Reporting
Attribution Models
3min
An attribution model determines how credit is assigned to different touchpoints in a customer journey. Consider this example:
A potential customer:
- Searches on Google and clicks on a blog post from your website.
- Sees a Facebook ad a few days later and clicks through to a product page.
- Receives an email campaign and clicks the link inside to revisit your website.
- Clicks a retargeting ad on Instagram and finally makes a purchase.
How do you determine which channel contributed the most to this conversion? Attribution models answer this question in different ways:
- First-Touch Attribution: Gives full credit to the first interaction, useful for measuring brand awareness and tracking the impact of SEO or paid ads on customer lifetime value (LTV). This helps businesses optimize acquisition strategies effectively.
- Last-Touch Attribution: Assigns 100% of the conversion credit to the last touchpoint before the sale. This model is particularly valuable for email marketing and retargeting campaigns since it focuses on the final engagement that drove the conversion.
- Linear Attribution: Distributes credit equally across all touchpoints that led to the conversion. Since this is a multi-touch attribution (MTA) model, credit is divided among different interactions, and values may not always be whole numbers (e.g., 1.23). This happens because conversions are weighted proportionally based on the number of touchpoints, ensuring a more balanced representation of the customer journey.
- AI (Machine Learning) Attribution: Uses machine learning to assign credit based on actual impact, dynamically adjusting based on historical data and user behavior. This model activates only after 100,000 page views to ensure accuracy and is ideal for businesses looking for data-driven, adaptive attribution.
Unlike other providers, Weberlo allows you to seamlessly switch between all four attribution models at any time. Your data is always available across First-Touch, Last-Touch, Linear, and AI Attribution views, meaning you can analyze different models without losing historical data. This smooth user experience enables marketers to compare results in real time and choose the most effective attribution approach for their strategy.
Updated 08 Feb 2025
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