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How to you manage 'Happy customer signals' in multiple Canvas
Hey Lin_To ,
I had the exact same challenge with overlapping signal-based canvases and tags helped us solve it. The key is to think from the top - you need to see the whole ecosystem first before building individual canvas logic. The governance structure you're looking for is Canvas-level tags - they're Braze's built-in orchestration layer for this. We tag each Canvas with 2-3 tags - for example, taking your use case, you could use tags like advocacy, revenue_expansion, tier1_revenue, tier2_advocacy etc. Then we use three main approaches: First, in Canvas entry criteria we add exclusions like "Last Received Message from Canvas With Tag 'advocacy' within 30 days" - this prevents users from entering multiple overlapping canvases. Second, we set frequency capping by tag in workspace settings (Settings → Frequency Capping) with rules like "max 2 messages/week from advocacy tag" or "max 1 message/week from tier1_revenue tag" - these work with standard frequency caps and the most restrictive rule wins. Third, we create a priority hierarchy based on revenue impact where tier1 canvases (your highest revenue generators like upgrades and renewals) have no exclusions and short cooldowns, tier2 (advocacy programs like referrals) excludes if tier1 sent in last 30 days, and tier3 (engagement) excludes if tier1 or tier2 sent. This ensures your revenue-critical moments always get priority while still capturing advocacy opportunities without fatiguing users. Important note: tags are counted at send time based on current Canvas tags, so don't frequently change tags on active Canvases. This approach prevents signal collision, controls user fatigue, and scales without needing a master canvas. We bulk tagged all Canvases, set the frequency caps, added tag-based exclusions to entry criteria, and documented the tag taxonomy for the team. Tags give you centralised governance while keeping each Canvas focused. Hope this helps!
- Lin_To12 days agoSupporter
This is very helpful, thank you for sharing!
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