MARKET RESEARCH
Detect Segment TAM Shifts in BigQuery and Alert Slack
On a monthly schedule, recomputes TAM per segment from BigQuery public data, compares against the prior snapshot.
How it runs
The automated pipeline, trigger to output.
- TriggerMonthly recompute schedule fires
- ActionCompute current per-segment counts and snapshot in BigQueryBigQuery
- ActionDiff current vs prior snapshot for percent changeBigQuery
- LogicKeep only segments past the change threshold; else end silently
- ActionDraft change summary with OpenAIOpenAI
- OutputPost movement alert to SlackSlack
What it does
Watches your addressable market for real movement. Each month it recomputes establishment and employment counts per segment from BigQuery public business datasets, diffs them against the previous month's stored snapshot, and only alerts when a segment grows or shrinks past a percentage threshold you set, so the team hears about meaningful shifts instead of noise.
When to use it
When segment dynamics matter to your strategy and you want an early signal that a market is expanding or contracting. Useful for GTM, RevOps, and corp-dev teams tracking where to lean in or pull back.
How it works
- 1A monthly schedule triggers the recompute.
- 2A BigQuery action pulls current per-segment counts and writes the new snapshot to a results table.
- 3A second BigQuery action joins current against the prior snapshot to compute percent change per segment.
- 4A logic step keeps only segments whose absolute change exceeds your threshold; if none qualify, the run ends silently.
- 5An OpenAI action drafts a concise change summary explaining which segments moved and by how much.
- 6An output step posts the summary to a Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Market Research workflows
Enrich Inbound Accounts with BigQuery Firmographics and Score Fit
When a new account row lands in Airtable, joins it against BigQuery public business datasets to attach firmographic attributes.
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.
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.
Hiring Surge Detector with Slack Alert
Detects when a target account's open-role count jumps above its recent baseline and posts a ranked Slack alert to the GTM channel so reps can act on a company that is clearly…
Tech-Stack Shift Inference from Job Descriptions
Reads new job descriptions for target accounts, uses an LLM to extract named technologies and infer stack changes.
Weekly Hiring-Intel Briefing for GTM
An agent reviews the week's accumulated hiring signals across all target accounts, writes a narrative briefing that infers each account's likely initiatives.
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.