Contact-Frequency Optimisation
Find the right cadence per customer, and cap by value not by guesswork.
What it does
Contact-Frequency Optimisation finds the right contact cadence for each customer: enough to keep them engaged, not so much they fatigue or opt out. It governs the 'how often' by setting frequency caps that flex by value, so your best customers are not silenced by a blanket rule and your fragile ones are not over-messaged into leaving. It is an analytical layer that reads send, engagement and opt-out history rather than a Braze AI toggle, so the caps are yours to set and defend.
What feeds it
- ·Send, engagement and opt-out events over time
- ·A value signal per customer, so caps can flex by worth
- ·Fatigue indicators such as falling open rates and rising unsubscribes
How to switch it on in Braze
- 1In Global settings, open Frequency Capping and define the caps per channel and time window.
- 2Segment the caps by value so higher-value customers can be contacted more, and fragile ones less.
- 3Mark essential or transactional messages as exempt so caps never block them.
- 4Set campaigns and Canvases to respect frequency capping.
- 5Review fatigue signals monthly and adjust the caps as the picture changes.
How Fuse builds for and utilises this
- ·We mine send, engagement and opt-out history in the warehouse to find where fatigue actually sets in, per segment.
- ·We set the value-tiered caps, so high-value customers keep their cadence and fragile ones get room to breathe.
- ·We sync the value tiers back to Braze as attributes so the caps can flex automatically.
- ·We tune on fatigue signals: falling opens and rising unsubscribes trigger a cap review, not a shrug.
What to measure
A capability that fires on people who would have converted anyway proves nothing. Hold a slice out, measure only the gap above them, and let the recipe earn its place on evidence.
- ·Opt-out and unsubscribe rates by value band, which should fall where caps tighten
- ·Engagement retained per customer as cadence changes, not just total sends
- ·Net incremental revenue against an uncapped control on /prove, so a quieter programme proves it earns more
Pairs with
On its own it is useful. Alongside these models it compounds.