Retail AI Solution

For chain retail, e-commerce, FMCG, apparel, beauty: natural-language sales analytics + omnichannel AI customer service + campaign-level AI Agents.

The four bottlenecks in retail data ops

SKU × channel × time analytics take forever

Category managers wait days for a single sell-through report; by the time it's ready, the promo window is over.

Member data trapped in the CRM

RFM, cohort retention, and lifecycle scoring require SQL. Marketing can't self-serve.

Cross-channel customer service is exhausting

Taobao, JD, Douyin, WeChat MP, private-domain groups — each channel needs its own agent, service quality drifts.

Promo ROI is unknowable in real time

By the time attribution reports come out, next campaign is already live.

Recommended product stack

Data Analytics

Yitu · NL2SQL Analytics Platform

Ask sales, inventory, membership, or promotion questions in plain Chinese. Semantic layer defines SKU / channel / member RFM once — everyone uses the same numbers.

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Customer Service

Yitu Kefu · Intelligent Customer Service

One inbox for Taobao, JD, Douyin, WeChat MP, and private-domain groups. AI answers standard product questions, humans handle high-value orders and complaints.

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AI Agent

Yituclaw · AI Agent Platform

Deploy campaign-copy generation, review sentiment analysis, and product description agents at scale — one Agent, thousands of SKUs.

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Typical scenarios

> Chain retail: store performance ranking, category-level sell-through
> Brand e-commerce: campaign ROI attribution, coupon effect analysis
> FMCG: dealer inventory monitoring, distribution health check
> Beauty & personal care: repurchase prediction, member lifecycle scoring
> Apparel: size-run analysis, seasonal markdown optimization
> Convenience & grocery: SKU affinity, dynamic replenishment

FAQ

Want a retail-focused demo with your own SKU data?

Book a working session — we'll wire up one data source in 30 minutes.

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