Attribution Models

Information about the attribution models that ThoughtMetric supports.

Michael Signorella avatar
Written by Michael Signorella
Updated over a week ago

What is an attribution model?

An attribution model is how you assign credit or value for sales and conversions across various customer touch points. It includes all your digital channels – paid search, display, email, social media, organic search, referrals – and the impact that each one has on the eventual conversion.

What attribution models does ThoughtMetric support?

ThoughtMetric supports the five main industry standard attribution models, as well as our proprietary data driven model.

  1. ThoughtMetric Data Driven Multi-touch (default)

  2. First Touch

  3. Last Touch

  4. Linear

  5. Position Based

  6. Time Decay

1.) ThoughtMetric Data Driven Multi-Touch

This is our proprietary data driven attribution model. It is a multi-touch model meaning that it will split up credit across all of the marketing channels that influenced a sale. This model is the default attribution model for ThoughtMetric and is our recommended model.

The ThoughtMetric data driven model takes many data points and factors into account when deciding which marketing channel deserves credit for a sale. This model considers data from both the ThoughtMetric tracking pixel, as well as the post purchase "how did you hear about us surveys".

The ThoughtMetric data driven model is designed with the e-commerce customer journey in mind to get you the most accurate and reliable understanding of how many orders are really coming from your various marketing platforms. Facebook will overreport their performance by taking too much credit for sales. For example if a customer clicked on a Facebook ad on Monday, then clicked on a Google Ad on Tuesday, then made a $100 purchase on Friday, Facebook will claim full credit for this sale and report $100 in revenue completely ignoring the fact that the customer also clicked on Google Ads. Likewise, Google Ads will also report $100 in revenue. So you have two ad channels reporting a total of $200 in revenue when you really only had one sale for $100. This is where ThoughtMetric comes in. ThoughtMetric knows that the customer clicked on both Facebook ads and Google ads and will split up the credit for the sale between those two sources.

2.) First Touch

The first touch (sometimes called first click) model will provide all the credit for any order to the first touchpoint in a conversion path. This is great for insight into how people find you and the top of your funnel. However, it is limited in the fact that it doesn't take any other customer touchpoints into consideration.

3.) Last Touch

The last touch model will provide all the credit for any order to the last touchpoint in a conversion path. The last touch model is a great way of looking at your bottom of the funnel conversions. This model gives you a clear look into which marketing touchpoints are the final piece of the puzzle to getting your customers to make a purchase.

4.) Linear

The linear model provides equally weighted credit to each touch point in the visitor's journey.

In the example above there are five touch points in total, using a linear attribution model, each touch point will split credit for the conversion equally at .20 each.

The linear model allows you to look at your return on ad spend across your marketing efforts for the entire length of your funnel equally. This is a great way to look at your marketing channels holistically providing equal credit to each touch along the visitor's journey.

5.) Position Based

Position based attribution assigns 40% credit to the first touch, 40% credit to the last touch, and splits the remaining 20% across the remaining touchpoints.

This is a balanced model which gives more credit to the first and last touchpoints to represent the fact that those touchpoints are often the most important.

6.) Time Decay

This model will provide greater credit to the touches that occurred closest to the conversion.

If the sales cycle involves only a short consideration phase, the Time Decay model may be appropriate. This model is based on the concept of exponential decay and most heavily credits the touch points that occurred nearest to the time of conversion.

The Time Decay model has a default half-life of 7 days, meaning that a touchpoint occurring 7 days prior to a conversion will receive 1/2 the credit of a touchpoint that occurs on the day of conversion. Similarly, a touchpoint occurring 14 days prior will receive 1/4 the credit of a day-of-conversion touchpoint.

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