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.