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Original Article Classifying customers on the basis of their attitudes towards telemarketing Received (in revised form): 13th July 2009 Ankit Mehrotra is a full-time faculty member at Jaipuria Institute of Management, Lucknow in the area of Information Technology. With a PhD from the University of Lucknow in the area of Supply Chain Management and Information Technology, his teaching career spans over 8 years. His areas of interest include Data Mining, MIS and Spreadsheet Application in Business and Logistics and Supply Chain Management. He has authored articles on Logistics, Supply Chain Management and Information Technology. He has been part of various MDPs, and has covered usage and penetration of Information Technology under various topics. Reeti Agarwal is a full-time faculty member in the area of Marketing at Jaipuria Institute of Management, Lucknow. With a PhD from the University of Lucknow in the area of Consumer Behaviour, her teaching career spans over 9 years. Her areas of interest include CRM, Services Marketing, Retailing and Effective Communication Skills. Extensively involved in research, she has authored articles on CRM, Retailing and Household Buying Decision Making. She regularly conducts MDPs in the area of Interpersonal Communication Skills, Building Customer Relationship and so on. ABSTRACT Telemarketing belongs to a new breed of potent technology-driven business tools that have evolved in direct response to the changes in today’s business environment. Being rooted in a technological foundation, telemarketing offers flexibility, and simultaneously lowers the costs of reaching customers and meeting their needs. Compared to traditional marketing approaches, the telemarketing approach has been designed and developed for the contemporary business environment. Despite its advantages, focussing too much on this technology-driven approach without understanding customers’ attitudes and preferences for such an approach can lead to disastrous results for an organization. The article argues that telemarketing practices ought to be managed in accordance with customers’ attitudes towards such practices. The objective of the article is to use intelligent techniques such as Feature Selection and Classification and Regression Techniques (C&RT) to classify customers according to their positive or negative attitudes towards telemarketing. The model thus arrived at may be used to better understand customer attitudes and accordingly target telemarketing efforts more successfully. Significant determining variables that can help capture acceptance or non-acceptance of telemarketing channels by customers were identified from the literature and focused group discussion. Likert scale responses were collected from a sample of 400 respondents using a structured questionnaire. The application of Feature Selection and C&RT resulted in the identification of two segments of customers: Acceptors and Rejecters. The findings also show that customers view telemarketing as an approach used by companies to sell their products ‘any which way’, with lack of concern for customers’ choices and comfort. This study, by building a model to classify customers according to their positive or negative attitudes towards telemarketing, helps in reducing this disconnect between customers and the telemarketing approach being adopted by organizations. Journal ofTargeting, Measurement and Analysis for Marketing (2009) 17, 171– 193. doi:10.1057/jt.2009.14; published online 17 August 2009 Correspondence: Ankit Mehrotra Keywords: telemarketing; privacy; customer Jaipuria Institute of Management, Vineet Khand, attitude; classification and regression tree Gomti Nagar, Lucknow 226010, India E-mail: ankitmeh@hotmail.com (C&RT); feature selection; data mining © 2009 Palgrave Macmillan 0967-3237 Journal of Targeting, Measurement and Analysis for Marketing Vol. 17, 3, 171–193 www.palgrave-journals.com/jt/
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Mehrotra and Agarwal INTRODUCTION Effective telemarketing requires high quality Telemarketing is an interactive process between customer data, clustering capabilities and a company and its customers that uses a explainable outcomes that provide action items comprehensive system of media and methods to for strategy and testing. Technology, particularly elicit a response.1 It is the art and science of in the form of intelligent techniques such as data getting the right offer, to the right people, at mining, is increasingly being used by companies the right time, and recording and fulfilling their to understand their customers better and request for products or services. Telemarketing consequently to serve them better. Data mining is is used in a variety of industries, including the process of sorting through large amounts of Telecommunications, Banking/Financial Services, data and picking out relevant information. It is Insurance, Mail Order/Catalogues, Travel and usually used by business intelligence organizations, Tourism, Charity/Non-Profits and Publishing.2 and financial analysts, but is increasingly being Telemarketing is a more dominant method of used in areas of marketing to better serve direct marketing being used by companies to customers and also to find ways to increase reach out to customers in which contact between profits for the company. Data mining techniques customers and salespersons is established via the contribute significantly to building better medium of telephone. There are two main customer relationship by better understanding types of telemarketing – inbound and outbound. customers and their likes and dislikes. For Inbound telemarketing is when the customer example, data mining helps a company in finding gets in contact with the company through prospects having a high likelihood of responding telephone for the purpose of making complaints, to an offer and accordingly optimizing campaign obtaining information, placing orders and so on. management to reduce the expenses for such a In contrast, outbound telemarketing is when the process incurred by the organization. Thus, data company initiates contact with the customer to mining techniques are increasingly being used by sell a product, to conduct market research and companies to predict response rates, to estimate so on.3 The telephone as a medium is ideal for market size, customer life-time value and return building and maintaining close relationships on investment (ROI), and to classify customers with customers.4,5 Technological advances in into segments.10 this area provide an opportunity for more This article makes use of two intelligent personalized, even distinctively new, forms of techniques – Feature selection and Classification customer relationships.6,7 Yet, in-depth analyses and Regression Techniques (C&RT) – to of telephone interaction from a customer’s identify the important attitudinal factors affecting perspective manner are exceptionally rare. In fact, customers’ responses to telemarketing offers and it is hard to find empirical analyses of telephone to classify customers according to their positive interaction from a customer’s perspective even or negative attitudes towards telemarketing in terms of basic marketing concepts such as as a channel of marketing. The resultant perceived value, quality and satisfaction. There model helps in classifying customers, and an have been virtually no attempts to investigate understanding of the resultant classes would how consumers define and evaluate telephone make it easier for companies to deduce which interaction in terms of these concepts and their class should be targeted or avoided in their corresponding dimensions. Telephone interaction marketing efforts. with customers managed through call centres This article begins with a discussion of the is still much too internally focused and cost/ theoretical background of the study. The production-oriented, and hence does not respond following sections present, successively, the to growing privacy concerns and cynicism objectives of the study, research design, sample towards direct marketing practices and declining of the study, analysis of research findings, and co-operation of respondents in telephone conclusion and implications, and the article surveys.8,9 ends with the limitations of the study. 172 © 2009 Palgrave Macmillan 0967-3237 Journal of Targeting, Measurement and Analysis for Marketing Vol. 17, 3, 171–193
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Classifying customers on the basis of their attitudes towards telemarketing THEORETICAL BACKGROUND direct marketing. Overall, the level of concern As consumers become increasingly pressed for for privacy was not high based on the Argentine time and overburdened with choices, convincing sample (11 per cent), compared to 46 per cent them to purchase a marketer’s products or of the US respondents in the Equifax Consumer services is subsequently becoming more difficult. Privacy Survey.14,15 However, there are statistically Thus, one of the most valuable avenues for significant differences in the overall concern marketers today is direct marketing, especially for privacy based on demographic factors: age telemarketing, which provides easy access and was a significant predictor of attitudes towards communication with consumers, allowing privacy, indicating that young people are the companies to reach customers whenever they least concerned; following age was the level of want and wherever they want.11 education: respondents with the least and the most education are most concerned about the Comparative studies on direct protection of privacy; last was the level of marketing income: higher-income earning participants are Most studies on consumers’ attitudes towards slightly more concerned about privacy than those direct marketing have sampled US consumers.12–15 at lower-income levels. These studies have generally focused on direct In their 1997 study, the Japan Direct Marketing marketing techniques and general attitudes Association18 found that 62.5 per cent of the towards marketing, privacy and direct marketing. total respondents answered yes to the statement There are only a few researches on attitudes ‘I feel my privacy is invaded if I receive direct towards direct marketing among consumers mail from unknown marketers’. However, only outside the United States. Maynard and Taylor16 11.8 per cent of the respondents felt that their conducted a study that compared American privacy was invaded by receiving catalogues from and Japanese consumers’ attitudes towards direct direct marketers from whom they had previously marketing. The results showed that Japanese purchased. In addition, 11.2 per cent of the and American respondents have similar levels total respondents conceded that they had prior of ambivalence towards direct marketing. experience with privacy invasion in direct However, attitudes towards telemarketing were marketing.18 more negative in Japan than they were in the Trust and privacy issues pose a significant United States. Milne et al17 investigated the barrier to e-commerce in the Greater China acceptability of target marketing, defined as region. Cheskin Research (US) and Chinadotcom gathering background and purchase information Corporation19 conducted an online survey in on consumers in order to better serve them. In 2000 to gain an understanding of Chinese contrast to the United States, where 67 per cent Internet population in Greater China (including found this behaviour acceptable, only 16 per cent Mainland China, Hong Kong and Taiwan.). This of the Argentine sample found this acceptable. study also received data from North American Their results also showed that the amount of Chinese respondents, which formed the basis experience with direct marketing did not affect for a comparison with their Greater Chinese the attitudes towards target marketing. counterparts. The survey was divided into the Maynard and Taylor16 found that the Japanese following categories: (1) attitudinal profile, participants in their study were more concerned including perceived barriers, advantages of online about privacy issues than their American use, trust and privacy issues; (2) behavioural counterparts. The Japanese were less tolerant profile, including online activities, services and of the practice of marketers sharing information purchase activity; and (3) demographic profile. about their age and purchasing habits. Milne They found that the respondents worry about et al17 investigated how consumers from different identity risk and how their personal information countries and cultures (Argentina versus United might be handled by a website. They are States) feel about consumer privacy issues and reluctant to use a credit card to purchase online, © 2009 Palgrave Macmillan 0967-3237 Journal of Targeting, Measurement and Analysis for Marketing Vol. 17, 3, 171–193 173
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