Braze Frequency Capping: Complete Guide
Quick Summary:
Frequency capping limits how many messages a user receives within a defined window, protecting against message fatigue and the deliverability damage that comes from users consistently ignoring or opting out of over-frequent messaging.
What Is Frequency Capping?
Frequency capping sets a maximum number of messages a single user can receive within a defined time window, whether within one specific campaign or globally across your entire messaging program. This exists to protect against a genuinely real risk: message fatigue that leads to opt-outs, and the sender reputation damage that follows from users consistently ignoring or actively unsubscribing from over-frequent communication. Getting this right is a genuine balancing act -- too restrictive, and valuable messages never reach their intended audience; too permissive, and the cumulative volume erodes the very engagement it's meant to protect.
⚠️ Frequency Capping Is a Deliverability Issue, Not Just a UX One
It's easy to think of frequency capping purely as a courtesy to users, but the deliverability consequence is genuinely significant -- mailbox providers and app platforms track engagement signals, and consistently over-messaged, unengaged users hurt your sender reputation in ways that affect inbox placement and delivery success for your entire messaging program, not just the specific over-frequent campaign.
Illustrative Relationship Between Capping and Unsubscribes
Illustrative pattern reflecting general industry experience -- actual unsubscribe impact varies significantly by audience, industry, and message quality.
Types of Frequency Capping
| Cap Type | Scope |
|---|---|
| Per-campaign | Limits repetition within a single campaign or Canvas |
| Global/cross-campaign | Limits total messages across your entire messaging program |
| Per-channel | Limits frequency within a specific channel (e.g. push only) |
| Combined/cross-channel | Limits total messages across all channels combined |
Coordinating Frequency Across Teams
Frequency capping's real complexity often isn't technical -- it's organizational. In any company running multiple concurrent campaigns, journeys, and teams, cumulative user experience depends on coordination that a single team's dashboard doesn't naturally surface.
Centralized visibility: A shared view showing total messaging volume across all active campaigns and Canvases, not siloed by team, helps identify when cumulative frequency is drifting upward even if no single campaign looks obviously excessive on its own.
Clear ownership of the global cap: Someone (often a lifecycle marketing or RevOps role) should own the actual frequency cap policy, with authority to enforce it across teams, rather than leaving it to informal, inconsistently-followed guidelines.
Regular cross-team review: Periodic review of overall messaging cadence -- not just individual campaign performance -- catches drift before it becomes a genuine deliverability problem, rather than discovering the issue only after unsubscribe rates have already climbed.
Measuring Whether Your Cap Is Actually Right
Setting an initial cap is a starting hypothesis, not a permanent decision -- these signals help determine whether it's actually calibrated correctly.
Unsubscribe/opt-out trend: A rising trend, especially concentrated among recently-onboarded users experiencing your current messaging cadence, suggests the cap may be too generous.
Engagement rate on capped vs uncapped sends: If suppressed sends (that would have exceeded the cap) show meaningfully different engagement patterns than sends that got through, this signals something about how your audience actually responds to frequency.
Suppression volume itself: A cap that's rarely actually triggered may be too loose to matter; a cap triggering very frequently may be preventing genuinely valuable messages from reaching users. Neither extreme is inherently right or wrong, but both are worth understanding rather than assuming the initial number was correct.
How to Get Started
Start with a reasonable, somewhat conservative global frequency cap rather than an aggressive one.
Configure exceptions for genuinely critical transactional messages that shouldn't be blocked by promotional capping.
Consider differentiated caps for highly engaged versus general audience segments.
Monitor suppression reporting to understand how often capping is actually being hit.
Adjust based on observed engagement and unsubscribe trends over time, rather than treating the initial cap as permanent.
A Real-World Example
A retail brand running multiple concurrent campaigns -- a weekly newsletter, promotional flash sales, and behavior-triggered Canvases -- discovers that some users are receiving five or more messages within a single week when all these programs happen to overlap for a given individual. A global frequency cap limiting total messages per user per week, with an explicit exception for order-related transactional messages, brings this under control without requiring any single campaign team to coordinate manually with every other team running concurrent messaging.
After implementing the cap, the team monitors both unsubscribe rate and overall engagement, finding that capped, lower-frequency messaging actually improves click-through rates on the messages that do get sent -- fewer total messages, but each one is genuinely more likely to be opened and acted on, since recipients aren't experiencing the fatigue that comes with excessive volume.
💡 Pro Tip
Review frequency capping suppression reporting regularly, not just at initial setup -- as your messaging program grows and adds new campaigns and Canvases over time, the cumulative frequency a given user experiences can drift upward without any single team noticing, since no individual campaign feels like it's over-messaging on its own.
Frequently Asked Questions
What is frequency capping in Braze?
Frequency capping limits how many messages a single user can receive within a defined time window, across one or multiple campaigns/Canvases, protecting users from message fatigue and protecting your overall deliverability and engagement metrics.
Why does frequency capping matter for deliverability, not just user experience?
Mailbox providers and app platforms track engagement signals -- users who consistently ignore or actively unsubscribe from over-frequent messaging hurt your sender reputation, which can affect inbox placement and delivery success for all your messaging, not just the specific over-frequent campaign.
Can frequency capping apply across multiple campaigns, not just within a single one?
Yes, this is a key capability -- global frequency capping can limit total messages a user receives across your entire messaging program, not just prevent repetition within one specific campaign or Canvas.
Does frequency capping apply per channel, or across all channels combined?
Both configurations are typically possible -- capping can be set per individual channel (limiting push notifications specifically) or as a combined cap across all channels a user might receive messages through.
Can certain high-priority messages bypass frequency capping?
Yes, critical transactional messages (order confirmations, security alerts) are typically configured to bypass general frequency caps, since these serve a genuinely different purpose than promotional messaging and shouldn't be blocked by a cap designed for marketing frequency.
How do I determine the right frequency cap for my audience?
This depends on your specific audience and industry -- there's no universal correct number, and the right approach is usually starting with a reasonable, conservative cap and adjusting based on observed engagement and unsubscribe/opt-out trends over time.
Does frequency capping affect Canvas-triggered messages the same way as standalone campaigns?
Yes, frequency capping rules generally apply regardless of whether a message originates from a Canvas step or a standalone campaign, protecting the user from cumulative over-messaging regardless of the source.
Can frequency capping be different for different user segments?
Yes, more engaged or high-value segments might reasonably tolerate a higher frequency than a general or less-engaged audience, and capping rules can be configured to reflect that distinction.
What\'s the relationship between frequency capping and message priority?
When a frequency cap would otherwise block a message, priority settings determine which message actually gets sent if multiple qualifying messages are competing for a limited number of allowed sends within the capped window.
Can I see how many users are actually being affected by frequency capping?
Yes, reporting typically shows how many message sends were suppressed due to frequency capping, giving visibility into how often the cap is genuinely being hit and affecting your campaign reach.
Does frequency capping interact with Canvas re-entry settings?
Yes, both mechanisms can affect how often a user experiences messaging -- re-entry settings control whether a user can enter the same Canvas multiple times, while frequency capping limits total message volume regardless of source, and the two should be considered together when planning overall user experience.
Can frequency capping rules be tested before applying them broadly?
Yes, testing capping configuration against a smaller audience or in a controlled rollout before applying it organization-wide helps catch unintended consequences, like an overly aggressive cap suppressing genuinely important messages.
What\'s a reasonable starting point for a global weekly message cap for a typical consumer brand?
There's no universal correct number, but many consumer brands start conservatively -- often in the range of a handful of total messages per week across all channels combined -- and adjust based on observed engagement rather than assuming a specific number is correct without real data.
Does frequency capping apply the same way to new users as to long-tenured, established users?
Capping rules can be configured differently across the user lifecycle -- some brands apply lighter caps during an initial onboarding period when more frequent touchpoints are genuinely expected, then move to a lower steady-state cap once onboarding is complete.