MARKET RESEARCH

Daily feature sentiment scorecard in Coda

Every morning pulls the last day's app reviews, scores sentiment per feature, and upserts a rolling scorecard table in Coda so product can track which features are trending up…

CategoryMarket Research
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule
  • ActionScrape trailing 24h of app reviewsApify
  • ActionExtract feature mentions and sentimentOpenAI
  • LogicAggregate into per-feature daily averages and counts
  • OutputUpsert daily rows into Coda scorecard tableCodaCoda

What it does

Runs on a daily schedule, collects the previous day's reviews across your app store listings, and uses an LLM to break each review into feature mentions with sentiment. It then writes one row per feature per day into a Coda table, building a rolling time series that product and leadership can chart and filter without touching raw review text.

When to use it

Use it when you want a durable record of feature sentiment over time rather than one-off alerts. Good for weekly product reviews, roadmap prioritization, and spotting slow declines that no single-day alert would catch.

How it works

  1. 1A daily schedule kicks off the run.
  2. 2Apify scrapes reviews from the trailing 24 hours.
  3. 3OpenAI extracts feature mentions and a sentiment score from each review.
  4. 4The flow aggregates scores into per-feature daily averages and mention counts.
  5. 5Coda upserts one row per feature for the day into the scorecard table, keeping the time series clean and queryable.

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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