A quarterly benchmark handed FanDuel a poor score on Login. Every login runs a location compliance check, and a gated path is supposed to feel heavy — so the number was widely read as the cost of doing business rather than a defect. It was not.
Correlating survey detractors against their own support records showed the check failing users at state lines, inside states where play was legal. This is the method that found it, and the deep dive that put an estimated $42M a year on a contact category that was a rounding error by ticket volume.
The loop
Usability, trust and loyalty scored against the industry every quarter, so a change in the number means something. Q1 sets the baseline; each round after it is a direct comparison.
Find where the detractors' scores actually come from rather than averaging them. Start at the top of the funnel, where the population is largest.
Split respondents by their support history — none, unrelated, relevant — and read the complaints sitting behind the low scores. Volume is a poor proxy for damage.
Product, friction and financial analytics on one side; the voices of the customer, the employee and the department on the other. Then price what it costs to do nothing.
The instrument
Status
It will carry the segmentation that surfaced the finding, the six-lens deep dive in full, the user story as delivered, and the path that took a compliance-gated defect through to state approval. In the meantime, the Red Eagle case study shows the same evidence discipline applied end to end to a generative AI build.
If you want the short version before then, ask me directly.
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Leaders partner with me when they need friction quantified, roadmaps sharpened, or customer sentiment explained in a way that drives action.