Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Campaigns that performed
30% weight
Ask which ads, packs or shelf tests they ran biometric studies on, and what changed: recut edits, pack redesigns, or in-market lift after their recommendation.
Evidence to listen for
Names campaigns or programmes they ran, with the metric they moved and the baseline it moved from
Distinguishes their own work from the team's or the agency's
Knows the audience and the offer, not just the channel
Can describe a campaign that failed and why
Five-point scoring guide
1
Poor
No numbers; describes activity rather than results.
2
Needs Improvement
Vanity metrics only; attribution to their own work is unclear.
3
Satisfactory
Real campaigns with some numbers; baselines often missing.
4
Very Good
Named campaigns with metric, baseline, and clear personal ownership.
5
Excellent
Names specific studies (ad copy tests, pack shelf sets) where their read altered the creative and in-market results followed.
02
Evaluation factor
Audience and segmentation
25% weight
Probe how they define and recruit study panels: sample sizes for EEG or eye-tracking cells, screening criteria, category buyers versus rejecters, and handling of segment-level differences.
Evidence to listen for
Describes real customer segments and what differs between them, not demographic guesses
Has built lifecycle stages, journeys, or nurture logic that reflect actual behaviour
Knows where the audience data comes from and its limits
Writes for the segment rather than for everyone
Five-point scoring guide
1
Poor
One message for everyone; no segmentation thinking.
2
Needs Improvement
Segments by demographics only; no behavioural insight.
3
Satisfactory
Workable segmentation; lifecycle logic is basic.
4
Very Good
Behaviour-driven segmentation and lifecycle design with evidence behind it.
5
Excellent
Sets panel composition deliberately, defends cell sizes for biometric power, and reports segment splits rather than one pooled average.
03
Evaluation factor
Measurement and testing
30% weight
Test command of the instruments: EEG or fNIRS metrics, GSR, facial coding (FACS or Affectiva), webcam eye-tracking, implicit reaction time tests, and triangulation with survey and sales data.
Evidence to listen for
Tests deliberately rather than changing everything at once
Understands attribution limits and does not overclaim
Knows what sample size and duration a test needed
Can name a test whose result contradicted what they expected
Five-point scoring guide
1
Poor
No testing; claims credit for correlation.
2
Needs Improvement
Runs tests but reads them badly; overclaims attribution.
3
Satisfactory
Tests sensibly; rigour drops under deadline pressure.
4
Very Good
Disciplined testing with honest attribution and a result that surprised them.
5
Excellent
Explains signal artefacts, baseline correction and time-locking to stimulus, and refuses to over-read a single biometric channel.
04
Evaluation factor
Working with the business
15% weight
Check how they brief creatives and brand managers who distrust neuroscience: second-by-second attention curves, clear do-this-not-that guidance, and honest caveats on predictive validity.
Evidence to listen for
Works with sales, product, or operations rather than throwing campaigns over a wall
Briefs designers and writers well enough to get usable work
Manages agencies or freelancers to a standard
Reports results to leadership without spin
Five-point scoring guide
1
Poor
Works in isolation; reports only flattering numbers.
2
Needs Improvement
Limited coordination; briefs are thin.
3
Satisfactory
Coordinates adequately; reporting is honest if basic.
4
Very Good
Strong partner to sales and product; briefs and reports clearly.
5
Excellent
Translates attention and arousal traces into concrete edit decisions, flags weak evidence openly, and gets creative teams acting on findings.
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