Customer satisfaction

Customer satisfaction is the most common form of market research in business-to-business markets and is often connected to quality and production measurement, rather than as straight marketing based research.

Before setting up a customer satisfaction programme, it is necessary to ensure that the organisation has the will to actually make changes for improvement, otherwise you will simply be annoying customers by taking their time to collect information, then not doing anything with it.

Quality of Design versus Quality of Delivery

Customer satisfaction has roots in two ideas about quality that come from an operational/production view of the business. The first idea is that quality can be measured by the gap between customers' expectations and their perceptions. This gap-based view of quality says that if you beat customers' expectations you have good quality.

The second idea is that quality is about conformance to a standard or specification. Within this idea is that once the design is set, quality is about ensuring that the end deliverable to the customer meets this design. Consequently from a production/operations point of view, customer satisfaction is about monitoring the quality of delivery of the product and service. The aim being to minimise production errors so saving money and making customers happy (see Quality is Free by Crosby).

These production focused roots of customer satisfaction are sometimes overlooked by the more marketing focused researchers who carry out these type of studies, which can lead to a gap between what you want and what the researcher is providing.

However, experience also shows that design is actually an essential part of customer's overall view of satisfaction and it is not necessarily fully possible to separate out design from delivery. So some care is needed in really defining what it is that you are looking for from a customer satisfaction study, what you are going to use the information for and whether alternative approaches might be better for you.

Samples and customers

The production background to satisfaction also comes into focus when you look at what should be sampled. For statistical quality control of production machines, you take a sample of items that have been produced and test each for conformance.

For customer satisfaction, the equivalent is sampling by product purchased, or for service industries, by service event. However, particularly in business markets, this can cause sampling problems in that a single customer may buy several products or make use of a service several times. If you sample these customers regularly, you are likely to face rapidly diminishing response rates and soon have no data.

The compromise is to take a sample of customers and to ask about their experiences over a certain period of time. Unfortunately for process control, this feedback typically just reflects the average view and will miss any key extremes that are important from an operational view.

For businesses, it is also very likely that you will have a small number of large customers and a large number of small customers. As you are trying to judge quality of delivery, clearly interviews with larger customer are of more importance than smaller customers, yet typically satisfaction is biased toward the views of the many and not the few.

Indeed, it is also likely that the way in which you deliver to your largest customers is different to the way in which you service smaller customers. For instance, an account team, specialist logistics, and custom builds. For this reason we typically advise that a relationship approach  to customer satisfaction such as One-to-One Research.

Scales and measurement

Most customer satisfaction measurement is conducted using a fairly standard 4 or 5 point scales from Very Satisfied, Satisfied, (Neither), Dissatisfied, Very Dissatisfied.

Typically satisfaction is reported as the percentage of customers rating you as either Satisfied or Very Satisfied. Unfortunately, this tends to be quite a crude measurement. Most companies will be scoring around 75-85%. Even poorly performing local government can still easily reach 60%. The maximum we have seen is 92%.

The difficulty is that within such studies is that  year-on-year improvements are very hard to spot. The accuracy of the study often means that changes of 1 or 2% points are within the statistical tolerance of the design and show no real change, yet most companies would struggle to see changes beyond 1-2%.

You then have the second question, which is if you are at 80%, how do you get to 82%? Some clever statistical techniques might show that improving delivery from 60% to 65% say, would improve satisfaction, but then how do you measure and improve delivery?

For these reasons, we favour using attribute and level style approaches (see conjoint analysis) in conjunction with satisfaction measures to get a more actionable set of data, and if pursued fully this leads to techniques such as Quality of Service Review as a mechanism for monitoring customer satisfaction within customer relationships.

A second major factor here, is that satisfaction questionnaires are really about measuring and controlling for dissatisfaction. If you have a satisfied customer then the only thing you need to understand is that they are happy. Many satisfaction surveys fail customers because they ask happy customers lots of irrelevant questions. In a good questionnaire, we measure which standard the service reaches and whether the customer is happy with that standard. If they are not, we then ask for and analyse the reasons for dissatisfaction. Consequently happy customers have a shorter questionnaire and a better questionnaire experience.

For help and advice on carrying out customer satisfaction projects contact info@dobney.com