Customer Feedback Intelligence — example input brief

Purpose: connect original feedback, topic evidence, owned remediation and a documented resolution.
This is a tutorial input brief, not a complete data export or production dataset.
Project: https://1369184940e1496c988c5d3db9663208.prod.enterapp.pro/login

Input tables: Feedback; Stores; Products; Topics; Topic-Feedback Links; Tasks; Resolution Records; Users.
Fields: feedback_id, original_text, channel, timestamp, rating, store_id, product_id, sentiment, urgency, topic_id, handling_status; task_id, linked_topic_id, owner, due_date, status, resolution_note.
Rules: retain original text; distinguish AI classification from confirmed facts; allow corrections; deduplicate without deleting evidence; respect date/store filters and unknown product links.
Workflow: identify topic -> read original evidence -> assign and follow remediation -> record resolution and verify closure.
Roles: Store Ops handles scoped feedback/tasks; Managers review; specialist teams own logistics/product issues.

Observed example, 2026-09-11: Marcus Bell (Store Ops), SoHo Flagship, Customer Service topic. Feedback FB-202607-1332 describes inattentive cashier service and leaving without purchase; feedback marked Resolved. Topic links to task TK-202609-0028, service-standards retraining, marked Remediated but overdue and not Closed. Closing requires a resolution note. Do not equate feedback resolution with task closure or invent training outcomes.
If additional demo data is needed, generate clearly labelled synthetic records with consistent IDs and dates.