there’s a completely different area of logistics, choosing the right components, building hardware, prototyping, and testing. Our approach is to start with a robot design that can take from a couple of months to a year. Then we start developing small components to be used for robot testing. We create small prototypes that we test and develop firmware for. After that, we produce a robot prototype based on the chosen design and software modules we write. Then we start making changes and optimizations based on the prototype feedback and performance. As we work on the prototype improvement, we start seeing things we hadn’t seen before. After creating a second or sometimes a third version of the robot, we go for certification. It’s an extremely important step. If you plan to enter certain markets, certification is a must for your robot to operate legally and be monetized. To get certified, your product needs to be well engineered and tested. Poorly tested solutions can fail the certification. The certification process puts an emphasis on the safety of your robot. For example, if your robot needs 230V to operate, a certification process will prove that your robot is safe to be used alongside humans. Sometimes certification is required to ensure your robot can be used alongside other measuring devices and that it will not interfere with the data gathered by those tools. We ensure each of our products follows standards to pass certification with flying colors. Cristian Dobre: I want to add that while it’s easy to follow software development methodologies and best practices, it’s trickier for the hardware side. With hardware, you have several revisions that need to be properly tested. What’s unique about Adapta is that we all work on-prem to avoid miscommunication between remote teams and make sure software and hardware integrations work in concert. Such an approach also helps us minimize bugs and errors at production and reduce the time to build a robot, as we can have fewer revisions compared to other companies that build robotic solutions in a distributed manner. Working in-house as a well-oiled machine allows us to quickly fix issues, align better in real-time, and lower our clients’ costs. Mihai C: Such an approach also helps our robotic team a great deal. If at some point we want to make changes or follow a different direction, or if someone on our team wants to tap into a different technology (e.g., from embedded to A.I. development), they have a good opportunity to see the whole process, how things are put together and provide input or initiate product changes. We always work based on the team feedback, and having an entire team work on-premises means more efficiency and better commitment. What are the key challenges or bumps in the road you’re facing as a robotic scale-up? Mihai C: It all comes down to the specifics of the European startup and scale-up market. Over the past twenty years, European investors have focused primarily on funding software solutions. The average investor has little to no experience with hardware startups. So, the market is shaky when it comes to investing in robotic or hardware solutions in general. If you really want to grow and scale up, you need to move your business to the United States. Besides those challenges, we’re facing other obstacles. We specialize in custom robotic solutions, so we need to find investors interested in such solutions or having the right contacts in industries essential for your brand evolution. But it’s not impossible, which is good news. It’s just a matter of the right outreach strategy and meeting the right people. And while looking for investors, do you keep working on new robotic solutions? Or do you guys mainly focus on improving your existing robots? Mihai C: We do both at the same time. As we received feedback from the market, we updated our MATT's value proposition for customers, built different add-ons to improve performance, and created new specialized use cases. When it comes to ERIS, we’re working on developing new functionalities. ERIS is a robot that can scan retail store shelves and provide information about the stock and prices. We’re turning it into a real data machine because it scans a lot of products and generates a lot of data and insights that can be used by other retailers later on. Besides this, we indulge in other robotic projects like an autonomous wheelchair. And what piece of advice would you give to fellow robotic startup founders? What should they focus on in the first place? Mihai C: My advice would be to focus on the technology side of their products. They should try to develop something that would add real value to the market and try to make their solution as refined and polished as possible. This will help them find the first users, raise additional funds, or find a reliable tech partner. Technical aspects need strong feedback from the market to work properly. If your initial product idea fails to prove feasible, don’t give up, as you can still use your technology for other use cases. As such, do focus on the technology behind your robotic solution, as it’s the backbone of your business. Also, we have some supply chain issues, especially in the semiconductor area. So you need really good partners and vendors to help you build your stock of components. And eventually, you need a good investor to help you sustain your solution with potential clients, advice, new market penetration, and more. Diana Baicu: Also, when the product’s prototype is ready, it’s important to keep an open mind regarding potential clients. Most of the time, they provide extremely useful information about the industry you’re looking to tap into and about your future product. Make sure you talk to your first customers to define how your final product should be modified and fine-tuned. Improve and pivot based on their feedback. From your personal perspective, do you believe that A.I. and robots will eventually overtake human intelligence? How will humans and robots co-exist in the future? Mihai C: That’s a tricky question. In my personal opinion, robots can be far better than humans in some specific tasks and jobs. However, with general AI able to understand our environment and context and make the best decision every single time, I don’t see it happening at scale yet. But I still don’t believe robots will overtake human intelligence in the future. Diana B: Having all these perspectives from the sci-fi world and seeing that a lot of damage can be done without proper regulations, I think that once we see more improvements and better performances of robots, many different regulations will come into effect. This will help minimize the risk of A.I. overtaking human intelligence. Cristian D: My take on this would be that it doesn’t necessarily have to be a super general AI that takes over. With AI we have today, we can still misuse it and cause damage to society. So, I’d be more apprehensive about how people use A.I. against other people than if general AI will take over. Mihai C: I agree with both Diana and Christian. I want to add about regulations. If we look at biotechnology, for instance, Europe and the USA ban the creation of “designer babies” or experiments with DNA of certain species, while other countries don’t. Without proper regulations, new technologies can be developed and used against us. As such, regulations really make sense, but they should be applied and enforced globally to meet their goals and prevent damage that A.I. can potentially cause. Videos and images courtesy of Adapta Robotics. Please feel free to check out my interview with the Chief Innovation Officer about how to grow geeks into π-shaped R&D Engineers .

Navigating Uncharted Waters: a Robotic Startup Journey

( ) “In the USA alone, over 700,000 companies shut down every year. In 2019, prior to the pandemic, 928,000 out of the 1.04 million newly established companies had shuttered.” U.S. Small Business Administration, 2021 Can you briefly introduce your company? With more than 80% of companies worldwide that won’t survive up to 10 years, , roiquant is offering affordable startup intelligence to help founders reduce the risk of business failure. evidently high shutdown rate Our roiquant solutions empower founders to build strong competitive businesses with high ROI ( ) by analyzing the capital markets, competitive landscape, companies’ performance, business strategies, risk factors, and more for actionable insights. return on investment In other words, our proprietary cloud-based software application is built with analytical company performance data, private capital market data, business tools, and simulators, as well as an investors database, to serve aspiring and budding entrepreneurs building profitable businesses. Any highlights on your recent announcement to share? We recently launched our pitch deck analytics to perform an evidence-driven assessment in order to diminish investing decisions clouded by or , as well as safeguarding founders from bad actors who would breach confidentiality by irresponsibly sharing their fundraising pitch decks with competing businesses. prejudices biases In addition, we’re also in the midst of planning our first virtual preseed startup competition, taking place in the Q4 2022, to groom world-class founders solving real-world problems aligning with the United Nations’ Sustainable Development Goals. Learn more about United Nation’s 17 sustainable development goals. Can you share more insights on your solutions offerings? As a business intelligence solution, our pitch deck analytics focus on analyzing the business components and fundability of fundraising pitch decks instead of reporting the number of shares, analyzing presentation interactivity, evaluating creative and template design, and so on. Moreover, our on-demand pitch deck analytics is powered by industry comparison benchmarks, real market data, and proven frameworks to help founders foster commercial viability and competitive differentiation by guiding them to enhance their business offerings. Powered by our roiquant solutions, our virtual preseed startup competition will allow participants to safely fail, learn, innovatively prototype, and pivot/pitch their ideas throughout the qualifying, semi-final, and final rounds. Leading up to the final round, the top 30 finalists shall demo and pitch to a panel of judges ( ). serial founders and investors After evaluation, we will announce the 3 winners and reward them with our equity-free cash prize money. 5-figure cash prize for the first place and second place winners 4-figure cash prize for the third-place winner More information will be shared in the coming months, but in the meantime, you may consider . joining our waitlist to receive our latest updates What are your plans for the rest of the year? Apart from upgrading our current features and releasing new features ( ), we’ll be raising to further boost our early traction ( ), R&D in AI, large data storage and management, and hiring experienced talents ( ). shown below seed investment achieving product-market fit remote employment 🔄 Upgrade current features 👉 Data: shuttered companies, discontinued products, investors’ losses, bankruptcy, product showcase Improve user experience, new filters function; more enriched data 👉 Startup intelligence: a postmortem analysis New charts, comparison benchmarks; more enriched data 👉 Venture intelligence: portfolio analysis New charts, comparison benchmarks; more enriched data 👉 Competitive intelligence: competitive landscape Improve algorithms and user experience; more enriched data 👉 Tools: idea validation Improve algorithms, user experience, results reporting, scoring system, and feedback; more enriched data 👉 Tools: pitch deck analysis Improve algorithms, user experience, results reporting, scoring system, and feedback; more enriched data 👉 Simulation: pre-revenue business valuation Improve user experience and comparison benchmarks** 👉 Simulation: market sizing Improve user experience and comparison benchmarks 👉 Deals sourcing: very-early stage, early stage Improve user experience and new features 🆕 New features releases 👉 Referral flywheel: referral program, affiliate partnership, ambassador program 👉 Pricing: Pro plan Public APIs integration for developers and enterprises 👉 Pricing: Pro plan Licensing for enterprises 👉 Funding sourcing: growth stage, late-stage, post-IPO stage 👉 Deals sourcing: growth stage, late-stage 👉 Simulation: start-up cost budgeting 👉 Simulation: financial modeling 👉 Tools: no-code builder 👉 Virtual preseed startup competition: equity-free cash prize money What is the best thing about your company that people might not know about? Our bootstrapping company enjoys ( ) because: low operating expenses burn rate We’re headquartered in a small oil-rich country, and so we benefit from relatively low corporate income tax (18.5% on a threshold basis) and no capital gains tax, as well as no individual taxation, such as personal income, net wealth/worth, inheritance/estate, capital gains, capital duty, payroll, and social security taxes. Importantly, and are . pioneer industry companies companies with revenue that does not exceed SGD $1 million exempt from corporate tax Our government launched an internship program to train fresh graduates for the job market by subsidizing the salary of interns hired by companies for 18 months, which helped us groom our homegrown talents with lean budgeting to compete with our direct international competitors. About roiquant With a huge value-free plan, roiquant (roi-kwant) offers affordable startup intelligence to founders building high-ROI ( ) and a strong competitive business. When founders want to build a business with a strong competitive edge but do not have the right knowledge and affordable tools, roiquant solutions help founders validate the market at minimal cost, so they can make data-informed decisions to improve and innovate their business. return on investment For more information about roiquant’s award-winning solutions, visit and join on Discord. www.roiquant.com roiquant community Last edited on 28 April 2022. Republished at and originally interviewed by . viewpoints.roiquant.com Tech Company News

Startup Intelligence Company Roiquant Helps Founders Reduce Risk of Business Failure

In this article I'll give you a quick overview of the concept of international sanctions, how they work and how it may impact a FinTech company, especially from the standpoint of technical implementation and tools. There are so many conspiracy theories, wrong interpretations, and misconceptions about sanctions and sanctions scanning. People sometimes get totally overwhelmed and feel like sanctions and embargoes are even more stressful than GDPR or Brexit. So, where do international sanctions come from? Sanctions can be imposed by individual countries or international organizations and, simply speaking, there are 4 types of sanctions: (e.g. North Korea or Crimea). These sanctions are extremely rare because territorial sanctions usually impact a lot of innocent people who happen to live or be in that place. Territorial sanctions mean that you cannot offer your services on that territory at all. For example, your perfectly valid Visa card may not work in Crimea. Against a country or territory , sometimes called "Specially Designated Nationals" or "SDNs." Usually, those people are criminals, known members of terrorist organizations and politicians responsible for civil wars, human rights violations, and other international crimes. Against specific individuals . For example, there are specific sanctions against members of Hamas or the Taliban, regardless of their residence or nationality. There are specific sanctions against members of certain governments or governmental organizations (for example, against certain government officials in Venezuela or members of the Iranian Revolutionary Guards). This category of sanctions does not always specify the names of individuals (because people may join these groups at any time), but rather they say that any member of this group or organization is under sanctions, and therefore you cannot offer your financial services to them. Against members of certain groups or organizations For example, you cannot buy Iranian or Venezuelan oil, you cannot buy or sell arms with governments of certain African countries, you cannot export certain products to or from Russia, etc. Against certain industries or types of commercial activities. Why is this important? People often say or or and it’s not correct. “Iran is under sanctions” “Russia is under sanctions” “Venezuela is under sanctions” From the technical implementation standpoint, it sometimes makes a huge difference: either you block an entire country and cannot serve anyone there, or you find a way to detect and block a couple of dozens of people and can work with everyone else without breaking any laws. On the other hand – the consequences of even a single mistake can be huge, especially if those are OFAC (US) sanctions. "Fun" facts: there are some contradictory and mutually exclusive sets of sanctions, which can make the life of a compliance officer super interesting. The most common examples would be Cuba (the US still has sanctions against most activities in Cuba, but Europe has nothing against Cuba whatsoever) and Russia vs Ukraine (where both countries claim that the other side is an occupant and international criminal). How do you go about the technical implementation of sanctions compliance to keep it simple and reasonable? Usually, I recommend to implement the following basic rules (obviously those are a very general set of guiding principles, just for an illustration purpose): IP block North Korea and Crimea as a minimum. If you have US-based financial partners, they will likely force you to block Cuba, because they would want all their partners to be OFAC-compliant. Even if you are in Europe. Don’t support countries where there are lots of problems and little economic opportunity. For example, many of my clients decide not to support countries that are suffering from a long history of civil wars, or with known active terrorist organizations on their territory, simply because it’s hard to know for sure who is who in these countries, and it’s easier not to support these countries than to investigate extensively each application from there and treat it as high risk with enhanced monitoring requirements going forward. So, even though there are no sanctions against certain countries, you may still decide not to support them, purely based on risk/opportunity analysis. There are countries with political problems and restrictions around some economic activities there (e.g. various sanctions against certain industries and government officials in Russia) or even with known terrorist groups operating there (e.g. Taliban in Pakistan), but the overall economic opportunity is still interesting for many. In this case, you may decide to invest in good monitoring tools, hire experienced native-speakers for investigative work, and this would allow you to support, for example, Russian or Pakistani clients with reasonable safeguards. Hope this summary was helpful. If you have any questions - feel free to reach out. You can find my contact details on my . company website

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