B2B Customer Insight Tool
Automated Data Analytics to improve the Deal Analytics workflow
T.J. Langhout (TU Delft - Electrical Engineering, Mathematics and Computer Science)
S.A.J. van Leeuwen (TU Delft - Electrical Engineering, Mathematics and Computer Science)
C.I. Ort (TU Delft - Electrical Engineering, Mathematics and Computer Science)
W.S. Volkers (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Dick H.J. Epema – Coach (TU Delft - Data-Intensive Systems)
M Kerkhof – Mentor (PwC)
L. Gunneweg – Mentor (PwC)
T. Boevink – Mentor (PwC)
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Abstract
The Deal Analytics group of PricewaterhouseCoopers Amsterdam has requested a tool for automatising the business-to-business customer analysis. This analysis was performed manually, which left room for performance improvement. This report discusses how the a product was developed which automates the analyses After two weeks of initial research, a complete system was designed and implemented in the subsequent nine weeks. The tool consists of two distinct parts: a front-end and a back-end. The front-end allows the user to customise the analysis to its own preferences, and communicates with the back-end to efficiently perform the analysis. With the help of user evaluations, the front-end has been designed such that it is usable by any PwC employee within the Deals branch.The back-end uses data analysis techniques and machine learning to analyse customer behaviour. Strong points and growth opportunities of a company are found using techniques such as customer segmentation, regression analysis, and cross-sell analysis. The product has been tested using a variety of techniques to ensure that the software does not crash on unexpected input. The final product is evaluated based on the requirements, design goals and success criteria set at the start of the project and can be considered successful.