MARKET RESEARCH
Competitor Hiring-Spike Detector
Crawls a watchlist of competitor career pages daily, flags sudden spikes or drops in open roles by department, and posts a ranked strategy-shift digest to Slack.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionScrape competitor career pagesApify
- ActionRead prior baseline countsAirtable
- LogicCompute per-department deltas, filter spikes/drops
- ActionInfer strategic meaning per changeOpenAI
- ActionWrite new baseline countsAirtable
- OutputPost ranked strategy digestSlack
What it does
This workflow watches the public career pages of competitors you care about and turns raw job counts into a strategic signal. Every morning it scrapes each company's open roles, buckets them by department (engineering, sales, ops, etc.), and compares today's counts to a rolling baseline stored in Airtable. When a department's hiring jumps or collapses beyond a threshold, it summarizes the likely strategic meaning and pings your team.
When to use it
Run this when you track 5-30 named competitors and want an early-warning system for moves like a new product push (eng + design spike), a geographic expansion (regional ops roles), or a retrenchment (broad freeze). It replaces the manual habit of refreshing career pages.
How it works
- 1A daily schedule fires the run.
- 2Apify scrapes each competitor career page and returns structured role listings.
- 3The pipeline reads yesterday's baseline counts per department from Airtable.
- 4A logic step computes per-department deltas and filters for spikes or drops past your threshold.
- 5OpenAI drafts a one-line strategic inference for each flagged change.
- 6New counts are written back to Airtable as the next baseline, and a ranked digest is posted to Slack.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect AirtableBases, tables, views, automations.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 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
Weekly Materiality-Ranked Filing Digest by Email
Each Friday, aggregates the week's regulatory filings across the coverage universe, ranks them by materiality.
Earnings Keyword-Spike Alert into Linear
Scans new earnings-call transcripts for a set of strategic keywords you care about, and when a competitor's mention frequency spikes above its historical baseline.
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.
Discover Adjacent Segments from BigQuery and Rank Expansion Bets
On a schedule, scans BigQuery public industry data for fast-growing NAICS sectors adjacent to your core segments, scores them as expansion bets.
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.
Cross-Competitor Theme-Shift Analyst
An agent that gathers the latest earnings transcripts across all tracked competitors, compares this quarter's themes against the prior quarter stored in Coda.
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.