Al

Alphie – see who's on your website and chat with them from Slack

Hacker News

Alphie – see who's on your website and chat with them from Slack

Hi HN, Yura here, co-founder of Alphie. In my previous YC company, we got a lot of good traffic, but only about 3% of it ever converted to demos. We tried RB2B and many other visitor resolution tools - but weren't happy with the accuracy. So, after that company was acquired, we decided to build our own platform. We've found a way to achieve a much higher ID rate and accuracy than most of the previous-generation visitor ID tools. Company-level visitor identification is about 3 times more accurate than individual-level. We use a waterfall of several data providers to boost it a bit further. Then an agent analyzes your ICP, figures out the decision-makers - and closes the loop by enriching their data. The thing is, for B2B, knowing who was the actual person that visited your website matters less than knowing that a certain company is in the market. An unexpected side effect is that about 30% of companies can be identified via reverse IP lookup, which takes less than a second. This allows you to do two key things for conversion: Display content uniquely tailored to this visitor (e.g. a fintech startup sees a case study for a Series B payment platform). Rank them against your ICP - so you know if an important buyer is currently browsing your pricing page. Alphie does the personalization in the chatbot only so far, personalizing answers and showing relevant bits of content, but potentially it could be possible to generate a whole personalized version of the landing page. The ICP ranking is super interesting, because it allows you to pull in a human rep while the buyer is still on the website - the moment of highest intent. We're currently running 16 pilots, 10 of them with YC companies. Would love to hear your thoughts. Happy to answer anything, especially on the identification accuracy tradeoffs and the privacy architecture. Video Demo: https://www.youtube.com/watch?v=ZFjQwGfsR0k Interactive demo: https://meetalphie.com/demo/app.html

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1points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: agent, slack · Missing: mac, agents, macos
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, video, answers · Missing: mobile apps, ios, entrepreneurs
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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