Koton
60% of customer conversations answered by AI, without losing the brand voice
One of Türkiye's largest fashion retailers moved from a traditional support model to an AI-first one across every messaging channel it sells on.
Published August 2025
Reported impact
- 60% of customer inquiries handled fully by AI agents
- 72% reduction in average response time
- 35% improvement in customer satisfaction within six months
- 40% less human workload on routine queries
- 28% lower customer service cost
- 22% more repeat purchases from personalised recommendations
Figures as published by GridStudio and the client at the time of the deployment.
The problem
Koton runs hundreds of stores and a fast-growing e-commerce business, which together generate millions of customer messages a month. Support was organised channel by channel, so the same question arrived three times in three inboxes, and seasonal campaign spikes meant either overstaffing or long waits.
What we built
- Consolidated WhatsApp, Instagram, Messenger and web chat into one AI-run inbox on MonoChat.
- Deployed specialised agents per job — returns, order tracking, style recommendation, loyalty — rather than one assistant that half-knows everything.
- Wired retrieval to Koton's own vector database so answers cite the real catalogue, real policy and real order state.
- Set up hybrid model routing across GPT-4o, Gemini 2.5 Pro, Claude 3.7 and Qwen Omni, choosing per request on speed, cost and accuracy.
- Enabled automatic language detection so Turkish, English and other customers are answered in their own language.
Where it landed
Support teams stopped triaging and started handling the queries that actually need judgement. Campaign and holiday spikes now absorb into the AI layer instead of the roster. Koton is targeting 80% AI-driven engagement.
This case study summarises our newsroom write-up. Read the original announcement.
