Adding a filter to your marketing message allows you to send to a segment of the list who is most interested in the content of the message. Listrak enables you to group your list based on many different criteria.
One of these filter types is Predictive Analytics, which allows you to leverage what actions a contact may take in the future. Explore the additional filter types that can be used to group your list.
Listrak's Predictive Analytics allows you to group contacts based on two different types of predictions:
Likelihood to Open an Email: A measure of the likelihood that a customer has to open an email.
Likelihood to Click an Email: A measure of the likelihood that a customer has to click through a link in an email.
Likelihood to Unsubscribe from Email: A measure of the likelihood that a customer has of unsubscribing from your email list.
Predicted Lifetime Value: A calculation representing the amount a customer is likely to spend with your brand in the next 365 days.
Likelihood to Purchase: A measure of the likelihood that a customer has of making a purchase.
Coupon Affinity: Groups customers by the chance that they will use a coupon when making a purchase. Passing coupon information in the orders file is required to identify a buyer's coupon affinity.
Discount Affinity: Groups customers by the chance that they will purchase an item using a discount. Passing discount information in the orders file is required to identify a buyer's discount affinity.
Life Cycle Stage: A measure of a customer's position in their purchase life cycle.
TYPES OF CLASSIFICATIONS
Predictive models allow you to break down your customer list in a few different ways. The Likelihood criteria breaks down each contact's list into four different groupings. Affinity criteria indicate the strength of a relationship. The Life Cycle Stage criteria classifies a contact based on where an individual customer is in their life cycle.
Likelihood classifications are based on comparing a specific contact's behavior to the average contact's behavior for a list or merchant. Likelihood classifications are available for Predicted Engagement models: Open, Click, Unsubscribe, and Purchase.
All likelihood models measure the chance that a given behavior will occur in the next 14 days.
Most Likely: Identifies contacts who are two times or more likely to complete a specific action.
More Likely: Identifies contacts who are more likely than the average customer and less than two times more likely to complete a specific action.
Less Likely: Identifies contacts who have between a 0.5 - 1x likelihood to complete a specific action.
Least Likely: Identifies contacts who have less than a 0.5x likelihood to complete a specific action.
PREDICTED LIFETIME VALUE
Predicted Lifetime Value: A measure of the potential revenue a customer will generate for your brand in the next 12 months.
Affinity models identify the strength of a relationship a customer has with a purchase motivator. Affinity grouping are available for Coupon and Discount motivators.
When a customer is counted as using a coupon, it means Listrak can identify the specific coupon that was applied to a customer's order. A discount is counted when Listrak receives information, such as a merchandise discount, that shows a customer spent less than the list price for a product.
Coupon/Discount Buyer: 100% of purchases made using a coupon or discount.
Coupon/Discount Preferred: 50 - 100% of purchases made using a coupon or discount.
No Preference: 25 - 50% of purchases made using a coupon or discount.
Full-Price Buyer: Less than 25% of purchases made at a discount.
Non-Coupon Buyer: Less than 25% of purchases made using a coupon.
LIFE CYCLE STAGES
Listrak uses purchase behavior to identify the length of an individual customer's life cycle, which is then used to measure a contact's likelihood to churn. If information is not available to identify a customized customer life cycle, Listrak uses the life cycle of the average customer until enough information is available to create a customized version. The length of a customer's life cycle will vary based on their purchase habits.
Active: Identifies customers who have made a recent purchase and are in the first half of their life cycle.
At Risk: Identifies customers who have not made a recent purchase and are in the second half of their life cycle.
Churned: Identifies customers who have not purchased within their expected life cycle.
Has Not Purchased: Identifies non-customers who do no have a life cycle stage because they have not made a purchase.
ADDING FILTERS TO YOUR MARKETING MESSAGES
Predictive filter criteria can be used in Segment Filter 2.0 to build Segments or apply message-level filtering, as well as anywhere the legacy filtering system is available in the Platform, including message-level filtering, split test filtering, on the contacts menu, and in Listrak Conductor conversations.
Follow the steps below to create Segments in Segment Filter 2.0
1. Navigate to the Authoring Page and the New Filter section.
2. Select One-Time Filter.
3. Then Add Filter.
4. In the criteria section, select Predictive Analytics - Purchase Likelihood to Purchase.
5. Select a merchant, if necessary.
6. Next, select if you would like target a contact who is or is not a part of the Likelihood to Purchase Model
7. Then, select the specific groupings of contacts.
NOTE: You can select multiple groups
8. Apply any additional criteria based on your filter goal.
9. Click Apply Filter.
Congratulations! Now you can add predictive filtering to your segmentation and filtering strategy. Check out Strategic Campaigns and Predictive Filters for some ideas on how to incorporate it into your strategy.