Predict propensity to buy items with an attribute
You can use the Predictions module to calculate the probability of customers buying items with a particular attribute value, such as color or size. The results can be used for better targeting of your marketing efforts.
In this use case example, an additional condition is added - the items must be available at the time of calculation.
Prerequisites
- Enable the Propensity model.
- The item feed must contain the attribute you want to use for the prediction and that attribute must be added to filterable attributes.
Creating the prediction
- Go to
> New prediction and select Propensity as the prediction type. - Select an audience for the prediction.
For more information, see the Predictions quick start article.
Define the item attribute
In this section, you define the items for which you want to calculate the prediction. This is done by creating an item filter that matches only the items with an attribute of your choosing.
- In the Item feed section, click Define.
- Click Choose item feed.
- Select the catalog that contains the items you want to make the prediction for.
Result: the Item filter section appears. - Click Define item filter.
- From the Select attribute drop-down list, select an attribute.
You can use the search field.
Note: Custom attributes have anattributeprefix in the selector. - From the drop-down list that appears, select the Equal operator.
- From the list of available values that appears, select a value.
You can use the search field.
You can only choose attribute values which already exist in the item feed. - Click Add condition.
- From the Select attribute drop-down list, select the availability attribute.
- From the drop-down list that appears, select the Equal operator.
- From the list of available values, select
true.
The filter matches items with an attribute value (attributes.exampleAttribute = "example value") and the items must be available - Click Save.
- Save the item feed configuration by clicking Apply.
Additional settings and saving
Configure the additional settings (or leave them at default) and click Save & Calculate.
What’s next
After the calculation is completed, a snr.propensity.score event is saved in the profiles of each customer in the audience. The event data includes detailed results of the prediction.
Based on the snr.propensity.score event, you can create segmentations of customers with different propensity and use those segmentations as campaign targets:
Email, SMS, web push and mobile push can be sent manually or you can launch them by using the Automation module.
Check the use case set up on the Synerise Demo workspace
You can check the configuration of the Propensity prediction directly in Synerise Demo workspace.
If you don’t have access to the Synerise Demo workspace, please leave your contact details in this form, and our representative will contact you shortly.
