8.1 Objectives of the analysis
This chapter is concerned with data mining methods for customer satisfaction analysis. Customer satisfaction is a measure of how the products and services supplied by a company match customer expectations. To enable it to be measured statistically, customer satisfaction must be translated into a number of measurable indicators, directly linked to factors that can be understood and influenced. For more details, see Siskos et al. (1998), Cassel (2000), Cassel and Ekl¨of (2001), Casselet al. (2002) and S¨arndal and Lundstr¨om(2005).
Satisfaction is a somewhat vague concept, but it can be measured by simply asking a series of questions. A customer may be completely satisfied with the quality of a service, not satisfied at all, or somewhere in between. We can take ‘not satisfied at all’ and ‘completely satisfied’ as fixed endpoints of an ordinal variable and then we have to decide how many points there should be in between. It would be ideal if satisfaction could be measured on a continuous scale. But for obvious reasons this is impossible and we have to compromise. The scale should be such that it allows the customer enough flexibility to accurately express an opinion.
For example, the customer may be asked to indicate which of the following best describes his or her views: 1, very unsatisfied; 2, moderately unsatisfied;
3, neutral; 4, moderately satisfied; 5, very satisfied. Questions presented in this way are scored on a five-point scale. Overall a questionnaire will contain some 30– 40 questions about the customer’s satisfaction with different aspects of the service. There should also be some background variables on the customer that will make it possible to do a more detailed analysis.
To estimate customer satisfaction descriptive statistical methods are typically used. The recent literature suggests comparing statistical models for customer sat-isfaction in terms of predictive performance. Guidelines provided by international quality organizations such as the European Foundation for Quality Management (EFQM), the European Quality Organisation (EOQ) and national quality organi-sations suggests using structures of latent variables.
Applied Data Mining for Business and Industry, Second Edition Paolo Giudici and Silvia Figini
© 2009 John Wiley & Sons, Ltd. ISBN: 978-0-470-05886-2
8.2 Description of the data
The data set analysed in this chapter comes from the ABC 2004 annual customer satisfaction survey. The survey was carried out by KPA Ltd., an independent consulting firm partner of the European Musing project (www.musing.eu). ABC, a software house (whose name has been changed to protect its identity), wished to measure customer satisfaction on the part of its customers. It collected infor-mation on:
• overall satisfaction levels;
• equipment (e.g. ‘Improvements and upgrades provide value’);
• sales support (e.g. ‘Sales personnel respond promptly to requests’);
• technical support (e.g. ‘Technical support is available when needed’
and ‘The technical staff is well informed about the latest equipment updates/enhancements’);
• training (e.g. ‘The trainers are knowledgeable about the equipment’ and ‘The trainers are effective communicators’);
• supplies and media (e.g. ‘ABC branded performance meets your expecta-tions’);
• pre-press/workflow and post-press solutions (e.g. ‘Capabilities and features of tools meet your needs’);
• customer portal (My ABC) (e.g. ‘The portal’s resources are helpful’);
• administrative support;
• terms, conditions, and pricing (e.g. ‘Equipment and service contract terms are clear’);
• site planning and installation (e.g. Equipment worked properly after installa-tion);
• overall satisfaction with competitors.
There were 81 questions in total; in most cases the level of satisfaction is mea-sured on a five-point scale from very low satisfaction (1) to very high satisfaction (5). The qualitative variables derived are thus qualitative and ordinal. A total of 261 customers eventually took part in the questionnaire.
8.3 Exploratory data analysis
Most of the items in the questionnaire take the form of a statement describing the customer’s experience with ABC during 2004. The person filling in the question-naire also gives his or her title or position, the company’s geographical location, and the length in years of its relationship with ABC.
The first part of the questionnaire deals with ‘Overall satisfaction’. There are four questions to be assessed on a five-point scale, and one to be answered
‘yes’ or ‘no’ which asks whether ABC is the respondent’s best supplier. Two of the questions imply a comparison with other companies, one asking whether the customer would buy a given product from ABC rather than someone else,
asking whether the customer would recommend ABC to other companies; these are scored on a five-point scale from very unlikely to very likely.
Then there are blocks of questions on equipment, sales support, technical sup-port, training, supplies and media, pre-press/workflow and post-press solutions, customer portal, administrative support, terms, conditions, and pricing, site plan-ning and installation, and overall satisfaction with other ABC’s competitors. The customer marks his or her level of agreement with statement on a five-point scale from 1 (strongly disagree) to 5 (strongly agree), and then assesses the level of importance of the statement on a three-point scale (1, low; 2, medium; or 3, high). Any statement that is not relevant or not applicable can be marked N/A.
After a descriptive data analysis phase during which Questions 68– 81 (on overall satisfaction with competitors) are deleted, we have a data set consisting of 67 variables on 240 customers. We give a short summary of the exploratory analysis.
Concerning overall satisfaction with ABC, only 91 customers consider ABC their best supplier. The results of Question 11, which measures overall satisfaction with the equipment, are shown in Figure 8.1: 54% of the customers report high satisfaction and 28% medium level of satisfaction. Figure 8.2 shows the overall satisfaction with sales support (Question 17): only a few customers (33) are very highly satisfied. On the other hand, as far as technical support is concerned, 99 customers are highly satisfied and 68 very highly satisfied. The overall satisfaction with ABC’s supplies and media is medium, and with workflow solutions very high. There is a high overall satisfaction with the administrative support and a medium level of satisfaction with terms, conditions and pricing. Regarding overall satisfaction with overall solutions with the customer portal, site planning and installation, much of the data is missing (the number of non-responses is very high).
Statistics on customer seniority and country location are reported in Figures 8.3 and 8.4. Germany accounts for 44% of the customers. Only a small percentage of the customers are located in France and Israel. In terms of customer seniority (i.e. the length of the relationship between ABC and the customer), we observe a quite high percentage of old and new customers, but a dip in the number of
Very low 2% Low
7%
Medium 28%
High 54%
Very high 6%
No answer 3%
Figure 8.1 Overall satisfaction with equipment (Question 11).
Very low
8% Low
15%
Medium 28%
High 29%
Very high 14%
No answer 6%
Figure 8.2 Overall satisfaction with sales support (Question 17).
17.92%
24.58%
17.08%
13.33%
27.08%
1 2 3 4 5
Customers
Years
Figure 8.3 Customer seniority.
Benelux 10%
France 5%
Germany 44%
Israel 9%
Italy 14%
UK 18%
Figure 8.4 Customer location.