Churn and offer take-up prediction

Shopitize logo

Project details

  • Date

     14/10/2015

  • Client

     Shopitize

  • Task

     Churn and offer take-up prediction

  • Category

     Commerce

  • Website

     Visit online

Business challenge

Following research into a number of companies, Shopitize selected Algolytics as their preferred supplier to carry out a predictive modelling test project. The purpose of the project was to construct models in order to predict the probability of churn and offer take-up on Shoptize’s platform.

Solution

The scope of the project included:

  • Building an Analytical Data Mart, so that data became easy to manage in the analytical process,
  • Construction of a recommendation model to select offers most likely to be accepted by customers,
  • Construction of a churn model to calculate the probability that customers will not transact in the given period using behavioral historical data,
  • Analysis of the recommendation and churn models performance.

Algolytics’ AdvancedMiner and AdvancedMiner SNA systems were used during the project.

Results

Algolytics’ predictive models increased the effectiveness in selecting the most probable churners as well as in selecting offers coresponding to customers’ needs.

 

We are extremely happy with the project results and everything we have seen from Algolytics.

 

Shopitize logo

Shopitize is a mobile marketing platform that delivers contextually relevant offers, brand engagements and interactive experiences directly to a shopper’s smartphone.
For leading brand-owners including Kellogg, Danone, Mondelez, United Biscuits and General Mills, Shopitize provides a direct route to deliver retailer-agnostic, paperless marketing and promotions to UK shoppers.

www.shopitize.com


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