attribution-model

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Set up attribution models. Use when: multi-touch attribution, credit distribution rules, GA4 config, channel contribution.

AI & Automation 136 stars 37 forks Updated 3 days ago MIT

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# /digital-marketing-pro:attribution-model ## Purpose Design and recommend a multi-touch attribution model with implementation guidance, credit distribution rules, and platform-specific configuration. Produces a complete attribution strategy tailored to the business's data maturity, sales cycle, and analytics infrastructure. ## Input Required The user must provide (or will be prompted for): - **Sales cycle length**: Average number of days from first touchpoint to conversion (e.g., 7 days for e-commerce, 90+ days for B2B enterprise) - **Active marketing channels**: All channels currently running — paid search, paid social, organic search, email, display, video, affiliate, direct mail, events, referral, content marketing, etc. - **Conversion types**: The key conversion events being tracked — lead form, MQL, SQL, opportunity, customer, revenue, or e-commerce purchase - **Data maturity level**: Current analytics sophistication — beginner (basic GA4, limited tagging), intermediate (UTM tracking, CRM integration, multi-platform), or advanced (data warehouse, CDI, unified user IDs) - **Current analytics tools**: Platforms in use — GA4, HubSpot, Salesforce, Adobe Analytics, Mixpanel, custom data warehouse, or third-party attribution tools - **Touchpoint volume**: Approximate monthly interactions across all channels (thousands, tens of thousands, hundreds of thousands) - **Offline touchpoints**: Whether offline channels (trade shows, phone calls, direct mail, in-store visits, sal...

Details

Author
indranilbanerjee
Repository
indranilbanerjee/digital-marketing-pro
Created
4 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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