MARKET RESEARCH

Weekly competitor review theme brief in Coda

Every Monday, pulls the past week of competitor app-store reviews, clusters them into recurring complaint themes with an LLM.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerMonday 7am schedule
  • ActionScrape last 7 days of competitor reviewsApify
  • LogicFilter to negative reviews in window
  • ActionCluster reviews into ranked complaint themesOpenAI
  • OutputWrite dated theme brief to Coda docCodaCoda

What it does

Each Monday morning this workflow scrapes the previous seven days of reviews for a set of competitor apps, groups the free-text feedback into recurring complaint themes (e.g. "sync failures", "pricing confusion", "onboarding friction"), and publishes a ranked weekly brief into a Coda doc. Product reads one tidy page instead of hundreds of raw reviews.

When to use it

Use it when you track two or three competitors and want a standing weekly read on what their users are angry about — useful for roadmap input, positioning, and spotting gaps you can exploit before they patch them.

How it works

  1. 1A Monday 7am schedule fires the run.
  2. 2Apify scrapes the last 7 days of App Store and Play Store reviews for each tracked competitor.
  3. 3A filter drops reviews under three stars are kept and anything older than the window is discarded.
  4. 4OpenAI clusters the remaining reviews into named themes, counts each, and writes a two-line summary plus a representative quote per theme.
  5. 5The brief, themes ranked by volume and week-over-week change, is written into a Coda table as a new dated row.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ApifyActors, scrapers, datasets.
  2. 2
    Connect OpenAIModels, embeddings, files.
  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.

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