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Predicting Customer Loyalty Using The Internal Transactional Database

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Author Info
W. BUCKINX
G. VERSTRAETEN ()
D. VAN DEN POEL ()

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Abstract

Loyalty and targeting are central topics in Customer Relationship Management. Yet, the information that resides in customer databases only records transactions at a single company, whereby customer loyalty is generally unavailable. In this study, we enrich the customer database with a prediction of a customer's behavioral loyalty such that it can be deployed for targeted marketing actions without the necessity to measure the loyalty of every single customer. To this end, we compare multiple linear regression with two state-of-the-art machine learning techniques (random forests and automatic relevance determination neural networks), and we show that (i) a customer’s behavioral loyalty can be predicted to a reasonable degree using the transactional database, (ii) given that overfitting is controlled for by the variable-selection procedure we propose in this study, a multiple linear regression model significantly outperforms the other models, (iii) the proposed variable-selection procedure has a beneficial impact on the reduction of multicollinearity, and (iv) the most important indicator of behavioral loyalty consists of the variety of products previously purchased.

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Publisher Info
Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 05/324.

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Length: 39 pages
Date of creation: Aug 2005
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Handle: RePEc:rug:rugwps:05/324

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Related research
Keywords: Predictive modeling customer relationship management behavioral loyalty overfitting multicollinearity data enrichment

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  2. M. Vanhoucke & S. Vandevoorde, 2005. "A simulation and evaluation of earned value metrics to forecast the project duration," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/317, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
  3. G. Poels & A. Maes & F. Gailly, 2005. "User Attitudes towards Pattern-Based Enterprise Information Models: A Replicated Experiment with REA Diagrams," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/315, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
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  5. S. Vandevoorde & M. Vanhoucke, 2005. "A Comparison of Different Project Duration Forecasting Methods using Earned Value Metrics," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/312, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
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  7. A. Heirman & B. Clarysse, 2005. "The imprinting effect of initial resources and market strategy on the early growth path of start-Ups," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/310, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
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  9. S. CLAEYS & G. LANINE & K. SCHOORs, 2005. "Bank Supervision Russian Style: Rules vs Enforcement and Tacit Objectives," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/307, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
  10. Vandevoorde, S. & Vanhoucke, M., 2005. "A comparison of different project duration forecasting methods using earned value metrics," Vlerick Leuven Gent Management School Working Paper Series 2005-16, Vlerick Leuven Gent Management School. [Downloadable!]
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