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 for specific cloud campaigns they owned: pipeline sourced, MQL to SQL conversion, ABM plays against named accounts, webinar or AWS/Azure marketplace co-sell programmes with dollar figures.
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 campaigns with sourced pipeline and CAC numbers, including the cloud partner co-marketing motion and what it returned.
02
Evaluation factor
Audience and segmentation
25% weight
Probe how they segment buying committees: CTO versus platform engineer versus procurement, cloud maturity stages, ICP definitions built from firmographic and intent data in 6sense or Bombora.
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
Describes distinct messaging for technical evaluators and economic buyers, backed by intent data and real win/loss interviews.
03
Evaluation factor
Measurement and testing
30% weight
Test their measurement stack: multi-touch attribution in HubSpot or Marketo, Salesforce campaign influence, A/B tests on landing pages, and how they handle long enterprise sales cycles.
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 attribution model choices and their limits, cites tests where the losing variant changed the roadmap.
04
Evaluation factor
Working with the business
15% weight
Check how they work with cloud sales teams and product marketing: SDR handoff SLAs, sales enablement decks, competitive battlecards against AWS, GCP, or Snowflake.
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
Shows enablement assets sellers actually used, and describes resolving friction over lead quality with concrete SLA changes.
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