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Propensity based Segment

Predict user behavior and create precise segments with Propensity based segmentation.

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Overview

Propensity segmentation on the Netcore CE Dashboard predicts user behavior, helping you create accurate audience segments. We integrate predictive analytics with segmentation workflows so that you can identify the likelihood of user actions like purchasing, repurchasing, churning, or unsubscribing. This feature simplifies targeting users based on predicted actions, which enables highly personalized campaigns.

Examples

Refer to the given table to learn ways to use propensity-based segmentation.

ExamplesWhat Propensity Model doesUser Impact
Prevent ChurnHelps identifiy users who are likely to churn.Reduce churn by re-engaging them with retention campaigns that offer incentives.
Boost Repurchase RatesHelps target customers with a high likelihood of repurchasing in specific categories.Show customers the products to encourage repeat purchases.
Increase SubscriptionsHelps identify users who are likely to subscribe.Encourage subscriptions by highlighting exclusive rewards or limited-time promotional offers.
Enhance App RetentionHelps identify users who are likely to uninstall the app.Send them notifications, rewards, or exclusive offers to retain them.

Create Propensity Based Segment

  1. Select models from the 15 available in the Account configuration and start using segmentation. Follow the given steps to know more.

Select Propensity Model

Select and Enable Propensity Model(s)

Select and Enable Propensity Model(s)

  1. Navigate to Profile> Account configuration.
  2. Scroll to the Propensity Model section and click Enable.
  3. Click Edit to open the settings window. Use the toggle button to enable or disable the Propensity Model. (Admin access required).
  4. Select up to five models from a dropdown of 15 predictive models. Refer to the given table to know the options here.
Propensity ModelDaysDescription
Repurchase7Predicts if a customer will repurchase within 7 days.
14Predicts if a customer will repurchase within 14 days.
28Predicts if a customer will repurchase within 28 days.
Purchase7Estimates the likelihood of a customer making a purchase in 7 days.
14Estimates the likelihood of a customer making a purchase in 14 days.
28Estimates the likelihood of a customer making a purchase in 28 days.
Churn7Identifies customers at risk of inactivity within 7 days.
14Identifies customers at risk of inactivity within 14 days.
28Identifies customers at risk of inactivity within 28 days.
Uninstall7Predicts the chance of app uninstallation within 7 days.
14Predicts the chance of app uninstallation within 14 days.
28Predicts the chance of app uninstallation within 28 days.
Unsubscribe7Determines if a user is likely to unsubscribe in 7 days.
14Determines if a user is likely to unsubscribe in 14 days.
28Determines if a user is likely to unsubscribe in 28 days.

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Important Points to Remember

  • You need to have Admin access to enable or disable the propensity models.
  • Uninstall and Unsubscribe models are only available if a mobile app is integrated.
  • You can select up to five models at a time.
  • After saving changes, the models will take 12 to 96 hours to appear in segmentation. The CE dashboard admin will receive an email notification once the models are enabled.
  • Once saved, you cannot make changes to the model selection. To modify or add more model(s), contact [email protected] with the specific model name.
  1. Click SAVE CHANGES. After this, the propensities are available in segmentation within 10 to 15 hours.

Create a Predictive Segment

  1. Navigate to the Audience section and select Segments.
  2. Click CREATE SEGMENT to open the segment creation screen.
  3. Click +ADD and follow these steps:
    • Select Predictive as your segmentation type.
    • Under the Propensity section, select a predictive activity, such as Purchase, Repurchase, Unsubscribe, or Churn
    • Select the likelihood (High, Medium, or Low). Refer to the given table to understand the likelihood.
LikelihoodDescription
HighUsers with a strong probability of performing the selected activity within the specified timeframe.
MediumUsers with a moderate likelihood of performing the activity.
LowUsers with a low probability of performing the activity.
    • Select the source. Refer to the given table to understand the sources.
SourceDescription
BrandTargets users on predictive behavior for specific brands.
CategoryTargets users based on their activity within product categories.
ProductsPredicts actions related to individual products.
Across CatalogueConsiders user activity across the entire product catalog.
  • Set the time frame from the dropdown. The options include: 28 days, 14 days, 7 days.
  1. Select the conditions of segmentation as required. Select AND or OR based on your requirements.
  2. To add a block, click ADD BLOCK.
  3. After you have defined all the conditions for your segment, click GET COUNT to check how many users lie in that segment.
  4. Click SAVE to finalize and save your segment.
Create a Predictive Segment

Create a Predictive Segment

Refer to the documentation for more detailed information about segmentation and its various functionalities.

Updated 4 days ago

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