MKF9704

Direct marketing statistics and mathematics

Dr Tim Fry

6 points · One 6-day week module plus 2x1.5 days · Second semester · Caulfield (week module) and (2x1.5 days) · Prerequisite: MKX9702

Objectives Upon completion of this subject students should be able to demonstrate sufficient knowledge and ability of direct marketing mathematics and statistics to permit the sound interrogation of modern direct marketing databases; interrogate direct marketing databases to determine interrelationships and structures that characterise customer profiles and behaviour; assess the marketing significance of the results from these interrogations, and apply that understanding in a competitive environment; forecast the profitability of proposed direct marketing activities. By modelling the market response and estimating characteristic parameter values, students will learn to determine the marketing mix that optimises a firm's profit or other quantitative objective.

Synopsis Introduction to learning resources, one shot mailing analysis, break-even point, sensitivity to response rate, lifetime values, simple club finances, sensitivity to retention, effect of premium values, negative option clubs, return on promotion, review of business statistics, summary of multivariate techniques, data visualisation software and inference, summary of quantitative marketing techniques, model fitting by minimising statistics, generalised response modelling, advertising/promotion dynamics, wealth maximisation, explanatory variables, clustering techniques, experimental testing, sample design and size, segmentation, RFM, tree methods, linear scoring, discrete choice models, advanced techniques, data mining, neural networks.

Assessment Assignments: 55% · Computer examinations: 45%

Prescribed texts

Shepard D and others The new direct marketing 2nd edn, McGraw-Hill, 1995

Back to the 1999 Business and Economics Handbook