Personalization
7 post(s)
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4 CRM shifts in 2026: incrementality, zero-party data journeys, and loyalty that changes behaviour
A credited summary of Optimove’s take on four CRM marketing shifts: speaking in incremental lift, designing zero-party data capture as a journey, earning attention fast, and closing the gap between loyalty membership and loyalty behaviour.
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Predictive customer analytics: turning churn risk and propensity into usable lifecycle triggers
A credited summary of Braze’s explainer on predictive customer analytics, with a practical lens: which prediction types are useful in apps, and how to avoid ‘export a score, send a blast’ failure.
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WWDC26’s App Store creative refresh: why your listing is turning into a living campaign
M+C Saatchi Performance argues Apple’s WWDC26 App Store changes (Creative Assets, Asset Library, and more personalised recommendations) move teams from ‘set-and-forget’ metadata toward ongoing creative and behavioural optimisation.
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Braze Banners: the ‘always-on’ in-app surface that changes your CRM playbook
A credited summary of Braze’s Banners announcement, with practical guidance for app teams: where banners fit vs in-app messages and content cards, and what to watch so ‘more surfaces’ doesn’t become ‘more noise’.
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RevenueCat Paywall Rules let one paywall behave like many (show or hide components based on offers and variables)
RevenueCat introduced Paywall Rules: logic that can hide or override paywall components depending on the selected package’s offer type, a package identifier, or custom variables.
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AI retention is mostly ‘better timing + less spam’: a practical checklist for engagement teams
Braze lays out how AI can improve retention by predicting churn risk, personalizing onboarding, and optimizing send-time and frequency across channels. The useful takeaway: coordination and suppression rules matter as much as the model.
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A practical customer engagement strategy for 2026 (data, orchestration, AI, measurement)
A credited summary of Braze’s ‘customer engagement strategy’ guide, focusing on the four pillars (understanding, orchestration, AI personalization, and measurement) and what to operationalise in an app lifecycle program.