LEAD GENERATION

Job-Posting Tool-Adoption Miner to HubSpot ABM Lists

Scrapes target-company career pages daily for job postings mentioning specific tools or skills.

CategoryLead Generation
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires the scan
  • ActionApify scrapes tracked companies' job postingsApify
  • LogicMatch posting text against tool-keyword dictionary; drop non-matches
  • ActionEnrich company and resolve owner in HubSpotHubSpotHubSpot
  • OutputAdd company to signal-tagged HubSpot ABM list with posting noteHubSpotHubSpot

What it does

This workflow continuously watches the public job postings of companies in your target market and flags the ones whose new roles imply they are adopting (or struggling with) a tool category you sell against. When a posting matches your keyword set — say "Snowflake", "dbt", or "reverse ETL" — the company is enriched and dropped into a HubSpot list keyed to that exact signal so your ABM sequence fires with the right angle.

When to use it

Use it when your best-fit accounts reveal their tech intent through hiring before they ever fill out a form. A posting for a "Senior dbt Analytics Engineer" tells you a company just committed budget to the modern data stack — a perfect moment to reach out. Run it as a standing daily scan across a defined account universe.

How it works

  1. 1A daily schedule fires the run.
  2. 2Apify scrapes job-board and career-page listings for your tracked companies.
  3. 3A logic step matches each posting against your tool-keyword dictionary and drops non-matches.
  4. 4HubSpot enriches the matched company record and resolves the owner.
  5. 5The company is added to the HubSpot ABM list named for the detected signal, with the posting title and URL written to a note.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ApifyActors, scrapers, datasets.
  2. 2
    Connect HubSpotCRM, deals, marketing, support.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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