Experimentation
9 post(s)
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Braze: The most practical way to adopt AI in CRM is to sequence it by risk, not hype
Braze lays out eight concrete AI use cases across the lifecycle, from behavioural segmentation and send-time optimisation to churn prediction and agentic execution. The useful framing is the adoption order: start with low-risk wins (content variants, timing), then move into data-dependent work (segmentation, prediction), and only then let AI make decisions or take actions.
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Inference cost vs UX: why cheaper AI models can quietly reduce engagement (Amplitude)
Amplitude ran a real production test swapping an agent’s model to cut cost. Conversion held, but latency doubled and people asked fewer questions. The point: your success metric needs to include ‘time-to-answer’ and ‘messages per session’, not just dollars and a top-line conversion proxy.
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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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RevenueCat: free trial length is a product decision, not a 7-day default
RevenueCat argues trial length should follow time-to-value and confidence-building, not a one-size-fits-all 7-day habit, and shares data patterns by category and price point.
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The Integrated Growth Manifesto: why the old playbook is dead
Phiture’s argument for integrated growth: break channel silos, use first-party data as the connective tissue, and use AI to increase experimentation velocity across the full funnel.
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RevenueCat: how to run a custom paywall UI alongside RevenueCat Paywalls (without splitting purchase logic)
RevenueCat explains a hybrid approach: keep entitlements + purchases centralized in the SDK, while swapping between a fully custom paywall and RevenueCat Paywalls using placements and offering metadata.
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Seasonality is a storefront advantage: treat major moments like a listing refresh
Gummicube uses the Super Bowl as a case study: when intent spikes, apps win by updating metadata and creatives to match the moment, then validating via structured A/B tests.
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Phiture updates the ASO Stack for 2026: variants, vitals, and faster testing
Summary of Phiture’s ASO Stack Redux 2026 update: more visibility levers (CPP/CSL, promoted IAPs, tags), app vitals as a visibility gate, and experimentation velocity as the compounding edge.
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Choosing a push platform in 2026: treat delivery, consent, and experimentation as one system
SashiDo’s 2026 guide is essentially a retention-team buyer checklist: reliable delivery and token hygiene, deep segmentation, journey automation with caps, and experimentation/holdouts that let you prove impact without drowning users in notifications.