Industry solutions
AI Adoption for E-commerce & Retail
Data is scattered across platforms and stores, so daily reports are pieced together by hand; negative reviews and complaints are spotted late; content production can't keep up with new launches.
Where the data lives
Platform back offices, ERP, customer service systems, DingTalk / WeCom
Recommended first use case
Store daily operations report + negative review alerts
High-frequency, clear rules, fixed output: it can be running in 2–4 weeks with quantified time savings, making the case for a full rollout.
Use cases by department
Start with the repetitive work that hurts most
| Department | Use case |
|---|---|
| Operations | Store daily reports (GMV, conversion rate, average order value), campaign reviews |
| Product design | Batch generation of main images, product detail pages and short videos |
| Merchandising | Competitor price monitoring, product selection analysis |
| Customer Service | Negative review classification, script library and FAQ updates |
Note: E-commerce back-office data collection uses only your own store accounts, with controlled frequency and in compliance with platform rules.
Cases
E-commerce & Retail rollout cases
让AI看懂风格-歌瑞尔AI工作流全链实战
「歌瑞尔AI工作流」作品帮助服装团队解决风格传递与开发链路协同难题，贯通企划设计和内容生产，将开款周期缩至15天。
O2O经营参谋-中智
面向O2O运营的AI数字员工。14个技能组合1个套件自动完成投流分析、看板与调价建议，人工确认后AI落价后台并自身优化完成loop。日耗时4h→0.5h，出错率20%→5%，ROI提升≥32%。
多平台电商经营数据打通与 AI 全量质检
某多平台电商企业
Reportdance FDE 驻场：打通多平台多店铺数据，AI 全量质检客服对话，售前询单转化率 +5%，客服人效 +6%。
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