Weekly competitor openings digest for each store location

By General Input

Every Monday morning, scan for new competitor venues that opened near each of your stores and post a Slack digest with a "how worried should we be" take.

Integrations

  • Geolocation
  • Airtable
  • Slack

Type

Agentic Task

Categories

  • Operations
  • Marketing

Every Monday at 6am, run a competitor scan for each of my store locations and post a market intel digest to Slack.

My store list lives in Airtable. Use Airtable List Records to pull two tables:

1) A "Locations" table with one row per store. Each row has an address, a competitor category (for example "specialty coffee" or "boutique gym"), and a search radius in meters.

2) A "CompetitorSnapshots" table holding the prior week's nearby venues per store, so we can diff against it.

For each store in Locations:

- Use Geolocation Forward Geocode to turn the address into latitude and longitude.

- Use Geolocation Search Nearby Places with that location, the store's category, and the store's radius to find candidate competitor venues.

- For the top results, use Geolocation Get Place Details to pull rating, review count, opening hours, website, and Google Maps URL.

- Use your own judgment to filter out venues that don't actually match the competitor category (skip gyms when the category is coffee, skip chain pharmacies when we sell pastries, etc.). Category match is a reasoning step, not a hard string filter.

- Diff the cleaned list against the previous CompetitorSnapshots rows for this store. A venue counts as "new" if it wasn't in last week's snapshot, OR if its review count jumped enough to suggest it just opened. Skip stores where nothing changed.

- Use Airtable Create Records to refresh CompetitorSnapshots with this week's results for the store (so next Monday has a clean baseline). Batch in groups of 10.

- For each store that had new openings, use Slack Send a Message to post one digest message to the configured channel. The message should list each new competitor with its name, rating, review count, distance from the store, hours if available, website, and a Google Maps link. Add a one or two sentence take on how worried we should be, weighing rating, review count, and proximity. Higher rating plus closer distance equals louder warning.

If no store had any new competitor activity, send a single short "all quiet this week" Slack message instead of staying silent.

Ask me for: the Airtable base ID and the two table names, the Slack channel to post into, and reasonable defaults for what counts as a "meaningful" review count jump.

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