cx-consumer-outcome-evidencelisted

# Evidencing customer outcomes Outcomes-based regulation asks a question that ordinary CX reporting cannot answer. Response time, CSAT and QA scores describe **activity and satisfaction**. The question is whether customers ended up in the right place — and specifically whether any group of them is systematically ending up in the wrong one. The gap shows up sharply the first time someone asks "how do you know customers aren't being harmed?" and the answer is a dashboard of averages. ## Averages hide the thing being asked about The question is about distribution and about groups, not about the mean. An operation with a 4.5 CSAT and a 92% QA score can be failing a specific group badly: customers in one language, on one channel, with one product, or with a characteristic that makes them less able to advocate for themselves. **The average is evidence that most customers are fine, which was not the question.** So the analytical shape is: **pick outcomes, define them observably, then look for groups where they are worse — and specifically for groups whose worse outcome you could not defend.** ## Define outcomes observably An outcome has to be something you can see in data, not a sentiment. For support, the defensible ones: - **Did the customer get what they were entitled to?** Redress paid where owed, the entitlement granted, the cancellation completed. - **Did they get it without disproportionate effort?** Contacts to resolution, channel switches, time from first conta