AI Crypto Analytics for Gem Hunters

Meme coins move fast, and the data on new launches is scattered, unreliable, or too technical for most people to use. Experienced traders have the tools and instincts to navigate it. Newcomers don't. The app needed to aggregate data from 10+ platforms, analyze each token across dozens of parameters, and surface only the launches worth paying attention to, in a format anyone could understand, without requiring a trading background. On top of that, crypto is a high skepticism space. People don't trust a product to tell them what to buy, especially one they've never heard of.

I started outside the product entirely: competitor research, reviews of similar apps, and time spent in the subreddits and Discord servers where traders actually talk about what frustrates them and what they're trying to get out of the market. That research pointed to two problems that had to be solved together. Newcomers needed the data simplified. The product needed to earn trust before it could ask anyone to act on a recommendation. Every design decision that followed came back to one of those two things.

Segmented users from the start. Onboarding captured four things early: experience level, token preferences, portfolio size, and desired engagement level. This let the product speak differently to a newcomer than to someone already active in the market, without building two separate products.

Turned raw data into a research brief. Rather than presenting raw metrics, each recommended token came with a clear context layer: why it's on the list, who's already holding it, the background of the launcher, a pros and cons breakdown, risk level, and an estimated time window before a price drop. Complex data structured into a decision, not a spreadsheet.

Built trust directly into onboarding. Crypto is a high skepticism environment, so I embedded trust signals into the onboarding flow itself: user reviews and platform ratings, real portfolio examples with clear PnL performance, a list of partner platforms, and a refund guarantee if the strategy didn't deliver. The goal was to earn confidence before users ever saw the product.

Designed a two way AI assistant. Users could ask the assistant about market movements, specific coins, trends, or trading style. The assistant also pushed proactive updates on recommended tokens when conditions changed, reactive when users had questions, informative when the market moved.

Used notifications as a retention lever. Smart notifications covered successful deal alerts, portfolio reviews, and educational content. This never fully solved the trust problem on its own, crypto trust requires long term credibility built with established platforms, but it meaningfully improved engagement and gave users reasons to stay.

• 72% onboarding completion rate
• ~6.5% free to paid conversion
• 2,000+ users acquired in the first two weeks
• 16% day 30 retention

Trust remained the hardest problem to fully solve. In a high stakes industry like meme coin investing, design alone isn't enough. Credibility has to be earned through partnerships, track record, and education over time. The onboarding trust signals helped, but building a truly trusted crypto product is a long game.