Document Name: Resource Manual for Customer Surveys Part 7
Date: 10/01/93
Owner: OMB
Title: Resource Manual for Customer Surveys Part 7

Author: OMB

Date: Oct 1993

Appendix B -- Selected Technical Notes

B.1 Introduction

No general recommendations will be given in this Appendix, except

on focus groups and only then because of the PRA process. One of

the reasons for this is that most of the considerations commented

on will have important dimensions that depend on your unique

circumstances. For example--

- Your existing knowledge of your customers.

- The nature of your product/service delivery.

- How quickly you can modify your agency's approach to


- The degree of satisfaction/dissatisfaction which exists with

what is currently going on.

This list could be much longer, as you will find in your own


While in the end your own thoughtful practice will become your

principal guide, some beginning observations may help in

identifying what to look for and where. A few of these are

provided here with others to be added in later versions of this

manual. In particular, private sector and existing government

applications of customer surveys suggest that special attention

should be paid to --

- How you use focus groups and similar methods (B.2),

- Analysis issues in the use of opinion scales (B.3),

- Complete coverage of your targeted customers (B.4),

- Some other issues which supplement Section 4 (B.5).

One of the best ways you may find to deal with these and other

issues that may be unique to your agency is to set aside

resources that will allow you to continuously improve the

measurement process.

B.2 Focus Groups and the PRA

One of the first tasks in developing useful customer surveys is

to determine what the customer perceives to be the important

service or product attributes. Focus groups can be a valuable

tool for eliciting this customer perspective and are widely used

for this purpose in both government and the private sector.

Focus groups fall within the coverage of the Paperwork Reduction

Act and require OMB clearance, but a program of focus groups is a

prime candidate for "generic" clearances described in Section 5.

Focus groups require planning, effort, and resources, just like

any other research method. They involve a recruitment process, a

"script" comprising the questions to be addressed by the group,

and one or more "moderators" to facilitate the participation of

all members of the group and keep the responses focussed on the

target issues. The information collected in a focus group

includes a verbatim record of the discussion (often a video tape)

and may also include comments and analysis. Both the recruitment

and analysis stages are generally time-consuming efforts.

Focus groups sponsored by Federal agencies often involve more

highly selective recruitment than is the norm for private sector

focus groups. Vendors of such services should be advised to

allow for higher recruitment costs (more telephone contacts per

successful recruitment) when this is the case.

Since the success of focus groups depends on full and willing

participation, vendors should be discouraged from using more

aggressive recruitment practices (e.g., "hard sell" or special

incentives) to bring in marginal participants. While OMB rules

restrict the use of cash incentives generally, payments of up to

$25 per participant have been routinely approved as an allowance

for the estimated "out-of-pocket" costs (transportation, child

care, etc.) of a focus group.

Well-trained moderators contribute substantially to the value of

a focus group. The "script" or moderator's guide should clearly

lay out the questions (and follow-up issues to be addressed by

the group). A clear statement of the purposes of the focus

group(s) is also needed to guide the moderator and for the PRA

review process.

In some circumstances formal focus groups may not be needed. For

clients who are both sophisticated and articulate, less formal

approaches (a less structured meeting or group discussion) may

serve very well to elicit customer opinions. These informal

opportunities for customer input require the same attention to

issues and careful selection of participants as are needed for

focus groups but they do not require PRA review.

Other techniques that have been used successfully to explore

customer perceptions are analysis of customer complaints,

"suggestion" boxes, and "mystery shopper" studies (where a person

poses as a client to observe how a service is delivered). The

"mystery shopper" approach was used to identify problems in the

IRS taxpayer assistance program. These other methods also do not

require PRA review and may offer quick and cost effective options

for identifying customer problems in some cases.

While focus groups can be very useful for exploring, specifying,

and understanding customer concerns, they are not useful for

generalization (e.g., quantitative measurements or comparisons).

Focus groups are almost never representative of the entire

customer base.

B.3 Opinion Scales

One of the important tasks in quantifying satisfaction or

dissatisfaction is selecting the measurement scale(s) you will

use. Now this is a very large subject but perhaps an

illustration of some of the issues will be of assistance.

A common strategy, for example, is to present questions about

important aspects of service with Likert scales for responses

(e.g., from "very satisfied" to "very dissatisfied" in some

number of steps.) When numbers are placed on such scales then the

means and variances computed on them do not necessarily have the

same properties as on continuous variables, e.g., age or income.

(One solution might be to use categorical data analysis


The use of ordinal scales has other implications as well.

For example, satisfaction is often viewed as a difference

between expectations and perceived performance, but the use of

an arithmetic difference between two opinion scores as a

measure of satisfaction has raised both conceptual and

statistical controversies in the literature.

Such issues suggest how measurement decisions and analytical

objectives are intertwined. Empirical methods and approaches

have provided means to address problems that cannot be resolved

within classical (mathematical) measurement theory.

In the example above, empirical results indicate that

responses couched in terms of satisfaction may already be

referenced to some implicit concept of expectations held by

the respondent. This, in turn, suggests using this natural

tendency by indicating some explicit reference point (e.g.,

"service that fully meets your needs").

Empirical results abound in the literature concerning opinion

scales and some scale properties are almost always estimated

empirically. Clearly, your judgement, and not some mechanical

manipulation of "the numbers," will be crucial. The bibliography

may help. Consultants are available (see Section 6). Workshops

are also planned (see Section 7).

B.4 Representativeness of the Customer Survey

Representativeness requires good frame construction and careful,

probability-based sample selection. Getting a good response rate

is crucial too.

The risk of significant nonresponse bias (the answers of

nonrespondents would have been different from those who

responded) increases with the amount of nonresponse. Indeed, the

technical consequences of inadequate response, when superimposed

on the other difficulties inherent in customer surveys can

seriously undermine the usefulness of your analyses.

The issues here have both a philosophical and a technical

dimension. Chapter 2 ("Putting Customers First") of the Report

of the National Performance Review states the philosophical


"We will ensure that all customers have a voice, and that

every voice is heard."

This principle calls for survey designs that make participation

convenient, simple, and free of unnecessary burden or perceived

threats -- in short, the kind of designs that generally produce

high response rates. One caution, however; some techniques

(e.g., incentives and aggressive follow-up) have been shown to

affect the respondent's attitudes toward the sponsoring agency.

(See bibliography).

In surveying customer opinions, we are not so much interested in

where the mean of the distribution lies, but in determining

accurately what portion of the customer population is highly

satisfied or highly dissatisfied (and why.) Nonresponse can be

particularly damaging in interpreting such surveys. For example,

it is not uncommon that the respondents may be either more or

less homogeneous than the full population -- both phenomena have

been observed in different settings. What will happen in your

situation cannot be predicted; however, you should be on the

lookout for this kind of distortion of the distribution.

B.5 Some Other Issues

Customer satisfaction needs to be thought of as multi-

dimensional. For example, much of the usefulness of a survey of

customers may come from the specificity of the insights provided

on agency practice. As already noted in Section 4, on a technical

level, multiple measures should help in reducing the inherently

greater uncertainties in opinion data.

Whatever choices you make, the scales used for opinion research

may set some practical bounds on the precision that can be

achieved and the types of analysis that can be used. Indeed,

opinion results may perform poorly when pressed to measure small

differences or relationships that are not strong. An

understanding of these problems will help avoid overambitious

analytical goals.

Section 3 outlined a step-by-step plan for a single survey design

cycle. It is important to remember that a customer survey is not

an activity to be done just once or once in a while. Much of the

benefit derived from systematically obtaining customer views

depends on a commitment to conduct measurements as frequently as


- Qualitative components of the process should be

repeated periodically to stay in touch with changing

customer perceptions and expectations. This will suggest

revisions to quantitative surveys as well.

- The quantitative surveys themselves need to be repeated

regularly, too, with or without changes in the questions

being used.

Since comparisons over time are an important quantitative

objective of the process, your studies (both qualitative and

quantitative) should include some overlap of new and old designs,

in order to calibrate improved measures against prior measures.

This is a common practice when significant changes are made to

major Federal statistical series, and it is even more important

here -- especially in the early going, when you may still be

learning the best ways for your agency to conduct and use

customer surveys.

Ironically, success in increasing customer satisfaction may lead

to a greater difficulty in measuring that satisfaction.

Technically the shape (e.g., skewness) of the distribution may

change as satisfaction grows; also the relationships (e.g.,

degree of collinearity) among the (multiple) satisfaction

measures may also change (as they all tend to go up together).

As your success increases a carefully designed change in your

measurement scheme can open up new information and rejuvenate the

analytical process.

Appendix C -- Case Studies

(to be supplied as available)

Appendix D -- Contracting for Surveys

Statistical Policy Working Paper #9 (supplied separately)

should be inserted after this page.

NOTE: This document is not available electronically at

this time -- it may be released in this form at

a later date.


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