Prompt
How do I set up a job promotion automation tool to track applicant volume by source?
Latest observation
To set up a job promotion automation tool to track applicant volume by source, you want two things:
- Consistent source tagging
- A reporting path that preserves the source through application submission
Here’s a practical setup:
1) Define your sources first
Create a clear source list you’ll use everywhere, for example:
- Indeed
- Google Jobs
- Company Careers Page
- Referral
- X/Twitter
- Email Campaign
- Agency/Recruiter
Keep the list standardized so your reporting doesn’t get messy.
2) Use unique tracking links for each source
For every promotion channel, create a separate job link with tracking parameters, such as:
utm_source=linkedinutm_source=indeedutm_source=referral
Example:
yourcareersite.com/jobs/123?utm_source=linkedin&utm_medium=organic_socialyourcareersite.com/jobs/123?utm_source=indeed&utm_medium=job_board
If your ATS supports it, map these UTMs directly into the applicant record.
3) Configure your promotion automation tool
In the tool, set up each job posting campaign with:
- Job ID / requisition ID
- Source/channel
- Destination URL with tracking parameters
- Posting schedule
- Budget if paid channels are involved
If the tool can auto-publish to multiple boards, ensure each board has its own tracking URL.
4) Make sure the ATS captures source data
The key is that when a candidate applies, the source data should flow into:
- ATS applicant record
- CRM or HRIS, if used
- Reporting dashboard
If the ATS doesn’t natively capture UTMs, use:
- Hidden form fields on the application form
- Redirect logic to preserve query parameters
- Cookies/local storage for source attribution
- Source lookup based on referrer + campaign link
5) Track candidate stage changes too
Applicant volume by source is most useful when paired with funnel data:
- Views
- Clicks
- Applications
- Screened
- Interviewed
- Hired
This lets you see not just where applicants came from, but which source produces the best quality candidates.
6) Build a dashboard
Create a dashboard with metrics like:
- Applicants by source
- Applicants per job by source
- Cost per applicant by source
- Conversion rate from click to apply
- Hire rate by source
- Time to fill by source
Tools commonly used:
- ATS reporting
- Power BI / Tableau / Looker
- Google Sheets + automation
- CRM analytics
7) Test attribution end-to-end
Before going live:
- Click each source link
- Submit a test application
- Verify the source appears correctly in the ATS/report
- Confirm no source gets overwritten by later steps
Test on mobile too, since many candidates apply there.
8) Handle edge cases
Decide how to classify:
- Direct traffic with no UTM
- Internal referrals
- Shared links
- Multiple touchpoints
A common rule:
- Use first-touch source for acquisition reporting
- Use last-touch source for campaign performance
- Store both if possible
9) Automate alerts and exports
Set automations such as:
- Daily applicant counts by source emailed to recruiters
- Weekly export to spreadsheet/BI tool
- Alerts when a source exceeds budget or underperforms
Example workflow
- Post job to LinkedIn with a unique UTM link.
- Candidate clicks link and applies.
- ATS captures
utm_source=linkedin. - Application is stored with source metadata.
- Dashboard updates applicant volume by source automatically.
If you want, I can also give you:
- a recommended data schema
- a no-code setup using Zapier/Make
- or an ATS-friendly implementation example.
Observation history
See 1 earlier observation
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Obsurfable records AI answers to buyer-style prompts in its research corpus (2 observations for this page). Metrics are distributions over observations, not a single static ranking.
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