Personalisation Gap

The personalisation gap is the distance between customers' expectation of relevant individualised communication and the generic, segment-based marketing most companies still deliver.

Key points

• Hightouch frames the gap with a customer-expectation mismatch: customers want communications that matter, but many still receive generic marketing despite companies having more customer data and marketing tools than ever ^[src-023].
• The article argues the problem is technological rather than simply operational. Segment and rule-based tools cannot make contextual decisions for each individual at scale ^[src-023].
• Surface-level personalisation includes cart-abandonment triggers, previous-purchase segments, personalisation tokens, and dynamic content. True personalisation requires adapting to complex individual behaviour, intent, urgency, and context ^[src-023].
• The practical failure mode is "segment of one" theatre: marketers keep creating smaller segments and more journey branches, but ROI eventually flattens because the system still relies on predefined rules rather than learning ^[src-023].
• The proposed bridge is AI Decisioning, where agents learn which actions across content, timing, channel, and frequency drive the desired outcome for each customer ^[src-023].
• Hightouch's final article recasts the gap as approximation versus precision: journeys and increasingly granular segments still make group-level assumptions, while contextual bandits learn and respond to individual customer patterns ^[src-026].
• Braze describes the same bottleneck from a lifecycle-marketing angle: even with rich first-party data and a large bank of content, the hard part is deciding which message, offer, channel, timing, and frequency should be used for each customer ^[src-152].
• The Braze whitepaper is a useful counterweight to generic generative-AI marketing claims: GenAI can help create variants, but it does not by itself solve the decisioning problem of who should receive which action ^[src-152].

Related entities

• Hightouch — source publisher and AI Decisioning vendor

Related concepts

• AI Decisioning
• Treatment Personalisation
• Contextual Bandits
• Multi Armed Bandits
• Customer Feature Matrix
• Community Of Bandits

Source references

• ^[src-023] Hightouch — "Under the hood of AI Decisioning, part one: Overcoming the personalization gap"
• ^[src-026] Hightouch — "Under the hood of AI Decisioning, part four: Contextual bandits"
• ^[src-152] George Khachatryan, Nathaniel Rounds, Victor Kostyuk / Braze – "A community of bandits" (source page: "From multivariate testing to AI decisioning", 2025-09-30)