MARKET RESEARCH
Post a Weekly Top-Movers App Digest to Discord
Once a week, aggregates seven days of BigQuery install-rank data into the biggest gainers and losers in your category, summarizes the storylines.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule
- ActionAggregate 7-day rank changes in BigQueryBigQuery
- LogicSelect top gainers and losers
- ActionGather context for standout moversBrave Search
- ActionWrite weekly narrative digestOpenAI
- OutputPost digest to Discord channelDiscord
What it does
This workflow produces a weekly category recap. It rolls up seven days of install-rank data from BigQuery, ranks the largest net gainers and losers across your tracked set, and pulls a short web-context lookup for the top storylines. An OpenAI step turns the numbers into a tight narrative — who climbed, who slipped, and the likely reasons — then posts the digest to Discord so the whole team starts the week aligned on the leaderboard.
When to use it
Use it when daily alerts are too noisy but you still want a regular pulse on category dynamics. Good for cross-functional teams who follow the space casually and want one well-shaped weekly read.
How it works
- 1A weekly scheduled trigger fires at the start of the week.
- 2A BigQuery query aggregates seven-day net rank changes per app.
- 3A logic step selects the top gainers and losers.
- 4Brave Search gathers context for the standout movers.
- 5An OpenAI step writes the weekly narrative digest.
- 6The digest is posted to the team's Discord channel.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect Brave SearchWeb, news, image, video search.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect DiscordCommunity channels + voice + bots.
- 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
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.