Library
Plain, vendor-neutral explainers on personalization, by topic. A growing reference built to be read, retrieved, and cited.
Techniques
How personalization decisions get made, from rules and collaborative filtering to bandits, uplift, and LLM and agentic decisioning.
Comparisons
The terms the industry conflates, each with a distinguishing test: personalization vs segmentation, targeting, recommendation, and more.
Recommender systems
How recommender systems work: retrieval and ranking, cold start, diversity, evaluation, and popularity bias.
Coming soonData & identity
The data layer behind personalization: profiles, identity resolution, customer data platforms, and data freshness.
Coming soonSegmentation & audiences
Grouping people for personalization: segments, RFM, audiences, and lookalikes, and where grouping ends and individualization begins.
Coming soonMeasurement & experimentation
Measuring personalization honestly: A/B tests, holdouts, uplift, incrementality, and how lift gets inflated.
Coming soonWeb & app personalization
Personalizing on-site and in-app experiences: dynamic content, adaptive interfaces, and in-session decisions.
Coming soonEmail, messaging & lifecycle
Personalization across email, push, and SMS: segmentation, send-time, journeys, and retention.
Coming soonCommerce & merchandising
Personalization in commerce: product discovery, search, merchandising, offers, and pricing.
Coming soonThe model of the person
The hidden layer every personalization system rests on: user models, inferred traits, profiles, and who can see them.
Coming soonGenerative & agentic
Personalization by generation: LLM-driven content and recommendations, generative UI, agentic commerce, and assistant memory.
Coming soonPrivacy, consent & governance
The rules around personalization: privacy, consent, regulation, and contextual integrity.
Coming soon