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Turning App Reviews into B2C Leads: Seeking Your Insights! | Clay

Discuss Anything

Turning App Reviews into B2C Leads: Seeking Your Insights!

·Oct 20, 2025 08:08 AM·

How I’m Trying to Turn App Reviews into B2C Leads — Would love your ideas! Hey everyone 👋 I’m Aleks — still pretty new to Clay and learning how to build more effective campaigns. Right now, I’m working on a B2C lead generation project in Germany, focused on the lottery & giveaway (Gewinnspiel) space. The concept . I’d like to scrape App Store / Google Play reviews from popular lottery apps (like Lotto24 or Lottoland) to identify potential users who are already engaging with these products — and then enrich, filter, and segment those reviews directly inside Clay. What I’m aiming to do:

Detect sentiment (positive/negative)
Extract emails or social handles (if publicly mentioned)
Classify potential users for outreach or remarketing

Where I’m a bit unsure: Would you recommend starting with an external scraper (like PhantomBuster or SerpAPI)? Or is there a way to handle this entirely inside Clay, perhaps using Sculptor and AI columns? I was also considering using Google Maps reviews or even Reddit threads as alternative data sources — but maybe there’s a smarter approach that fits Clay’s ecosystem better. I’m fully aware that GDPR and privacy compliance are key here ⚖️ — so I’m only exploring publicly available review content, not personal or inferred data. If anyone has tackled something similar (App Reviews → Lead Generation flow), I’d love to see how you structured your table, enrichments, and prompts. 🙏 Thanks so much in advance for any guidance or examples! — Aleks

5 comments

· Sorted by Oldest

Hunain F.
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Hi - Aleksandar Z. That’s a really creative approach using app reviews as a lead source for B2C campaigns is super smart especially in niches like lottery and giveaways where user intent is already strong I’d suggest starting with an external scraper like SerpAPI or Apify since they can reliably pull both App Store and Play Store reviews at scale. Once you have the raw data you can import it into Clay and then: Use AI columns for sentiment analysis and classification (e.g likely user, unhappy user, etc.) Use Sculptor to extract any structured data like emails, usernames, or keywords Run enrichments on the extracted handles/emails for segmentation and outreach Reddit and Google Maps reviews are also solid secondary sources especially if you want to test different audience behaviors. And yes you’re absolutely right to keep GDPR in mind as long as you’re only using publicly available info and not inferring private data you’re on the safe side. Would love to see how your first version turns out sounds like it could be a really powerful workflow once it’s automated end to end.
Cecil K.
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Hi Aleksandar Z., we're working on a tool that can potentially help out with this through an API. It goes a bit further than external scrapers, and supports all the sources you listed. Would you want to try it out? We're currently testing it out to get feedback. Did you already have a table going in Clay? Curious how close you've gotten with Sculptor and AI columns.
Aleksandar Z.
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Hunain F. Hi Hunain, thank you so much for the great tip! I wasn’t familiar with tools like SERP API and Apify yet — I’ll definitely give them a try and see how they perform. I’ll be happy to keep you posted on how it goes.👍🙂 Thanks again for your awesome feedback, Hunain! Best regards, Aleks
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Aleksandar Z.
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Cecil K. Hi Cecil, I’d be happy to test it out. My schedule is a bit tight at the moment, so it might take me a little while, but I’ll gladly give it a try. Thanks a lot for the offer!🙂✌️ Greetings from Germany, Aleks
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Cecil K.
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Appreciate that Aleks, I'll reach out over DM!