CrowdChunk

Deep insight into what consumers really think of mobile apps

2 followers

Deep insight into what consumers really think of mobile apps

2 followers

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Launch tags:Web App•Developer Tools•Tech

Launch Team

Zendesk for StartupsUp to 2 years free for startups + AI Agents & Copilot

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Product Hunt

This is super useful for apps with a medium to large number of reviews. Here's the Product Hunt iOS app. Fun fact: I just got off a call with the team discussing our upcoming redesign of the app. 💃

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11yr ago

Codeq Natural Language Processing API

Maker

@rrhoover Correct. We're useful to apps that have a lot of feedback. (by proxy a lot of passionate users) Product Hunt has enough users to generate relevant scores. We haven't been able to find any strong correlation in similar feedback. 55% of your app reviews are positive feedback. That's a great back pocket stat.

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11yr ago

Osaurus

Hunter

@rrhoover invite me to beta! The iOS app needs much love! :)

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11yr ago

Product Hunt

@chrismessina agreed! It's going to be so 🔥 but we're a ways from a beta. I'll keep you posted!

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11yr ago

Osaurus

Hunter

Really great (free?) alternative to App Annie. Slightly different offering, but I like the holistic, NLP-based approach.

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11yr ago

Codeq Natural Language Processing API

Maker

@chrismessina yep, we have a great lexical analysis engine looking at every review ever written about all apps on the iOS App Store and Google Play. What's cool is we look at entire statements, not just keywords, which is huge.

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11yr ago

Osaurus

Hunter

@russ_sm right -- but so, a lot of reviews are gibberish. How do you make sense of those? Also, have you detected any oddities/fake reviews/bots/spam?

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11yr ago

Codeq Natural Language Processing API

Maker

@chrismessina At the moment we focus on english reviews. English based reviews are the easies for us to detect precise feedback and emotion. Codeq is a precision over recall shop. We do have some baked in logic to notice when there's noise or a bot involved, but it's a work in progress. So far we've found our signals to be statistically accurate based on our expectations. Our computational linguistics team has spent a massive amount of time doing supervised learning to ensure we're filtering out questionable data.

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11yr ago

Codeq Natural Language Processing API

Maker

@chrismessina thanks for hunting us dude. CrowdChunk has been a labor of love. We've gathered a great team of people who think critically about app reviews and we hope you’ll find some of the insights we’ve generated useful. Looking forward to folks feedback and critiques. Interested in what people have to say about your app? or a friends app? or an app category? Check us out.

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11yr ago

Interesting - seems very useful. Is there a way to compare the results between different apps in my portfolio (ie if I'm a larger publisher and have dozens of apps?) Also - it would be cool if i could define my own terms (and related terms) to see what the score for that would be . Overall, I think it looks pretty cool

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11yr ago

Codeq Natural Language Processing API

Maker

@johnpjoseph Great ideas. Currently the only way to view a portfolio is by searching by publisher. We're working on better tools to compare apps at the moment. You're totally right.

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11yr ago

This seems like the type of tool that provides insights a product manager looks for from the support team to make sure satisfaction is high.

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11yr ago

Codeq Natural Language Processing API

Maker

@normanliang for now! We're really hoping to expand the feature set to encompass a lot of use cases. Really excited to see how people use it!

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11yr ago

@russ_sm it would be great to hear some ways people can use this today to solve problems you have encountered as a developer

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11yr ago

Codeq Natural Language Processing API

Maker

@normanliang Sure. One of the biggest use cases is looking at competitive apps, or apps within an entire category, to gauge who is winning with consumers. It's especially effective for app categories with lots of feedback. (EG: Games, Social, etc.) You can also look at data trends for specific apps over long ranges of time to compare when you released a feature and what effect it had on your consumer experience. We scan both Play and the iOS App store daily. That's more text than a human could ever read within 24 hours. We're doing something for developers humans simply can't do fast enough. We're finding insights you could only produce with machine learning at scale.

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11yr ago