Why someone is reading job ads all day
For a recruitment agency, a new vacancy at a target company is a lead. For a software vendor, a company hiring for a certain role is a hint it may need your product. For a training firm, a wave of similar vacancies shows demand. So someone checks job boards and company career pages, copies the interesting ones into a spreadsheet and passes them on.
It is endless, repetitive and patchy. The same role appears on several boards, some companies post only on their own careers page, and the most useful ones are seen after a competitor has already called.
Why postings are hard to follow
Job data is spread across large boards, niche boards, applicant tracking systems and company websites. Titles vary wildly for the same role. Many postings are reposted by agencies with the employer's name removed.
Access differs too. Some boards and ATS platforms publish public job feeds by design, since they want postings seen. Others restrict automated collection in their terms.
| Source | Typical route |
|---|---|
| Company careers pages on common ATS platforms | Public job feeds or JSON the ATS publishes |
| Job boards with partner programmes | Official API or feed |
| Boards whose terms forbid scraping | Manual alerts or commercial data licence |
| Government and public sector job sites | Often open data feeds |
What manual tracking costs
- Signals seen late or missed completely
- Duplicate entries from the same role on several sites
- Time spent reading irrelevant postings
- No trend view of who is hiring for what
For sales teams the timing matters most. A company is most open to a conversation while the need is fresh.
For recruitment firms there is an extra cost in duplicated effort. Two consultants spot the same vacancy on different boards and both approach the client, which looks disorganised. Without a shared, deduplicated record, the agency has no easy way to see who is already working which opportunity.
And because the spreadsheet only holds what someone happened to copy, it is useless for spotting trends, such as a sector that has started hiring heavily in one region.
How we build a job postings feed
- We agree the target: companies, sectors, roles, locations and what action a posting should trigger.
- We map sources and pick routes: ATS job feeds for company career pages, official board APIs and open data first, polite collection of public pages only where terms allow.
- Postings are normalised into one structure: employer, title, location, salary where given, date, link, source.
- Titles are classified into a consistent role taxonomy using rules plus an AI model, so varied titles for the same job are grouped.
- Duplicates across boards are merged, and agency reposts are linked to the employer where it can be inferred, with a confidence flag.
- Relevant postings go into your CRM, such as HubSpot, Salesforce or Bullhorn, as signals on the company record, or into a daily digest.
- Trend reports show hiring volume by company, role and region over time.
We avoid collecting personal data such as recruiter names beyond what is needed, and we do not collect candidate data at all.
Signals delivered instead of searched for
The team receives relevant postings as they appear, grouped and deduplicated, already linked to the company in the CRM. Reps or consultants act on signals rather than hunting for them, and management can see which sectors or regions are hiring more or less.
Closed postings are tracked too. When a vacancy disappears it is marked as filled or withdrawn, which tells a recruiter whether to follow up and tells a sales team whether the moment has passed.
The history becomes useful for planning as well. A staffing firm can see which clients hire in cycles and prepare before the next wave, and a sales team can prioritise accounts that are growing their teams in the areas your product supports.
Check your situation
- Someone checks job boards or careers pages by hand
- New vacancies are a sales or recruitment signal for you
- You often see the same role several times
- Competitors reach hiring companies before you