how does linear attribution work? does the number of events for each utm source impact the resulting attribution, i.e., if a user visited more times through sourceA instead of source B or sourceC, will sourceA get more credit? or just 33%
Hi Elena M., Please stand by as I search the Mixpanel knowledge base for an AI-powered answer. I normally take about 15 seconds or so. In case AI cannot answer your question, feel free to reach out to Mixpanel support at mixpanel.com/get-support. If you have follow-up questions for this thread, please tag me again with your question: @kapa.ai <follow-up question> 👋
Feel free to ask a follow-up question once I've answered by mentioning me with @kapa.ai
Linear attribution in Mixpanel assigns equal credit to every unique touchpoint (e.g., UTM source) that a user interacts with during the attribution lookback window leading up to a conversion. This means that if a user’s journey includes three different UTM sources (sourceA, sourceB, sourceC), each will receive exactly 33% of the credit for the conversion, regardless of how many times the user interacted with each source.The number of events or visits associated with each UTM source does not increase the share of credit for that source in linear attribution. Each unique touchpoint is counted once, and the credit is divided equally among them. For example, if a user visits your site five times via sourceA, once via sourceB, and once via sourceC before converting, all three sources will still receive 33% credit each—not more for sourceA due to the higher number of visits.This is confirmed in Mixpanel’s documentation: > Linear - Gives equal credit to every touchpoint seen leading up to a conversion within the attribution lookback window Docs: Attribution ModelsAnd further clarified in the blog: > Linear attribution weighs all touchpoints equally. It’s the easiest model to implement and offers a bird’s eye view of the entire customer journey. How multi-touch attribution helps teams make data-driven decisionsSo, in summary: with linear attribution, each unique touchpoint (e.g., UTM source) gets an equal share of credit, regardless of the number of events or visits per source.
kapa.ai is still learning and improving, please let me know how I did by reacting below.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
Let me check the knowledge base for you again. One moment! 📚
You're correct that, according to Mixpanel's documentation, the linear attribution model should assign equal credit to each unique touchpoint leading up to a conversion. For three unique sources (direct, google, facebook), you would expect to see 0.33 for each if linear attribution is applied as described: > Linear - Gives equal credit to every touchpoint seen leading up to a conversion within the attribution lookback window Docs: Attribution ModelsHowever, the result you're seeing (direct: 0.75, google: 0.13, facebook: 0.13) does not match the expected output for linear attribution. This pattern more closely resembles a J-shaped attribution model, where the last touchpoint receives the most credit, the first touchpoint receives some, and the middle touchpoints share the remainder: > J-shaped - Gives 20% credit to the first touchpoint, 60% credit to the last touchpoint, and divides the remaining 20% to any touch points in between. With 2 touchpoints, the credit is normalized (25%, 75%). With 6 touch points the middle 4 touch points would share the 20% (20%, 5%, 5%, 5%, 5%, 60%) Docs: Attribution ModelsIt's possible that the attribution model applied in your report is not linear, but rather J-shaped or another model. By default, Mixpanel uses the last touch model, but you can change the model in the metric section. To ensure you are using linear attribution, double-check the attribution model selected in your report setup: > To change the model, head to the metric section. Leverage Mixpanel to experiment with linear, time decay, and custom attribution models based on your product’s unique user journey. How to implement multi-touch attribution using MixpanelIf you have confirmed that linear attribution is selected and are still seeing these results, there may be additional configuration or data issues at play. The knowledge sources do not provide further details on this specific discrepancy.
kapa.ai is still learning and improving, please let me know how I did by reacting below.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
