AI-Native Readiness Assessment
A 10-minute self-scoring audit across data, measurement, org design, and tooling. The same rubric we run before greenlighting any client AI deployment.
10 questions. No email required.
Pick the option closest to your current reality. Scoring happens in your browser — nothing is sent anywhere until you explicitly ask us to follow up.
How unified is your customer record across systems?
Can one query return a complete picture of a single customer — purchases, sessions, emails, support tickets?
4 sections · 10–12 minutes
Pillar 1 — Data foundation
Is there a unified customer record and trustworthy event stream?
- Single durable customer ID across systems
- Warehouse with unified event schema
- Attribution stack modernized beyond last-click
Pillar 2 — Measurement architecture
Can you quantify AI contribution net of cost in a board review?
- Fast MMM running at least monthly
- Incrementality tests at least quarterly
- Cohort-level LTV reporting
Pillar 3 — Organizational design
Is the team shaped for agent-augmented operations or still for campaign execution?
- Senior-to-junior ratio recalibrated
- Operators hired who can write agent specs
- Observation layer in place for agent decisions
Pillar 4 — Tooling consolidation
Has the stack collapsed from point tools to decision-layer orchestration?
- Four-layer architecture implemented (data / decision / execution / observation)
- MarTech SaaS line trending down
- At least two agents running in production with clear goal functions
A specific diagnosis, not a generic report.
A readiness score out of 100 across four pillars, a prioritized list of the three highest-leverage gaps to close first, and a 90-day sequence calibrated to your current maturity.
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