MARKET RESEARCH

Cluster App Store reviews into feature-request themes

Scrapes recent App Store and Google Play reviews, clusters them into recurring feature-request themes with a zero-shot classifier.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionScrape App Store + Play reviewsApify
  • LogicKeep only feature-request reviews
  • ActionZero-shot classify into themesHugging FaceHugging Face
  • LogicAggregate and rank themes by weighted demand
  • OutputUpsert ranked theme table to CodaCodaCoda

What it does

Every week this pulls fresh reviews for your app from both the Apple App Store and Google Play, isolates the ones asking for something new ("I wish it could…", "please add…"), groups them into named themes, and publishes a ranked table to Coda so product can see what users keep asking for.

When to use it

When your roadmap planning is driven by gut feel instead of evidence, and review volume is too high to read by hand. Best for teams that already track roadmap candidates in Coda and want a recurring, deduplicated signal of demand.

How it works

  1. 1A weekly schedule fires the run.
  2. 2Apify review scrapers fetch the latest reviews for your app IDs on both stores.
  3. 3A filter step keeps only reviews that express a request or unmet need, dropping pure praise and bug reports.
  4. 4A Hugging Face zero-shot model assigns each surviving review to a candidate feature theme and confidence score.
  5. 5A logic step aggregates themes, counts mentions, and computes a demand rank weighted by review recency and rating.
  6. 6The ranked theme table is upserted into a Coda doc, replacing last week's rows so the product team always sees current demand.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ApifyActors, scrapers, datasets.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect CodaDocs, packs, automations.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.