By the end of this lesson, you’ll be able to:
- Understand how points are allocated to Campaign Member responses based on Campaign Attribution Model settings
- Know the key benefits of a point weighted Attribution system
- Be able to calculate the revenue amount for a given Campaign Member response based on an example of a Model configuration and Opportunity
NOTE: These lessons refer to a fictitious company, Spiral Inc. and how they utilize Campaign Attribution to solve marketing challenges. Please review Intro to Spiral Inc. to learn more about Spiral’s use case.
Dina Rogers, Director of Marketing Operations at Spiral Inc. needs to build some custom models based on Spiral Inc.’s business processes to more effectively measure Campaign performance. Before building out her models, Dina needs to understand how point weighting works within Full Circle Campaign Attribution so she can make informed decisions about the weights she applies in her models based on her desired output.
Full Circle’s Campaign Attribution system is a very flexible tool for attributing Opportunity value (represented by a currency field on the Opportunity object) to Campaigns based on mathematical attribution models that you custom configure. The system uses a simple and effective point-based weighting system.
Ultimately, the goal is to allocate Opportunity value to Campaign Member responses that are associated with the Opportunity (whether through Contact Roles on the Opportunity or from Contacts at the same Account as the Opportunity). It’s up to the attribution model to determine which Campaign Member responses to consider in this allocation.
To determine how much value to allocate to each response, the attribution model has several areas where points can be assigned. For example: To give an even amount of credit to each Campaign Member response on Contacts on the Opportunity you would give 1 point of credit to Primary Contact and 1 point of credit to Other Contact. Dina may decide to give extra points to the Primary Contact so the Primary Contact’s responses get a greater proportion of the Opportunity’s value:
Another example of criteria is the timeframe of the Campaign Member response. Dina may decide for certain models she wants to give greater weight to the very First Touch relative to the Opportunity as well as the Last Touch before Opportunity creation. Weights can be applied to these areas as well:
As Dina builds out her attribution models she’ll need to choose the criteria that is most relevant to Spiral Inc.’s business processes. More on how Dina decides to customize her models in Lesson 6 (coming soon).
The attribution model evaluates each response against the criteria, and allocates the configured number of points to the Campaign Member response for each criteria it meets.
Example Point Weighting Breakdown
For example: let’s say Dina has configured a model that gives weight as outlined above: 2 points to the Primary Contact, 1 point to Other Contact, 5 points to First Touch, and 5 points to Last Touch.
If a single response was the Last Touch and on the Primary Contact, the response would be allocated 7 points, 2 because it’s on the Primary Contact, and 5 because it’s the Last Touch on the Opportunity.
This process, of testing each response and assigning points based on criteria from the model, is repeated for every response. You might ask, how many points can you allocate for each criteria? The answer – as many or as few as you want. Why, you can even assign negative points – where if a response meets a certain criteria, you reduce its total points.
Conceptually, it’s similar to what happened back when you were in school and a teacher assigned a possible score to an exam. Let’s say the test has a possible grade of 100, but it was a very hard test, so the highest score was a 48. If your teacher was cruel, she’d flunk the entire class because everyone did so poorly. But if your teacher decided that the test was too hard, she might grade on a curve, adjusting the top grade to match the actual scores. When a teacher grades on a curve, you don’t care about the actual score you get on the test – you only care what your score is in relation to the other students.
Full Circle Campaign Attribution does much the same thing with the points that are allocated to each Campaign Member response. Campaign Attribution allocates opportunity value based on the total number of points that are allocated.
Example Opportunity Value Breakdown
Taking our example a bit further, let’s say we have an Opportunity with an Amount of $1,000. Using the same model above, we have 3 Campaign Member touches, one that is on the Primary Contact and is also the First Touch, another that is on the Primary Contact and is also the Last Touch, and another response that is on another Contact Role on the Opportunity (not Primary). How would that $1,000 be split among the 3 touches?
Evaluating the model criteria against the 3 touches, the Opportunity would have a total of 15 points. The $1,000 of Opportunity value would be split across the 3 touches as follows:
- Campaign Member 1 with 7 points would get: ($1,000/15)*7 = $466.67
- Campaign Member 2 with 7 points would get: ($1,000/15)*7 = $466.67
- Campaign Member 3 with 1 point would get: ($1,000/15)*1= $66.67
What if instead the model allocated 50 points to response A and 150 points to response B? The value allocation would remain the same. The total number of points doesn’t matter; all that matters is the proportion of points allocated to each response.
By basing attribution calculations dynamically on the points you define, attribution models have enormous flexibility when it comes to assigning weights to different criteria.
When it comes to configuring an attribution model, just remember that the weight you assign to each criteria depends only on its relation to the total weight on all of the responses for the opportunity.
Whether you want to assign values from one to 10, or 1 to 100, or even include negative numbers, doesn’t matter at all.
Full Circle Campaign Attribution allows you to specify the weighting you wish based on your own experience and judgment, without any artificial limits, and without the stress of keeping track of distributing a fixed number of points. You can easily adjust models and iterate configurations to arrive at the weighting that makes the most sense for your organization.