Audience Opportunities
Use our actionable audience recommendations to create highly impactful marketing campaigns.
Audience Opportunities
- ✓Automatically classify your customers into audiences, updating numbers as new data is entered.
- ✓Our recommendations are based on data models such as RFM, Lifetime Value (CLV), and Funnel Conversion.
- ✓You will also get automatically detected audiences from your E-commerce.
- ✓Understand and activate your opportunities in the Audience Insights module.
RFM model
It is a segmentation technique that allows us to understand the behavior and value of customers based on historical transactional data using three key variables:
- ✓Recency: Time since the customer's last purchase.
- ✓Frequency: Number of purchases made within a specific time period.
- ✓Monetary: Total amount of money a customer has spent on a product or service.
Predictable Media generates 10 audiences based on this model.
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Customer Lifetime Value
Customer Lifetime Value (CLV) represents the monetary value a customer has for a company. Predictable Media's CLV model:
- ✓Allows you to see and compare the lifetime value for all your audiences, for both proposed opportunities and your customized audiences.
- ✓Updates over time, always reflecting changes in the volume and purchasing behavior of each audience.
- ✓Shows change from previous periods, helping to understand how each audience is being made profitable for the business.
Having this metric helps to understand the potential of each audience, allowing you to assess whether it is worth investing in their loyalty or spending on acquiring similar customers.
Conversion funnel
It is a segmentation that categorizes customers, both already-existing and potential, based on their conversion rate. It allows you to:
- ✓Understand the steps from non-customer to best customer
- ✓Create strategic campaigns focused on different stages of conversion
Predictable Media generates 4 audiences based on this model.
E-Commerce opportunities
- ✓Builds automatic audiences based on the number of purchases and abandoned checkouts.
- ✓Detects specific E-Commerce behaviors, such as the use of discount codes.
The number of opportunities generated varies according to the data source.
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