GenAI mapped every customer comment to a service SLA, and showed that being on time was not the same as being good enough.
Based on the 15-comment analysis shown below. NPS figures are indicative; validated metrics available on request.
Customer feedback arrived as free text. The SLA guidelines lived in a separate document. Nobody could say which promises were being kept and which were hurting NPS.
Verbatims mixed delivery, packaging, app and pricing in one paragraph. Manual tagging was slow and inconsistent.
Deliveries landed inside 2–5 days, yet customers compared the retailer with faster platforms and felt let down.
Logistics, app, catalogue, support, returns and packaging each owned part of the experience, and each saw only its own slice.
Zero-tolerance SLAs, such as wrong items or tampered packaging, were breached without anyone tracking them against the guideline.
Two inputs, customer comments and SLA guidelines, turned into one decision-ready report.
Select a step to see what happened.
The customer's voice and the company's promise, side by side.
Deliverable: Comment set and a single SLA guideline sheet.
Each comment gets the same structured treatment.
Deliverable: Prompt frame and output template.
Claude read every comment against the guidelines and produced the report.
Deliverable: Feedback vs SLA HTML report: Summary, Comment Analysis, SLA Scorecard, Recommendations.
The report became the agenda for a cross-functional CX review.
Deliverable: Action log with owners and dates.
The same frame now runs on the full NPS comment stream.
Deliverable: Monthly Feedback vs SLA pack.
Each row is a customer comment; each column an SLA dimension. Hover or click a cell to see the observation and the guideline it tests. Toggle the lens to see how much of the problem is a breach and how much is perception.
Screens from the actual analysis: two inputs and the four-tab GenAI report. Click an image to enlarge.
Each recommendation is linked to the comments it would fix. Switch fixes on to see how sentiment, and an indicative NPS, would move.
The 15 comments as promoters, passives and detractors
Comments per SLA dimension, by status
NPS classification of the 15 comments is indicative, inferred from comment sentiment. Validated metrics available on request.
13 of 15 deliveries were on time, yet 8 customers still felt short-changed. Competitors set the expectation, not the SLA document.
Zero-tolerance SLAs need prevention: scan-verified dispatch and packaging checks at handoff, not better apologies.
One fully satisfied customer showed the standard: fast, secure, as described. Design for more of those on purpose.