Braze × RTL+
Braze x RTL+, AI-personalized messages lift watch engagement 21%
~21% uplift in watch engagement vs. control group
Generic segmented messaging to individually personalized communication at scale
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Why it works
The case study earns its headline numbers by anchoring results against a no-message control group, which gives the 21% watch engagement uplift genuine credibility. The mechanism is explained in enough operational detail (20 data points, signal hierarchy, Liquid templating assembly, fallback logic) that a reader can map the approach. This is close to a New Capability story because RTL+ explicitly states that infinite individual variants within a single campaign 'was never possible before now,' but the framing leads with a number going up, so Breakthrough takes primary.
Steal this
Pairing a no-message holdout control group with the reported uplift metric, rather than a before/after comparison, makes the causal claim much cleaner and harder to dismiss.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are Braze's published work; we link to the source and lead with our analysis.