ooligo

Plum

talent-assessment personality-assessment · behavioral-fit · internal-mobility · succession-planning
AI-NATIVE API
Recruiting & TA
7.3 /10

What it is

Plum is the talent-assessment platform built around behavioral and personality fit — measuring candidate attributes (problem-solving style, work motivation, social style, adaptability) and matching them against role profiles. Different category from skills assessment (HackerRank, TestGorilla, Vervoe) — Plum measures who the candidate is rather than what they can do.

Why it shows up in Recruiting stacks

  • Behavioral fit signal. Some research suggests behavioral fit correlates with retention and on-the-job satisfaction more strongly than skills alone — particularly for roles where culture fit and team dynamics matter.
  • Reusable across the employee lifecycle. Plum profiles persist beyond hiring — useful for internal mobility, team composition, and succession planning. The same data that informed a hire informs a promotion 3 years later.
  • One assessment per candidate, applied to multiple roles. Candidates take the assessment once; results are matched against multiple role profiles. Reduces the assessment-fatigue that hurts candidate experience.

Pricing

  • Custom only. Per-employee or per-assessment pricing typical; effective entry point in the mid-five figures annually for mid-market.
  • Annual contracts standard; pilot programs available for evaluating before broader deployment.
  • Implementation typically 30-60 days.

Best for

  • Mid-market and enterprise companies where behavioral fit is a recognized hiring criterion
  • Organizations investing in internal mobility and succession planning beyond hiring
  • Customer-facing roles where personality and behavioral attributes meaningfully predict success

Watch-outs

  • Personality-assessment validity is contested in the research literature — meta-analyses show modest predictive power, far less than structured interviews or skills assessments
  • Behavioral assessment must be carefully designed to avoid disparate-impact bias against protected classes — particularly important for the AI-graded variants
  • AI bias-audit obligations under EU AI Act, NYC Local Law 144, Illinois AVDA apply
  • Should be one signal among several in hiring decisions, not the primary signal — over-weighting personality assessment produces worse outcomes than weighting it appropriately alongside skills and structured interview signal