Attribution helps teams attribute conversion credit to the touch-points in a user-journey, whether it be just to the first or last touch which are single-touch attribution models or to multiple touchpoints using a multi-touch attribution model like U-shape or Linear.
Let’s take an example user journey:
- A user sees an ad for a product on Facebook
- The user clicks on the ad and is taken to the product page on the company's website
- The user adds the product to their cart and begins the checkout process
- The user abandons the checkout process
- The user receives a retargeting ad for the product on Instagram
- The user clicks on the ad and completes the purchase
In this example, there are two touchpoints that contribute to the successful conversion: the Facebook ad and the Instagram ad. Using an attribution model, we can assign different weights to these touchpoints to determine their relative importance in the conversion.
- Using a linear attribution model, we could assign a weight of 0.5 to each touchpoint, meaning that both the Facebook ad and the Instagram ad contributed equally to the conversion
- Using a J shaped attribution model, we could assign a weight of 0.75 to Facebook ad, and 0.25 to the Instagram ad
- Using last touch model, the complete conversion can be attributed to the Instagram ad
- Using first touch model, the complete conversion can be attributed to the Facebook ad
Step 1 - Add your conversion metric
Step 2 - Attribution makes sense only when distributing the conversion metric across segments. So head to the breakdown section and choose the Mixpanel computed property -
Step 3 - In the second layer that opens up, choose the property you want to break-down by (eg. UTM medium). You can also choose a custom property to breakdown here, for example marketing channel which generally is a combination of UTM medium, UTM source and referrer.
Step 4 - You have a working attribution model. By default, Mixpanel will assign the metric the Last touch model with a 30 day lookback window. To change the model, head to the metric section
Step 5 - If you want to include only certain channels or touchpoints in your attribution analysis, you can filter touchpoints from the breakdown overflow menu. A use-case for this is excluding organic touchpoints from attribution analysis.
👉🏽 NOTE: if you are running attribution predominantly on UTM_medium, UTM_source, UTM_campaign, make sure you’re tracking UTM parameters as event properties on every user touchpoint. If you use a Mixpanel js-sdk, we’ve updated our sdk to track utm parameters more effectively to support multi-touch attribution models.
- First Touch - Gives 100% credit to the first touchpoint within the attribution lookback window
- Last Touch - Gives 100% credit to the last touchpoint within the attribution lookback window
- Linear - Gives equal credit to every touchpoint seen leading up to a conversion within the attribution lookback window
- Participation - Gives 100% credit to every unique touchpoint seen within attribution window. The total number of conversions is inflated compared to other attribution models. For example with 5 property values, each would receive 100% credit showing 5 conversions.
- Time-Decay - The weight of each channel depends on the amount of time that passed between the touch point initiation and the eventual conversion. This model follows an exponential decay with a 7 day half-life parameter.
- U-shaped - Gives 40% credit to the first touchpoint, 40% credit to the last touchpoint, and divides the remaining 20% to any touch points in between. With 2 touchpoints, the credit is normalized (50%, 50%). With 6 touch points the middle 4 touch points would share the 20% (40%, 5%, 5%, 5%, 5%, 40%).
- 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%).
- Inverse J-shaped - Gives 60% credit to the first touchpoint, 20% credit to the last touchpoint, and divides the remaining 20% to any touch points in between. With 2 touchpoints, the credit is normalized (75%, 25%). With 6 touch points the middle 4 touch points would share the 20% (60%, 5%, 5%, 5%, 5%, 20%).
- Custom - Customize the weightage to be given to the first and last touchpoint, and all other touchpoints in between based on your use-case.
- User journey: Consists of touchpoints and the conversion event. It is possible for a conversion event to have no corresponding touchpoints (eg. utm parameters). In this case we consider it a ‘direct’ conversion
- Conversion: The primary event you’re interested in analyzing with multi-touch attribution models. Typically some final value generating interaction such as “Signup” or “Upgrade” or “Payment”.
- Touchpoint: These are actions (events) a user’s taken or exposed to along the journey before doing the conversion event. [Eg. does event A → B → C → D (conversion event) in a 7 day period; For a lookback window of 7 days, A, B, C are all considered touchpoints]
- Attributed by property: This is the property on a touchpoint event that we use for the attribution model. The canonical example is utm_source
- Lookback window: The time window where a user's events with this attribution property are counted towards the calculation. The window ends when the conversion metric happens.