The Future of Traditional Shopping Driven by Customer Centric Approaches by Santiago Cabrera Naranjo
summary
Argues stores shift to points of experience and offers a six-step pipeline that turns transaction logs into prescriptive shelf decisions: product affinity analysis (collaborative filtering + graph models), path/cohort analysis, price/promo demand models (GAMs), clustering and loyalty scoring, then A/B tested layout changes. Adds camera-based metadata via person product detection tracking (CNN + tracking), a dashboard and CI-style analytic ops with model validation/versioning. Claims increased revenue and funding and projects to billion-query scale.
AI-written summary · about
chapters (16)
- 0:00Intro
- 2:35The customer is going to get to the center
- 5:50What should I do
- 6:54Product Affinity Analysis
- 9:37Path Analysis
- 10:44Demand Analysis
- 13:05Customer Loyalty
- 14:08Making Decisions
- 15:57What is Next
- 16:10Traditional BI
- 17:20Product Detection
- 20:32Data
- 21:11Analytics and digitization
- 24:41Analytics at scale
- 29:08Web perspective
- 32:32Takeaways
related talks
33mPanel: Industry Impact - Retail
19mThe Future Of Retail: A Decentralized Economy Of Data
25mRevolutionizing Customer Experience Through AI & Data
22mFrontiers of Machine Learning from the Lens of Retail
48mSmart Retail - Vision, Cognition and Intelligence
44mSituationalization: Using situational data to optimize online shops
43mConsumer Intelligence and the Age of Predictive Marketing Analytics
22mPowering the Next Generation of Products