MARKET RESEARCH
Correlate App Rank Spikes With Competitor Releases Into a Notion Brief
Each morning, queries BigQuery for overnight install-rank movements, cross-references Brave Search for competitor release events on the same dates.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily morning schedule
- ActionQuery yesterday's rank deltas from BigQueryBigQuery
- LogicKeep only apps past the movement threshold
- ActionSearch competitor release events for each moverBrave Search
- ActionDraft correlation narrativeOpenAI
- OutputPublish analyst brief as Notion pageNotion
What it does
Every morning this workflow pulls the previous day's app install-rank deltas from your BigQuery store-rank dataset, isolates the biggest movers, and tries to explain each one. For every notable jump or drop it searches the web for competitor release activity (new versions, feature launches, pricing changes) dated within the movement window, then assembles a correlated brief in Notion that pairs each rank shift with a plausible cause.
When to use it
Use it when you track a category leaderboard and need a daily, low-effort read on why ranks moved overnight — without an analyst manually joining store data to news. Best for competitive-intelligence and product-marketing teams watching a defined competitor set.
How it works
- 1A daily scheduled trigger fires before the workday starts.
- 2A BigQuery query returns yesterday's rank deltas per tracked app.
- 3A logic step filters to apps whose rank moved beyond a set threshold.
- 4For each mover, Brave Search looks for competitor release events on the relevant dates.
- 5An OpenAI step drafts a correlation narrative linking moves to events.
- 6The brief is published as a new Notion page in the research database.
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 NotionPages, databases, comments.
- 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.
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Run this workflow in your colony.
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