Building predictive goals can be an iterative process. After you create a goal and review the resulting prediction, you might decide to edit your goal criteria to see if you get a different result. Use the steps in this article to create, edit, or delete a predictive goal.
In this article
Create a new predictive goal
NOTE
At this time, you can create up to six predictive goals. If you already have six, and want to create another, delete one of your existing predictive goals. See Delete a predictive goal.
To create a predictive goal:
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Navigate to Insights > Predictive Goals and click New predictive goal to access the Goal Criteria page.
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Specify the events and properties that are relevant to your goal.
For example, to find people who are likely to be highly engaged with your product, your goal criteria could look for users who might add at least one item to their carts OR redeem at least one promo code, AND who have a Premium account type within a given month.
Click Perform event or Have property, depending on the type of data you’re using as criteria.
Select the event or property names and frequency operators and values.
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If you want to include more goal criteria, add it:
Immediately following the first item to create an "or" statement (if either criteria is satisfied, a user might convert on the predictive goal).
In the box below the previous entry to create an "and" statement (this criteria must also be satisfied to count as a conversion).
Select the period of time within which the events are likely to take place.
Provide a Predictive goal name, a Contact property name, and a description.
Predictive goal names appear on the header of the Goal Details page. For readability, you might use a sentence structure (for example, "Remain highly engaged").
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Contact property names appear in segmentation and on the user profile. Structure them as you do other metrics used in your project (for example,
HighlyEngagedPropensity
).
- Click Create predictive goal. After 12–24 hours, you'll be able to review results.
TIP
To learn how a sample brand created their first predictive goal, see Create a predictive goal for C&M.
Review your prediction
To view the results of a prediction that has a Ready status:
Navigate to Insights > Predictive Goals.
Click the goal you want to view.
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Select a group of users with conversion probabilities you'd like to focus on. Use the radio buttons above the chart to select the top or bottom 10% of your users, or select a custom range by entering specific values (or using the sliders).
If the prediction shows that most of the users in your project are likely to convert on a given predictive goal, edit your goal criteria to include additional criteria.
If the prediction shows that significantly fewer than 1,000 users are likely to convert, pare back your goal's criteria.
If the prediction doesn't provide the insight you need, try different data points altogether.
TIP
To learn more about the information in your prediction, see Evaluate your prediction.
Edit a predictive goal
To edit a predictive goal:
Navigate to Insights > Predictive Goals.
In list view on the Predictive Goals page, click the overflow button (three dots) in the goal's row, and click Edit.
Provide the new details and click Update predictive goal. After 12–24 hours, you'll be able to review results.
Delete a predictive goal
WARNING
Deleting a predictive goal also deletes the related conversion probability property and scores from all user profiles in your project. References to the conversion probability property (user profile field) that you've included in campaigns, journeys (workflows), lists, or templates will be impacted. Delete all references to conversion probability user profile fields before you delete a predictive goal.
On the Predictive Goals page, click the overflow button (three dots) in the goal's row, and click Delete. Within 12–24 hours, the predictive goal is deactivated, and all related contact properties are removed from user profiles.
Next steps
Learn how to evaluate your prediction, once it's ready. See Evaluate your prediction.
For an example of how a fictional company built predictive goals to meet their needs, see Use case: Reward loyalty with memorable experiences.
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