Eight questions, four dimensions: the customer-data join, prioritization evidence, delivery context, and outcome verification. Honest answers in, a band and a next move out.
The join
1. Can you see what an account pays and what it asked for on one screen?
The join
2. When feedback arrives, does it carry the account behind it automatically?
Prioritization evidence
3. How is the backlog ranked?
Prioritization evidence
4. How long does 'which paying customers asked for this, and what do they pay' take to answer?
Delivery context
5. When work enters the tracker, does the customer context travel with it?
Delivery context
6. Can engineering see who a task is for without asking a PM?
Outcome verification
7. After a feature ships, do you check whether the requesting accounts adopted it?
Outcome verification
8. Can you name a shipped feature that moved retention or expansion, with the data?
Maturity score
0/24
Ad hoc
The join0/6
Prioritization evidence0/6
Delivery context0/6
Outcome verification0/6
Decisions run on memory and volume. The quickest win is the first join: put feedback and the paying account on one record, and the rest of the ladder opens up.
Decisions run on memory and volume. The quickest win is the first join: put feedback and the paying account on one record, and the rest of the ladder opens up.
Connected in places
Some joins exist but people maintain them. Ranking still leans on estimated inputs; make request counts and revenue computed instead of typed and the scores start defending themselves.
Evidence-led
Prioritization runs on real signals. The open loop is usually post-ship: work leaves the record, ships, and nobody verifies the outcome against the accounts that asked.
Closed loop
Feedback, revenue, work, and outcomes are joined, and shipped features report back. Maturity work now is keeping the loop cheap enough that nobody routes around it.
How reliably a team's product decisions run on joined evidence instead of memory. Low maturity looks like feedback in one tool, revenue in another, and prioritization by whoever argued best. High maturity means every request carries its account and revenue, work carries its customer context through delivery, and shipped features are verified against the accounts that asked.
How does this assessment score maturity?
Eight questions across four dimensions: the customer-data join, prioritization evidence, delivery context, and outcome verification. Each answer scores 0 to 3 for a 0-24 total across four bands, from ad hoc to closed loop. The questions are the methodology; there is no hidden weighting, and the per-dimension read matters more than the total.
What should a team fix first?
The lowest-scoring dimension, and almost always the join before the process. Frameworks and rituals layered onto disconnected data produce confident-looking scores with estimated inputs. Once feedback, revenue, and work share a record, the same rituals start running on evidence, and the later dimensions (delivery context, outcome verification) become cheap instead of heroic.