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I scraped 25M Shopify products to build a search engine

Hacker News

I scraped 25M Shopify products to build a search engine

Hi HN! I built Agora as a side-project leading up to the holiday season. I wanted to find an easier way to find Christmas gifts, without needing to go store-by-store. My wife asked me for a a pair of red shoes for Christmas. I quickly typed it into Google and found a combination of ads from large retailers and links to a 1948 movie called 'Red Shoes'. I decided to build Agora to solve my own problem (and stay happily married). The product is a search engine that automatically crawls thousands of Shopify stores and makes them easily accessible with a search interface. There's a few additional features to enhance the buying experience including saving products, filters, reviews, and popular products. I've started with exclusively Shopify stores and plan to expand the crawler to other e-commerce platforms like BigCommerce, WooCommerce, Wix, etc. The technical challenge I've found is keeping the search speed and performance strong as the data set becomes larger. There's about 25 million products on Agora right now. I'll ramp this up carefully to make sure we don't compromise the search speed and user experience. I'd love any feedback!

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Actual performance

317points
268comments
Made the leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, wife, including · Missing: supports, reddit linkedin, podcasting
93%93% 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: google, user · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
59%59% 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, reviews, exclusive · Missing: plus, intuitive, host
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr, shopify · Missing: mrr, revenue, profit
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
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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