AI: Redefining Customer Experience
summary
Retailer case studies show recommendation engines moving conversion from 2% to 12% on 1 million members by consolidating logs, loyalty and browsing data; appliances like washing machines and refrigerators require >20 touchpoints for decision, phones far fewer. Models vary by funnel stage: simple statistics for anonymous visitors, session-based recommenders on product pages, cart-level upsell models at checkout. Channels include Viber and email as highest-impact outputs. Key limits: poor data, weak offers or bad placement break results, and consent/GDPR gating filters who the models use.
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chapters (11)
- 0:00AI in customer experience
- 1:07Overwhelming customer data
- 2:13Hyper-personalization importance
- 3:38AI recommenders drive personalization
- 6:51Customer behavior analysis
- 10:25AI in customer journey stages
- 12:56AI as business tool
- 16:56AI in Serbian retail success
- 19:47Q&A: Data models
- 22:17Q&A: GDPR and privacy
- 23:52Closing remarks
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