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Wallet prediction by using best benchmark
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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

Wallet prediction by using best benchmark


International Conference on Big Data Analysis and Data Mining

May 04-05, 2015 Kentucky, USA

Yuhui Yao

Scientific Tracks Abstracts: J Comput Sci Syst Biol

Abstract :

In most of organizations, sales quota and customer value focus on historical bookings. It is useful for customer retention but fewer insights to do customer acquisition and cross sell. Therefore customer wallet estimation becomes important if we want to know the true upside potential. There are some ways have been explored to size the customer value but facing challenge for scalable or actionable. Wallet Prediction by Using Best Benchmark is a novel methodology that estimates wallet potential by using key factor analysis, experimental design and linear/non-linear fit. The estimation also simulates the real selling process and business rules, which is close to business and easy for sales people to understand. Based on the estimated wallet potential and historical bookings, a new strategic RAD customer segmentation was also created to understand different landscape of different customers. By adding customized sales and marketing elements and programs, the deployment of the new customer segmentation has successfully gained $100M incremental revenue.

Biography :

Yuhui Yao has completed his PhD from Singapore Nanyang Technological University. He has published 10 papers and 14 years data analytics working experience in UOB, IBM, Cisco, Autodesk based in Singapore, and PingAn based in Shanghai. Currently he is the Deputy General Manager of Database Marketing department in PingAn Direct.

Google Scholar citation report
Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

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