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Usermaven Launches Attribution 2.0 For A Deeper Understanding Of Marketing ROI
Usermaven has just launched Attribution 2.0 for its privacy-friendly, cookieless and no-code web and product analytics platform to give marketers a deeper understanding of their marketing ROI.
Attribution 2.0
Attribution 2.0 includes multi-touch attribution models, look-back windows, conversion goals and more. This allows you to easily gain deeper insights to improve your marketing efforts and make data-driven decisions.
- 7 Attribution Models:
- First Touch: Gives full credit to the customer’s first interaction
- Last Touch: Attributes conversion to the final touchpoint
- Linear: Distributes credit evenly across all touchpoints
- U-Shaped: Assigns 40% credit to first and last touchpoints, 20% to middle interactions
- Time Decay: Gives more credit to touchpoints closer to conversion
- First Touch Non-Direct: Attributes to the first non-direct channel interaction
- Last Touch Non-Direct: Credits the last non-direct channel before conversion
- Customizable Lookback Window:
You can set the attribution lookback window from 30 to 180 days. This custom pre-conversion period ensures that recent, relevant interactions are properly credited in your chosen attribution model. - Conversion Time Period:
The Conversion Period filter allows you to analyze conversions within a specific date range. - Conversion Goal Selection:
Before running your attribution analysis, Attribution 2.0 now requires you to create or select a conversion goal. - Default Channel Analysis:
Usermaven provides a comprehensive breakdown of how each channel contributes to your conversions. - Visual Attribution Insights:
A clear visual representation of the impact of each channel under different attribution models is provided by the new Conversions by Channel and Attribution Model graph. It is a great tool for comparison and analysis of your marketing performance.
Usermaven‘s Attribution 2.0 enables you to gain accurate insight into your marketing performance, optimize your marketing spend based on the true value of the channel and finally make data-driven decisions with confidence.
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