MARKETING
Weekly SERP rank drift detector with BigQuery history and Slack alert
Every Monday, looks up your tracked keywords in Brave Search, compares each result's position to last week's snapshot stored in BigQuery.
How it runs
The automated pipeline, trigger to output.
- TriggerMonday morning schedule fires
- ActionRead tracked keywords + owned URLs from BigQueryBigQuery
- ActionQuery live SERP per keyword in Brave SearchBrave Search
- LogicJoin to last week's snapshot and compute position drift
- LogicFilter to movements past threshold or page-one exits
- ActionAppend new snapshot to BigQuery historyBigQuery
- OutputPost gainers-and-losers digest to SlackSlack
What it does
Tracks the Brave Search ranking position of your owned URLs across a list of target keywords, stores a dated snapshot in BigQuery, and computes week-over-week movement. It then summarizes which keywords climbed, which slipped, and which fell off page one entirely, delivering a ranked digest to a Slack channel so the SEO team starts the week knowing exactly where to focus.
When to use it
Use it when you own a content library and need a low-noise weekly pulse on organic visibility without paying for an enterprise rank tracker. It is ideal for teams that already warehouse marketing data in BigQuery and want SERP history alongside it for trend analysis.
How it works
- 1A Monday morning schedule fires the run.
- 2The keyword list is read from a BigQuery table of tracked terms and their expected owned URLs.
- 3For each keyword, Brave Search returns the live SERP and the workflow records the position of your matching URL.
- 4The new positions are joined against last week's snapshot to compute per-keyword drift.
- 5A filter flags only movements past a threshold (for example, +/- 3 positions or page-one exits).
- 6The fresh snapshot is appended to BigQuery for next week's comparison.
- 7A formatted gainers-and-losers digest is posted to Slack.
Set it up
What you configure once, before turning it on.
- 1Connect Brave SearchWeb, news, image, video search.
- 2Connect BigQueryDatasets, queries, schemas.
- 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.
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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.
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