Timeline event rollups enable a range of CDP use cases that employ time-based segmentation.
These use case examples illustrate how you can use timeline rollups to extend or enrich your existing BlueConic CDP use cases.
Segmentation
Roll up timeline event data - such as orders, or other timeline events - to profile properties and create new dynamic customer segments.
Suppression use case: Exclude customers from an email re-engagement campaign if they have ordered between April 1 and April 30 this year.
Abandoned cart use case: Send email to customers who have abandoned a shopping cart between April 1 and April 7.
Order-based use case: Create a segment of customers who have placed more than 6 orders between January 1 and June 30 this year. Example use case: Aggregating order data with timeline event rollups
Fine-tune your campaigns: Exclude profiles from a campaign if they have ordered during the month of May.
Suppression use case: Send no more than 5 emails or push notifications per week across all ESPs.
Reporting
Use timeline event rollups to create better reports on profile activities.
Gain insight into average order values.
Measure customer loyalty based on purchase, page views, email clicks, etc.
Augment your business intelligence reports with timely order and purchasing statistics for customer segments.
Find the top shipment date of orders for certain products in the month of March.
Exporting data
Show the total order value in an email to explain to the customer why they get a certain loyalty discount reward.
Create customer audiences based on recent orders.
Export rolled up data to external systems that rely on this information using BlueConic Connections.
AI and Machine Learning
Enable machine learning feature engineering by supporting the data aggregation needed to train ML models.
Train ML models that make predictions based on customer spending, total order spending, total emails sent, total emails opened, etc.
Roll up data for a next-best channel model using:
Total number of emails opened
Total number of emails clicked
Total number of push messages sent
Total number of push messages opened
For a model that predicts propsensity to churn/subscribe, roll up data for:
Number of times a subscriber consumes premium content
Number of report downloads
Number of visits to account benefits page
Number of views of dialogues promoting account benefits page
Number of renewal page views
Number of visits
Number of free newsletter clicks
Learn more about AI Workbench for applying AI and machine learning models to your first-party data.