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Braze

skill-thatrebeccarae-claude-marketing-braze · by thatrebeccarae

Braze customer engagement platform expertise. Audit campaigns, Canvases, segments, messaging channels, and data architecture. Use when the user asks about Braze, customer engagement, push notifications, in-app messaging, cross-channel orchestration, or lifecycle marketing at scale.

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Install

$ agentstack add skill-thatrebeccarae-claude-marketing-braze

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Braze Customer Engagement Platform

Expert-level guidance for Braze — auditing, building, and optimizing Canvases, campaigns, segments, data architecture, and cross-channel messaging.

Install

git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/braze ~/.claude/skills/

Core Capabilities

Canvas Auditing & Design

  • Audit existing Canvases for logic errors, timing issues, and missed opportunities
  • Design multi-step, multi-channel Canvases (email, push, SMS, in-app, Content Cards, webhook)
  • Implement Canvas Flow features: Action Paths, Audience Paths, Experiment Paths, Decision Splits
  • Review entry schedules, exception events, re-eligibility, and rate limiting

Segmentation & Targeting

  • Build segments using Braze's filter system (user attributes, custom events, purchase behavior, engagement)
  • Design segment extensions for complex queries (event property filters, nested AND/OR logic)
  • Implement predictive audiences (Predictive Churn, Predictive Purchases)
  • Connected Audience sync from external CDPs (Segment, mParticle, Amplitude)

Campaign Strategy

  • Plan cross-channel campaigns: email, push, SMS, in-app messages, Content Cards, webhooks
  • A/B and multivariate testing with Intelligent Selection
  • Personalization with Liquid templating, Connected Content, and Catalogs
  • Frequency capping and Intelligent Timing optimization

Data Architecture

  • Design custom event and attribute schemas
  • Implement Currents data export (to Snowflake, BigQuery, S3, Mixpanel)
  • Plan data migration from other platforms (Klaviyo, Iterable, Salesforce MC)
  • API integration patterns (REST API, SDK implementation)

Deliverability & Compliance

  • Email: SPF, DKIM, DMARC, IP warming schedules
  • Push: Token management, provisional authorization, opt-in strategies
  • SMS: Short code vs long code, compliance (TCPA, CTIA), opt-in management
  • GDPR/CCPA data handling and consent management

Key Benchmarks

| Metric | Good | Great | Warning | |--------|------|-------|---------| | Email Open Rate | 20-25% | 30%+ | 0.5% |

Essential Canvas Checklist

  1. Onboarding — Multi-step cross-channel (push opt-in prompt, email welcome, in-app tutorial)
  2. Activation — Drive key actions in first 7 days (feature adoption, profile completion)
  3. Re-engagement — Target lapsed users (7d, 14d, 30d inactivity tiers)
  4. Transactional — Order confirmations, shipping updates, receipts (use Transactional API)
  5. Promotional — Scheduled campaigns with audience targeting and frequency caps
  6. Abandoned Cart / Browse — Trigger-based with exception events for conversion
  7. Winback — Long-term lapsed users (60d, 90d, 120d)
  8. Feature Announcement — Targeted by segment, channel preference, and platform
  9. NPS / Feedback — Post-interaction surveys via in-app or email
  10. Sunset — Suppress unengaged to protect deliverability

Workflow: Full Braze Audit

When asked to audit a Braze workspace:

  1. Canvas & Campaign Inventory — List all active Canvases and campaigns, identify gaps
  2. Channel Coverage — Map which channels are active (email, push, SMS, in-app, Content Cards)
  3. Segmentation Review — Evaluate segment definitions, overlap, and growth
  4. Data Architecture — Custom events, attributes, schema consistency, data freshness
  5. Personalization — Liquid usage, Connected Content calls, Catalog implementation
  6. Performance Metrics — Channel-level KPIs, Canvas step conversion rates, variant performance
  7. Deliverability — Email reputation, push token health, SMS compliance
  8. Frequency & Fatigue — Global frequency caps, quiet hours, Intelligent Timing usage
  9. Integration Health — SDK version, Currents export, CDP sync, webhook reliability
  10. Recommendations — Prioritized by impact with estimated effort (Quick Win / Medium / Large)

Braze vs Klaviyo Context

When working with teams migrating or comparing:

  • Braze excels at: Cross-channel orchestration, mobile-first (push, in-app), enterprise scale, real-time event streaming
  • Klaviyo excels at: E-commerce focus, simpler setup, Shopify-native, strong email/SMS for DTC
  • Key migration consideration: Braze's event/attribute model is more flexible but requires upfront schema design

How to Use This Skill

Ask me questions like:

  • "Audit my Braze Canvases and identify gaps"
  • "Design an onboarding Canvas for a mobile app"
  • "Help me plan a migration from Klaviyo to Braze"
  • "What's the best data architecture for a SaaS product in Braze?"
  • "My push opt-in rates are low — help me design an opt-in strategy"
  • "Build a re-engagement Canvas with Experiment Paths"
  • "Plan IP warming for a new Braze workspace"

For detailed Braze data model, Liquid reference, API endpoints, and Canvas patterns, see [REFERENCE.md](REFERENCE.md).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.