MARKET RESEARCH
Hiring Velocity Spike Detector
Daily it counts each competitor's open roles, computes rolling hiring velocity per function, and raises a flag in Linear when any function's posting rate spikes past its baseline.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule
- ActionScrape open-role countsApify
- ActionStore counts, fetch trailing baselineSnowflake
- LogicFlag functions exceeding spike threshold
- OutputOpen investigation issueLinear
What it does
Each day it captures the count of open roles per competitor and per function, computes a rolling average velocity, and detects statistical spikes. When a function's hiring rate jumps well above its own baseline, it opens a tracked Linear issue so an analyst investigates the cause.
When to use it
Use this when you want quantitative early warning rather than per-posting noise. A sudden surge in a rival's recruiting headcount often precedes a hiring sprint; a spike in support roles can foreshadow a big customer win. The baseline math surfaces only changes that matter.
How it works
- 1A daily schedule fires the run.
- 2Apify scrapes current open-role counts for each tracked competitor.
- 3Snowflake stores the daily counts and returns the trailing baseline per competitor and function.
- 4A logic step compares today against baseline and flags functions exceeding the spike threshold.
- 5For each flagged spike, a Linear issue is created with the function, magnitude, and trend context for follow-up.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect SnowflakeWarehouses, queries, shares.
- 3Connect LinearIssues, projects, cycles, triage.
- 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 this workflow in your colony.
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