Recruitment analytics

See where hiring work is moving—and where it is waiting.

Review open roles, pipeline movement, recorded sources and outstanding follow-ups using the work already captured in your ATS—or describe the dashboard you need and review what TiLab builds.

At a glance

  • Open-role and pipeline visibility
  • Recorded source and stage movement
  • Candidate aging and outstanding next actions
  • Interview follow-up and offer progress
  • Dashboards you can describe in plain language

Growth plan

Operational visibility, not predictive certainty

Recruitment analytics, including dashboards built through chat, is part of the Growth plan, coming soon. It reports on the records captured in your workspace; it does not promise like-for-like external benchmarks, guaranteed attribution, or a forecast of who will succeed after hire.

From records to review

Make each metric answer an operating question.

A dashboard is useful when the team knows what action follows the number. Start with consistent records, review a small set of operational questions, and return to the candidate or role that needs attention.

  1. Record consistently

    Use clear stages, source labels, owners, and next actions so the underlying hiring records mean the same thing across the active team.

  2. Review the workload

    See open roles and the shape of their pipelines before deciding where recruiter time and hiring-manager attention are needed.

  3. Find waiting work

    Use stage aging, stuck candidates, and missing next actions to identify records that need a concrete follow-up rather than another report.

  4. Check the handoffs

    Review interview feedback status and offer progress to locate delays outside the recruiter’s immediate task list.

  5. Improve the records

    When a number looks wrong, return to its candidate, application, job, or source record and correct the operating data at the source.

Questions to answer

Analytics for the next recruiting conversation.

The product focuses on the questions a hiring team can act on during a regular pipeline review, using the records created by everyday ATS work.

  • What is active, and what is stuck?

    Review open roles and candidate distribution across the pipeline, then use aging, ownership, and next-action records to find applications that have stopped moving.

  • Dashboards built through chat

    Describe the dashboard you need in plain language and review the result. The AI proposes a validated configuration, not calculated figures; TiLab computes the numbers under the viewer’s own access.

  • Where did candidates come from?

    Review the source labels recorded on candidates and applications while keeping the limits of manual and incomplete attribution visible.

  • Which step needs follow-up?

    Check interview feedback and offer progress so overdue team input is connected back to the affected candidate and role.

Data quality first

A clean chart cannot rescue an inconsistent process.

Recruitment reporting inherits the meaning and gaps of the underlying workflow. Agree on stage definitions and update discipline before treating a trend as evidence for a staffing or process decision.

Make the data usable

Define the operational fields the team can maintain as part of its normal recruiting work.

  • Use stable stage meanings across active roles
  • Record a source only when the team actually knows it
  • Keep owners and next actions current
  • Close or update records when the process changes

Interpret with care

The dashboard reflects activity in TiLab; it does not establish causation, and any industry reference point shown beside a metric is orientation rather than a like-for-like comparison.

  • Missing updates can look like process delay
  • A source label does not prove the source caused the hire
  • Small pipelines can swing sharply between review periods
  • Operational metrics do not measure candidate quality by themselves

Common questions

Use the numbers without over-reading them.

Does TiLab provide industry benchmarks?

Only as orientation. The analytics overview shows a few cited, dated industry reference points (for example, average time-to-fill and offer acceptance) next to your own figures. Everything else reports on the jobs, candidates, stages, sources, interviews, and offers recorded in your workspace. Treat those reference points as context, not a like-for-like comparison.

Can we build a dashboard by describing it?

Yes. Create with chat sends your instructions, the recent conversation, and the dashboard definition to one external AI processing service, which proposes a validated configuration. It does not receive the underlying report data or computed results. TiLab calculates the figures separately under the viewer’s access permissions, and saved dashboards keep their chat and definition history. The security page sets out the full data handling.

Can source reporting prove which channel caused a hire?

Not by itself. TiLab can report the source labels the team records, but attribution depends on the quality and meaning of those records and may not capture every influence.

Is this a replacement for a general BI platform?

It is designed for operational recruiting review close to the ATS record. Teams needing broad financial modelling or cross-company analysis may still use a separate analytics environment.

Explore the workflow

Continue with a related guide.

Agree on stage and source definitions now, so the records are ready to review. Recruitment analytics comes with the Growth plan, coming soon; talk to the team about the reporting your hiring reviews need.

Contact the team

Measure the workflow your team can maintain.

See the Growth plan