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All attribution starts with tracking

Dema's first-party tracking captures every customer touchpoint, ensuring you own and control your data for precise attribution and actionable insights. Seamlessly integrating with your e-commerce platform, our tracking solution monitors website interactions, marketing channels, order management, and fulfillment costs.

Learn more about Dema's own tracking pixel

Dema's Machine learning Attribution Model

Dema's advanced data-driven attribution model leverages deep learning to analyze how each traffic channel influences a customer’s purchasing decision. Unlike traditional models, it considers dynamic interactions between different ad platforms and incorporates session details like user activity and device used, ensuring precise predictions. By accounting for time decay, it recognizes that ads closer to the purchase time have greater impact. Tested on extensive real-world marketing data, Dema’s model provides superior accuracy in predicting conversions, helping marketers optimize their ad spend effectively.

mapping: A Key Benefit when using attribution

Dema enhances attribution accuracy by providing flexible traffic mapping and grouping, eliminating the dependence on rigid UTM naming conventions. Customized channel mapping ensures precise traffic classification, even when UTMs are misused. This allows for easy sorting of incoming traffic and cost assignment to specific channels such as influencer collaborations or Snapchat ads. Automated and with a user-friendly update interface, Dema ensures reliable, standardized data for your attribution model, significantly improving the reliability of your insights.

ATTRIBUTION MODEL COMPARISON

To illustrate how different attribution models work and how important it is to use a data-driven attribution model like Dema's, we can use an example customer journey. Let's say that we have one customer with 5 touchpoints before purchasing, ie, sessions. With the help of the Dema tracking script, we know what sources sent the customer to the shop, and after the purchase is made, the different attribution models will attribute different values to each source.

Last click attribution in Dema

The last-click attribution model assigns 100% of the credit for a conversion to the last touchpoint that the customer interacted with before making a purchase. This approach is straightforward and easy to implement but overlooks the influence of earlier interactions in the customer journey. As a result, it may not accurately reflect the true impact of all marketing efforts that contributed to the final conversion. Applying it to the example above would give full credit to the Newsletter.

Linear attribution in Dema

The linear attribution model evenly distributes credit for a conversion across all touchpoints in the customer journey. This method acknowledges that each interaction contributes equally to the final conversion, providing a balanced view of the customer’s path. While simple and fair, it doesn’t account for the varying influence that different touchpoints may have. Applying it to the example above it would mean that 40% of the order value would be attributed to TikTok, which has two sessions, and 20% each to the rest of the touchpoints.

FAQ about Attribution in Dema