Measure whether you appear, how you are evaluated, whether the facts are right, and which parts of your story survive.

Start with the decision, not the dashboard

The first question in an AI measurement program should be what the organization needs to decide. A reputation team may care about Error Rate after a crisis. A product marketer may care about recommendation criteria. A destination may need to understand how portrayal changes by traveler audience and location.

Those goals determine the questions, models, audiences, locations, and evaluation dimensions worth monitoring. Without that foundation, a dashboard can produce many metrics and very little clarity.

Measure AI portrayal with the SEEN Framework

Share of Answers tells you whether AI includes you. Evaluation, Error Rate, and Narrative tell you what it says when it does. Together, the SEEN Framework defines your AI portrayal; the combined result is your portrayal profile.

  • Share of Answers: How often do you appear across the unbranded prompts that matter, and under which conditions?
  • Evaluation: How does AI evaluate and recommend you on customer-defined dimensions?
  • Error Rate: How often do AI claims conflict with the facts your organization supplied?
  • Narrative: Does the answer carry the messages your team chose to track?

Vary the context deliberately

AI portrayal can change by model, audience, geography, language, time, and question wording. Treat those as experimental variables rather than mixing them into one global score.

Change one meaningful dimension at a time when possible. The same prompt, audience, and model run from different simulated locations can reveal geographic effects without confusing them with rewritten language.

Preserve the evidence

Every score should lead back to the exact answer, prompt context, cited sources, and evaluation logic. This lets teams verify a finding, explain it to stakeholders, and decide whether the right response belongs in content, communications, technical work, or monitoring design.

Measurement becomes useful when it supports a defensible action, not when it produces the largest possible number of charts.