Create a new Model

The Model Builder is the heart of the Predictions Platform. It is an immensely powerful tool, that can help you create Predictions for your Campaigns, and refine them with time and data.

To simplify the Process of Creating a new Data Model, CrossEngage Predictions Platform offers 4 Template Models that can be configured with just a few clicks, without the need of any Machine Learning knowledge.

To Create a new Model, go to the Model Builder Tab, and Click on the Create Model button. Next, choose one of the existing Model Templates, or choose User-Defined Model to configure the model yourself.

Customer Lifetime Value

Customer lifetime value (CLV) is the total worth of a customer over the entire duration of their relationship with a business. It is a measurement of how valuable a customer is to your company, not just on a purchase-by-purchase basis but across the whole relationship.

It is important to understand the Value of your Customers, as it helps you make better business decisions, such as which customers to invest costly Print Campaigns for. With Customer Acquisition Costs rising across the board, predicting the Value a Customer will return in their lifetime can maximise profits while cutting costs.

Classic Re-activation

A Customer Re-activation Model targets customer who have made purchases in the past, but have been inactive since. In a "Classic" Re-activation model, Inactive Customers are identified as those who have not made a purchase in a fixed amount of time. This time period will largely depend on the nature of your Business.

In a Classic Re-activation Model, we follow the same procedure as a CLV model, with the exception of a Custom Filter added by CrossEngage to identify Inactive Customers.

Re-Activation based on IPT

IPT stands for Individual Purchase Interval. This type of Model takes into account that different Customers have their individual purchase patterns. Hence, while the Classic Re-activation model gives a fixed definition of Inactive Customer (e.g those who haven't made a purchase for 4 or 6 weeks), IPT-Based Model identifies purchase frequency of all customers, and targets Customers those who have been inactive recently, compared to their own usual purchase frequency.


With a 1st-To-2nd-Order Model, the target group is restricted to one-time buyers in addition to the information from the CLV model. This can be valuable if you have a large number of One-Time Buyers, whom you wish to turn into Repeat Customers.

Configure the Model

  • After selecting a type of Model in the Model Builder, click on "Proceed to Model Builder".

  • In Basic Configuration, it is necessary to answer questions (1), (4) and (5). Other options can be used to further refine the model, or left blank to be set as default.

  • Provide the time-offset for your data. The time offset is the time between the most recent transaction data available on the Predictions Platform and the start of the campaign. The time offset ensures that process times that are necessary (e.g. address printing) are taken into account in the model.

  • The forecast period defines the future period for which a forecast of the purchase probability and the expected turnover should be created.

  • Configure other options as needed. You can also leave them blank to be set as default.

  • Click 'Save'.

Your new Model is ready. It should reflect a Status of 'New'. You can submit the Model for Calculation by clicking the button on the right. Note that once a Model is calculated, it can no longer be edited.

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