The feedback problem in Indian retail
Most Indian retail brands run NPS surveys quarterly, dashboard them monthly, and act on them never. GPT AI for Closed-Loop Customer Experience Management closes that gap — turning unstructured customer feedback into named, prioritised, routed actions that hit a store manager's phone within 24 hours.
This page walks through the model, the metrics and how Fundle.ai's Feedback Intelligence Agent runs this in production across 912+ stores.
The 5-step framework
- Capture: WhatsApp + SMS + in-app surveys with 30-40% response rates (vs email 4%)
- Listen: GPT-4 classifies every open-text response into 50+ taxonomy buckets in 8 seconds
- Detect: emerging-issue detection flags issues 10+ days before they hit social media
- Route: complaint goes to the right store manager, BU head and CX team automatically
- Recover: detractor win-back orchestrated over WhatsApp; closed-loop NPS measured weekly
How Fundle delivers this
Fundle's Feedback Intelligence Agent combines a conversational survey engine (GPT-4 powered, multilingual including Hindi/Tamil/Telugu/Kannada), real-time sentiment scoring, automatic theme extraction and a routed-action layer that integrates with WhatsApp Business API. Detractors get a personal recovery offer in under 60 minutes — automatically.
India benchmarks
- NPS survey response rate over WhatsApp: 30-40% vs email 4-8%
- AI theme classification accuracy: 91-94% across English + Indic languages
- Detractor recovery rate with automated win-back: 42% (vs 11% manual)
- Time from survey response → store-manager action: under 24 hours
Related resources
Looking for more? Open the Industries menu to browse playbooks by sector, brand or mall.