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Cross selling campaigns aim at selling additional products to existing customers. 
A cross selling model estimates the propensity to uptake an add-on product for each scored customer.

A cross selling model can be built on the results of a test campaign to analyze respondents and identify customers with increased purchase potentials.

An easier approach which does not require the running of a test campaign, is to analyze the profile of customers who acquired the product of interest in the recent past. Here are a couple of examples based on the latter approach:

Banking: Cross-selling an Investment product to Savings’ customers.
  • Modeling population: all active customers not owning the investment product at H (end of the historical period). 
  • Target population: those that acquired the product at T (end of the event outcome period). 
  • Scoring population: all active customers not owning the product at present.
Mobile telephony: Cross-selling a telephony service, e.g. Internet usage
  • Modeling population: all active customers not using the service before H (no traffic before H). 
  • Target population: those that used the product at T (at least some traffic between H and T). 
  • Scoring population: all active customers not using the service now. 

 

 

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Tags: CRM, analytics, cross-selling, data, mining, modeling

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Comment by Anit Anit on June 29, 2016 at 4:57am

Where is "now" in the time line? is it the same as "H"

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