Hi, my name is Nick Havryliak, and together with my co-founder Calson Shang, we are building Assisterr— Web3 analytics that combines fine-tuned ChatGPT and dynamic dashboards with up-to-date on-chain and off-chain data.

In this blog post, I will cover the following topics:

• My background, which has shaped the product my team is currently building;
• The challenges retail or non-professional investors face in web3;
• The Assisterr ideation process;
• Artificial Intelligence and Wall Street;
• My thoughts on the opportunities ChatGPT brings to web3 analytics.

About Myself

I started my career in management consulting as a product manager. Since 2017, I have been working with startup teams building in the ETH, Solana, NEAR, and Polkadot ecosystems. Alongside my professional track, I have also been buying and trading crypto.

The problem with retail investors

I remember my first 6 months in crypto — endless research, looking for “insights,” following opinion leaders, reading news and blog posts, making emotional decisions, and experiencing FOMO and FUD.

My idealized dreams of “invest X, get X2 in Y-time” were destroyed by reality.

I simply became a full-time market analyst, which wasn’t my goal at all.

By the end of the 2017 bull season, we entered a bear market — the first bear market of my life. It was a crazy time, and I lost up to 80% of the money I had previously earned in USD equivalent. It was painful to see how all those “promising” tokens became worthless, and there was nothing I could do about it.

“Between 73% and 81% of retail investors — end up losing money on these initial investments” — BIS report.

My story is not unique, and there are several reasons why non-professional investors keep falling into the same traps during waves of crypto or NFT hype:

• Poor emotional management — FOMO & FUD are the main enemies of retail investors. Resilience comes with time, and most investors learn how to manage themselves and avoid impulsive decisions only after experiencing peak negative and positive situations.

• Lack of financial intelligence — the industry is quite new, and an average non-professional investor who was a marketing expert, photographer, student, office worker, or trade staff on Amazon yesterday is not as skilled as they wish to be. There are many skills that pro investors learn over years, and it is naive to believe that anyone can learn them overnight. It takes time and consistency.

• Not knowing which metrics and data matter and how to validate them — there are pro analytic tools that pro-traders and VC analysts use, but the average retail investor doesn’t know SQL and is not as good at building custom dashboards. It’s quite hard to upskill yourself, especially if you don’t know what knowledge and skills you’re missing.

• Biased data all around — retail investors often rely on data from media or opinion leaders whom they believe are unbiased and trustworthy. But in fact, most of the content you may find about crypto & NFT projects on Google is paid marketing content promoted by the marketing & PR teams of the projects, or simply through bounty/grant programs for content creators. Promotional integrations are all around.

• Portfolio monitoring is time-consuming — it may become your full-time job instead of an investment if you try to monitor your portfolio and follow all updates for all your tokens & NFTs — news, announcements, on-chain activity, social activity, roadmap updates, competitors, macro-factors, and much more.

It took me years to gain the experience needed to find unbiased, high-quality, and accurate data sources for making investment decisions. Even now, my challenge is how to minimize the time I spend monitoring my portfolio.

Assisterr Ideation process

In Q4 2022, I joined the Entrepreneur First Acceleration Program in London where I met many future founders including my current co-founder Calson Shang (ML & Fullstack engineer).

Through market research and CustDev interviews, I shut down two startup ideas and start working on a third idea with Calson: analytics for web3 community managers based on user profiling and segmentation. However, we were too slow and focused on gathering Letters of Intent instead of delivering our product to the market. As a result, by the end of the program, over 10 startups worldwide raised funds to deliver similar products. We realized that the market is not as big and decided to find a less competitive and more interesting frontier.

After conducting more customer interviews with crypto investors, we discovered that new investors struggle to find unbiased data and understand all those metrics. As a result — they often rely on “experts” for recommendations. Through my conversations, I realized that I can relate to their experience as I was in their shoes.

We double-checked existing solutions, discussed them with retail investors, and defined critical disadvantages: tech complicity that I mentioned before and pricing — it is simply not affordable for retail investors to pay up to $3,000 monthly or $24,000 yearly for analytics they can’t even use properly.

In one of our interviews, I talked with an investor who paid $1,000 to join a 500+ member “smart investors” TG community that offered basic education, including an 8-page instruction on project analysis: social media activity, bots, engagement, on-chain activity, financial metrics, and news.

This manual required the same time-consuming analysis I did 6 years ago in my early crypto days. Disappointing.

But it was something for us as we already know how to aggregate and clear social and on-chain data as well as knew which data matters for investment decisions. We had something to offer to those thousands of people who are paying to be a part of such communities.

But what about the deeper aspect of the problem we have uncovered? How can we help users understand the intelligence we provide and give them the unbiased assistance they are seeking?

AI and Wall Street

Artificial intelligence (AI) has revolutionized the stock market. When Wall Street statisticians realized they could apply AI to many aspects of finance, including investment trading applications, it changed everything.

“Algorithmic trading accounts represent 60 to 73 percent of U.S. equity trading.” — report.

AI trading refers to the use of artificial intelligence, predictive analytics, and machine learning to analyze historical market and stock data. This helps investors get investment ideas, interpret the financial market, identify reasons behind price fluctuations, build portfolios, automatically buy and sell stocks, and monitor the ever-changing market.

AI tools provide hedge funds, investment firms, and stock investors with numerous benefits, including cutting research time and improving accuracy, predicting patterns, and lowering overhead costs.

Professional traders use these tools to aggregate intelligence and consult their clients or invest on their behalf.

So, why not give such tools to retail investors?

The reason is that they are still too heavy and highly expensive for the average investor and not self-explanatory. However, the next big thing has arrived in the form of ChatGPT, which has the potential to disrupt the entire industry.

ChatGPT opportunity in Web3

The existing version of ChatGPT is not very useful for investment decisions — it has generic information, old data sets, and no social or on-chain web3-related data. But we knew what to do and how to overcome this challenge by fine-tuning ChatGPT and becoming a web3 data wirehouse.

After discussing this with my co-founder Calson, we realized that our solution could fill a gap in the market:

Web3 analytics that combines fine-tuned ChatGPT and dynamic dashboards with up-to-date on-chain and off-chain data.

Using ChatGPT in Web3 analytics offers several benefits:

• Personalized recommendations: ChatGPT keeps the context and can offer personalized recommendations based on the investor’s level, risk tolerance, and interests;
• Virtual assistance: ChatGPT can serve as a virtual assistant and explain unknown metrics, correlations, and unusual deviations;
• Insights tracking: ChatGPT can alert you to risks and opportunities it recognizes as related to your portfolio and interests;
• Social element — community members may share their prompts and get rewards from other community members;

With all of this in mind, we are building Assisterr — a solution that I wish existed during my early days in the crypto world. We are thrilled to be here and excited to build what we are building.

We just released on Product Hunt last week and became the #2 Product of the Day with:

• 440+ upvotes

• 160+ comments from the community;

• 250+ registrations to the early Beta waitlist;

We would love to hear your thoughts. Please feel free to contact me on LinkedIn or Twitter, follow us on Twitter, and join our Discord.

Waitlist registration - assisterr.xyz