MARKET RESEARCH
Negative Review Early-Warning Tracker in Airtable
Polls 1- and 2-star app reviews daily, classifies each by churn driver (bugs, pricing, missing features, performance), and logs every one to an Airtable base with a weekly trend…
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionScrape reviews, keep 1-2 starApify
- ActionClassify churn driver + severityOpenAI
- ActionUpsert review records to AirtableAirtable
- LogicCompare category trend vs last week
- OutputAlert Slack on rising categorySlack
What it does
This workflow watches your low-star reviews and turns them into a structured churn-risk log. Every negative review is tagged with the reason a user is unhappy and written to Airtable, where a rollup view shows which complaint categories are accelerating week over week.
When to use it
Use it when a sudden dip in ratings catches you off guard and you want a standing early-warning system. It suits founders and support leads who need to know whether the latest spike is about pricing, a broken release, or a feature gap before it becomes a review-bomb.
How it works
- 1A daily schedule starts the run.
- 2Apify pulls reviews from the App Store and Play Store, then a filter keeps only 1- and 2-star entries.
- 3OpenAI classifies each review into a churn-driver category and extracts a short quote and severity score.
- 4Each classified review is upserted as an Airtable record with category, rating, severity, store, and date.
- 5A logic step compares this week's category counts against the prior week.
- 6If any category jumps past a threshold, the workflow posts an alert to Slack naming the rising driver.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect AirtableBases, tables, views, automations.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Market Research workflows
Weekly Materiality-Ranked Filing Digest by Email
Each Friday, aggregates the week's regulatory filings across the coverage universe, ranks them by materiality.
Earnings Keyword-Spike Alert into Linear
Scans new earnings-call transcripts for a set of strategic keywords you care about, and when a competitor's mention frequency spikes above its historical baseline.
Allocate Sales Territory TAM from BigQuery Geo Data to HubSpot
When triggered by a webhook, queries BigQuery public ZIP-level business data to compute TAM per sales territory.
Discover Adjacent Segments from BigQuery and Rank Expansion Bets
On a schedule, scans BigQuery public industry data for fast-growing NAICS sectors adjacent to your core segments, scores them as expansion bets.
Blend BigQuery TAM with Live Competitor Signals into a Notion Brief
On demand, sizes a chosen segment from BigQuery public data, gathers current competitor signals via Brave Search, and synthesizes a one-page market brief into Notion.
Cross-Competitor Theme-Shift Analyst
An agent that gathers the latest earnings transcripts across all tracked competitors, compares this quarter's themes against the prior quarter stored in Coda.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.