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analyst-attribution

Analyze campaign attribution discrepancies between Braze and mobile measurement partners.

Updated Apr 6, 2026
Search Tags:#integration#diagnostics#measurement#attribution#attribution-models#mmp#braze
One-click install
npx skills add https://github.com/delta-and-beta/braze-agency --skill analyst-attribution
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: analyst-attribution
Source: https://github.com/delta-and-beta/braze-agency/tree/main/skills/analyst-attribution
Command: npx skills add https://github.com/delta-and-beta/braze-agency --skill analyst-attribution

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Attribution and measurement data from multiple mobile measurement partners and ad platforms often disagree, making it hard to confidently determine which touchpoints drove installs, re-engagements, or conversions. This Skill provides a structured diagnostic lens to identify mismatched attribution windows, differing attribution models, missing postback mappings, and device identifier mapping issues that commonly cause discrepancies between Braze and external partners.

Core Features & Use Cases

  • Partner mapping & integration checklist: Step‑wise guidance for mapping partner postbacks to Braze fields and verifying data import keys and endpoints.
  • Model & window diagnostics: Compare last-touch, first-touch, linear, and algorithmic models and reconcile differences in attribution windows and view-through/click-through settings.
  • Troubleshooting workflows: Walk through common issues such as missing device identifiers, organic vs. paid attribution, re-engagement vs. re-attribution, and community-maintained integration caveats.
  • Analytics & segmentation advice: Use attribution fields for ROAS/CPA analysis, audience segmentation, and Currents/warehouse exports for cross-system reconciliation.
  • Use Case: Diagnose why Braze shows fewer attributed installs than an MMP by validating device ID mappings, postback configuration, attribution windows, and event forwarding settings.

Quick Start

Analyze recent campaign attribution discrepancies between Braze and a specified MMP, identify likely root causes, and recommend configuration or segmentation changes to reconcile counts.

Frequently Asked Questions about analyst-attribution

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Why do attribution counts differ between Braze and my mobile measurement partner?▼

Attribution counts differ between Braze and your MMP due to mismatched attribution windows, differing attribution models, or missing postback mappings. Diagnosing device identifier mappings and event forwarding settings helps identify these root causes.

How do I map MMP postback fields to Braze attribution attributes?▼

Mapping MMP postback fields to Braze attribution attributes requires verifying data import keys and endpoints through a step-wise integration checklist. This ensures external partner data correctly populates Braze attribution fields for accurate measurement.

Does this attribution diagnostics process work with Adjust, AppsFlyer, and Branch?▼

Attribution diagnostics work with Adjust, AppsFlyer, Branch, Singular, Kochava, Airbridge, and Linkrunner. The process applies to both mobile and web integrations when debugging postback mappings and attribution windows across these platforms.

What is the best way to reconcile attribution window mismatches in campaign measurement?▼

Reconciling attribution window mismatches involves comparing view-through and click-through settings across last-touch, first-touch, linear, and algorithmic models. Adjusting these configurations and segmentation strategies aligns measurement counts between systems.

How can I use attribution fields for ROAS and CPA analysis in Braze?▼

Using attribution fields for ROAS and CPA analysis involves applying audience segmentation and Currents warehouse exports. This enables cross-system reconciliation of paid versus organic attribution data for deeper analytics.

Attribution troubleshooting not resolving missing installs, what are common limitations?▼

Attribution troubleshooting limitations often involve organic versus paid attribution classification issues, re-engagement versus re-attribution distinctions, and missing device identifiers. Community-maintained integration caveats highlight these common configuration edge cases.

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