Marketing Analytics Stack Audit AI Prompt

Audit the marketing analytics stack for this organization and identify gaps, redundancies, and improvement opportunities.

Current tools: {{tools_list}}
Data flows: {{data_flows}}
Team capability: {{team_capability}}

1. Analytics stack layers:
   Map the current stack against these layers:
   - Data collection: (pixels, SDKs, server-side tagging, webhooks)
   - Data transport: (tag management, event streaming, APIs)
   - Data storage: (data warehouse, CDP, CRM, platform-native storage)
   - Data transformation: (dbt, Fivetran, custom ETL)
   - Analytics and reporting: (BI tool, platform dashboards, spreadsheets)
   - Activation: (email platform, ad platforms, personalization engine)

2. Data quality assessment per layer:
   - Collection: are all key events tracked? Are there data gaps?
   - Storage: is there a single source of truth or multiple conflicting sources?
   - Transformation: is business logic documented and version-controlled?
   - Reporting: do different teams use different definitions for the same metric?

3. Redundancy identification:
   - Are multiple tools doing the same job? (Two CDPs, two email platforms)
   - Can any tools be consolidated without loss of capability?
   - What is the total annual cost of the current stack?

4. Critical gaps:
   - Multi-touch attribution: is there a cross-channel attribution solution beyond platform-reported ROAS?
   - Customer identity resolution: can you link the same person across devices and channels?
   - Offline-to-online: is offline (store, call center) data connected to digital behavior?
   - Incrementality measurement: is there any program to measure true causal marketing impact?

5. Priority improvements:
   - Top 3 gaps with highest impact on marketing decision quality
   - For each: recommended solution, estimated implementation effort, expected ROI

6. Data governance:
   - Is there a marketing data dictionary? (Agreed definitions for all metrics)
   - Who owns each data source and is responsible for its quality?

Return: stack layer map, quality assessment, redundancy analysis, critical gaps, priority improvements, and governance recommendations.