Test-Ready or Not? Facebook Ads Creative Audit Scorecard
Score the evidence behind your next Meta creative decision. The result labels workflow readiness, not expected ad performance.
Creative decision readiness
60%
Ready to testSet a control, one variable and a recorded success measure.
- Decision evidence points
- 18
Assumptions
- Each of the six inputs is a self-assessed whole-number score from 0 to 5.
- All six inputs have equal weight in the readiness score.
- The readiness score is rounded to a whole percentage after dividing total points by 30.
- The score labels workflow readiness only. It does not predict CTR, CPA, ROAS, revenue, fatigue or test outcomes.
- A signal-quality score of 0 or 1 should pause creative interpretation until measurement is reviewed.
- Competitor evidence refers to visible public activity and must not be treated as proof of private commercial performance.
By Sachit Sharma, CEO & Founder · Updated 25 Sept 2026
In brief
A Facebook ads audit is most useful when it shows whether your team can make one defensible next creative test. Score six decision inputs, then fix the weakest one before treating a new idea as a priority.
Worked example at the defaults
With Creative coverage at 3 / 5, Signal quality at 3 / 5, Competitor evidence at 3 / 5, Customer feedback at 3 / 5, Learning capture at 3 / 5, Test queue at 3 / 5:
- Decision evidence points
- 18
- Creative decision readiness
- 60%
As configured in September 2026, the calculator adds six self-assessed inputs: creative coverage, signal quality, competitor evidence, customer feedback, learning capture and test queue. Decision evidence points equal the six inputs added together. Creative decision readiness equals (decision evidence points / 30) × 100.
The inputs are intentionally equal-weighted so the result stays explainable. The lowest input should determine the first corrective action. If signal quality is 0 or 1, review measurement before using the overall score to choose a creative priority. Continue with the Creative Test Capacity Planner to check whether the team can execute the queue, or use review mining for Meta ad angles when customer feedback is the gap.