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Customer & Prospect Value Estimation

A leading telephone operator needed to estimate the value of prospects and Upselling potential for small and medium-sized enterprise customers. Softlab, utilizing SAS Base and R technology, integrated operator data with external sources to develop two models for forecasting prospective customer value and evaluating Upselling potential. The analysis identified qualifying characteristics in future new customers, relevant variables, and model development through multivariate regression. Results showed greater precision in assigning regional sales force targets and more focused sales on high-value customers. The results of forecasting prospective customer and Upselling potential had R2 values of 91% and 83%, respectively.

Category:
Data Analytics

Softlab employed two models for forecasting the value of Prospect customers and evaluating the potential of Upselling on the Customer Base. In the first phase, the analysis and knowledge of the customer base identified qualifying characteristics of future new customers, as well as relevant variables. Softlab developed models using multivariate regression and tested and applied them to estimate the potential spending on voice contracts and Mobile Broad Band (MBB) on an individual customer level. Finally, Softlab designed and built a report to share relevant information with stakeholders.

 

The Softlab solution led to an estimated value of the voice contracts with R2 = 91% and the MBB contracts with R2 = 83%. The analysis resulted in greater precision in assigning the target to the sales force at a regional and local level, bringing more focus on sales force on high-value customers.

 

 

 

Softlab utilized SAS Base and R technology to develop models for forecasting prospective customer value and evaluating Upselling potential. Additionally, Softlab integrated operator data with external sources to create the models with high R2 value, leading to precise target assignments for the sales force.