The repurchase and complaint data all exists, but 'raise repurchase, cut complaints' still lives in ratings, meetings, and improvement suggestions — nobody ultimately owns the outcome.
Take a workflow that grades products by complaints and repurchase and optimizes or delists them one by one, and hand it to an Agent for three layers of scrutiny: first diagnose the gaps in the workflow itself, then audit the execution board's formulas and definitions column by column, and finally deliver a RACI matrix and a project battle-board design — then build and deploy the board on the spot.
Reads plan docs and Excel, diagnoses workflow gaps, checks formulas column by column, outputs the RACI and board design, and builds and deploys the static board directly.
We're turning 'experience improvement' from an initiative into an operating mechanism. Rules:
The boss speech-to-texts the current SOP straight into the channel, plan archive attached.
The Agent returns seven improvements: hard thresholds for grading, root-cause splits for complaints, leading indicators, business judgment for sleeper hits, stop-loss gates, tiered cadence, RACI.
The execution-board Excel gets checked column by column: formulas referencing the wrong column, inconsistent definitions, external-link formulas unverifiable after export, nonstandard coding — with a prioritized fix list.
Delivers the RACI matrix (13 work modules × 10 departments) plus a six-block battle-board design, and recommends keeping exactly one overall owner.
The boss says 'just design and build it,' and the Agent develops the static visual board and deploys it live on the spot.
High-sales high-complaint products, overdue items, and products still advertising while complaints worsen.
Product tiers and resource allocation: which to amplify, which to fix, which to delist.
Whether complaint root causes recur, how often optimizations succeed, and whether the mechanism itself works.
Wire the static board to live data sources, freezing a monthly data snapshot for traceability.
Automate complaint root-cause tagging, extracting cause labels from support records.
Guard the results section against fake improvement: delisting or cutting ads makes complaint rates look better while brand-wide repurchase never moves.