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MFC Spotlight Note

8

Many Microfinance Institutions (MFIs) in the Central and Eastern Europe and the New IndependentStates (CEE and the NIS) region have started to measure client satisfaction and loyalty in order to becomemore client-oriented and improve performance. This information is very useful as MFIs are working inincreasingly competitive environments. As measuring client satisfaction and loyalty is a relatively newundertaking, MFI practitioners usually have to learn from their own mistakes. This Spotlight Note isbased lessons learnt drawn by the Microfinance Centre for CEE and the NIS 2 and its partners from theclient assessment work conducted underImp-Act3 and SEEP Practitioner Learning Programme (PLP)4projects. We intend to facilitate this new task for MFI marketing departments by presenting someprinciples in measuring microfinance client satisfaction and loyalty using a quantitative survey.5

In this paper we present some general marketing research rules as well as new insights specific for themicrofinance industry. We focus on general concepts of satisfaction and loyalty and discuss the potentialresults one can obtain. It is important to note, however, that the list of principles and rules is not meantto be exhaustive.

Dont fall into the satisfaction trap. It appears from the research studies that 60 to 80 per cent ofclients who switched their supplier would have declared they were very satisfied just before leaving(Reichheld 1996). Client satisfaction is indicative of the degree to which services and products satisfyclients preferences. However, satisfaction is not a static idea and it changes as soon as a client findsa better deal and along over-time- raising client expectations.

It is client loyalty that counts. Satisfaction doesnt indicate a clients emotional connectedness,commitment to the institution, which means that a satisfied client is not necessarily a loyal client.A loyal clients commitment can be verified through client behaviour and attitude. A committed clientrecommends the institutions to relatives or friends, decides to travel a little bit further than necessary touse one service and not another or pays a higher interest rate. At the same time a loyal client will believethat their chosen MFI is the best from all the institutions on the market.

Satisfaction and loyalty information can help you improve your programme and develop loyalty-building strategies. Satisfaction is necessary but not sufficient for loyalty. However its measurement ishelpful in detecting dissatisfaction factors that could be disadvantageous and costly for your MFI in thefuture. It will also be helpful in building greater commitment on the part of your clients.

Satisfaction and loyalty studies can enable you to streamline your operations. An appropriatelyconducted satisfaction and loyalty study will provide you with information helpful to prioritise your

1Katarzyna Pawlak and Dorota Szubert work in Research Unit at the Microfinance Centre for Central and Eastern Europe and the New Independent States

(MFC). More information about MFC research work can be found at www.mfc.org.pl/research. The authors are very grateful to Graham A. N. Wright for hiscomments on the first draft.2More information on MFC can be found at www.mfc.org.pl. The brief is based on experience and lessons learnt from the research work conducted in coopera-

tion with partner MFIs: Partner (Bosnia and Herzegovina), Inicjatywa Mikro (Poland), BosVita (Bosnia and Herzegovina), MDF Kamurj (Armenia).3. More information on ImpAct - the Ford Foundation sponsored global action-research programme designed to improve the quality of microfinance services

and their impact on poverty by developing impact assessment systems can be found at http://www.imp-act.org/. More information on the regional work is

available at www.mfc.org.pl/research.4More information on the USAID sponsored SEEP Practitioner Learning Programme can be found at www.seepnetwork.org. More information on the regional

work is available at www.mfc.org.pl/research.5For more information and references on other quantitative methods and techniques see the annex in the end. As the paper focuses on measurement of satisfac-

tion and loyalty, the issue of understanding with regards to these concepts is not discussed here. A reader may find more information on the latter in documents

available at the AIMS http://www.usaidmicro.org/pubs/aims/ and MicroSave www.MicroSave.org websites.

Katarzyna Pawlak and Dorota Szubert1 February 2004

Counting (On) Your Prospective Clients:Guiding Principles in Measuring Microfinance

Client Satisfaction and Loyalty

Client satisfaction

vs loyalty

What purpose does

satisfaction and

loyalty informaion

serve?


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Counting (On) Your Prospective Clients


improvement programme allowing you to achieve better results in a cost effective way leading to betterperformance. You may use the results to prompt product revision and development, improve youroperations and/or inform your strategic and tactical decisions.

Satisfaction and loyalty information does not replace data on impact. Although, keeping satisfiedand loyal client is necessary for achieving impact, the fact that they are satisfied and loyal does notallow to claim it. This is because met client preferences dont necessarily reflect the fulfilment of theirdevelopment needs.

General satisfaction question will not tell you much! As general satisfaction level is a consequenceof the client satisfaction from particular areas of institutional performance, general how are yousatisfied question will not tell you much although will be helpful in further analysis.

If you want to evaluate the forest, look at the trees. It is important to evaluate an institutions performancewith regard to different areas of its operation i.e. product, service, delivery, etc. The 8Ps concept canbe very helpful for unpacking the microfinance product and selecting its detailed characteristics forevaluation.6 Looking at this information will allow you not only to see which areas are better or worseevaluated, but will be also helpful in constructing aggregated indices and calculating overall satisfaction

rating that is more meaningful than a standing alone question on general satisfaction.

Not all performance areas are equally important. There are usually only a few key aspects whichimprovement will lead to increased client satisfaction. The others either increase satisfaction whenpresent but dont harm it when absent. Generally, the more significant the area is found to be, the moreits improvement influences general satisfaction.

Segmentation is key for effective operational use of the satisfaction and loyalty study results. General satisfaction and loyalty rating will not tell you much how to improve and where. Segmentationof satisfaction and loyalty data will help you to determine where improvement is most warranted andwhere it will offer greatest return. Thanks to the segmentation you will be able to identify prospectivegroups among your clients and the priority areas for the improvement action related to the preferencesof those groups.

How much do you need to improve to be the best? You might know your overall rating, but do

you know how well you are really performing, if you lack benchmarks for comparison purposes? Theproblem in microfinance is that it is still new and in many context clients are not financially educatedand have limited knowledge of competitors services. However, this situation is changing and there isincreasing scope for comparing clients responses to the services of different service providers.

Loyalty client attitude and behaviour. To measure client loyalty we need to look at the measuresreflecting his/her behaviour such as depth, length and breadth of loyalty, as well as referrals and intent torepurchase (Churchill, Halpern 2001). Loyalty is a consequence of different aspects, so as in the case ofsatisfaction, a general rating is required that is based on various aspects of behaviour and attitude.

3-D Behaviour: depth, breadth, length of Loyalty. The loyalty depth refers to exclusitivity and isreflected in a share of purchase - the degree to which a customer uses your institution for all her financialservices needs. This may vary according to an institutional type; for example, in credit only institutions,the information requested could be whether a client has any other debts outstanding, or the degree towhich a clients needs for additional money have been satisfied.7 The longevity can be measured by theaverage number of years a client has used your services. The breadth of loyalty reflects the effectivenessof your product cross selling strategies. The more products your client purchases, the more loyal he/sheis likely to be. This measure, however, is not useful in the institutions that dont offer a wider range ofproduct.

Are clients really loyal or do they have no choice? A client may stay with your institution and buy onlyyour products without feeling any loyalty. This could be because they have no choice, are used to yourservice or perceive switching to another service provider to be too costly. Although they demonstrate allthe behaviour of a loyal client, this doesnt mean they are loyal and that tomorrow their behaviour willnot change. Only attitude and behaviour are a true indication of client loyalty.

6The 8Ps stand for people, place, price, promotion, positioning, physical evidence, process, product. More information about the concept can

be found in any marketing related literature (e.g. Kotler 2000); more information about ncept application in microfinance can be found in the

MicroSaves Market Research for Microfinance Handbook.7This information on using other credit sources, although very valuable not only for this purpose, is difficult to obtain as clients have disincentives

to provide accurate information in this regard. That is why its interpretation should be taken with care and cases identified should be considered as

underestimated.

Measurement

basics


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MFC Spotlight Note #8


Secondary behaviour counts. Referrals, endorsements, and spreading the word are examples ofsecondary behaviour that indicate customer loyalty. What is more, they are the most effective promotionaltools in microfinance.8 The way to measure secondary behaviour is to ask about the number of referralsmade in a certain period or whether they would be willing to recommend your organization to theirrelatives and friends. This indicator is also a powerful proxy for high client satisfaction.9

Intent to repurchase is an additional sign of loyalty and can be used as an insight into a clients futurebehaviour. However, since this information does not guarantee the clients behaviour, it should be treatedwith care, especially as clients may feel that admitting they dont want to repurchase may jeopardizefuture opportunities to do so.

Clarify your objectives first. There are many approaches to measuring and understanding client

satisfaction and loyalty so it is important that you choose the one that best suits your needs. First, beclear about what information you are looking for, since this will determine the approach you undertakeand the methodology you choose.If you would like to better understandissues related to satisfaction and loyalty,or have a specific loyalty or satisfaction-related problem to explore, consider usingqualitative methods.If you want representative informationabout the degree of your clients satisfactionand loyalty, about your performancein terms of adjustment of products andservices to the clients preferences and foridentifying areas for improvement, choosea quantitative survey.

Last but not least, if you want quickoperational statistics on an on-goingbasis you will need an easy tool formonitoring satisfaction and loyalty. A fewwell-selected indicators should help youmaintain executional speed and remain affordable, although providing somewhat superficial information.However, satisfaction monitoring should not replace periodic satisfaction and loyalty assessments thatgenerate in-depth analysis that can direct improvement efforts on a broad scale.

8According to the results of the MFC work in the region 40% - 70% of clients choose their MFI on the basis of the word-of-mouth. In East Africa, the

MicroSave reports on around 60-80% clients.9For an interesting discussion on this issue please see The One Number You Need to Grow, Frederick F. Reichheld, Harvard Business Review, December

2003.

1. Clarify your objectives

2. Get your sample right

3. Design the questionnaire

4. Pre-test the questionnaire

5. Collect data

6. Analyze data

7. Report and use findings

Key issues in the

study design

Box A.Design and ImplementationProcess Steps:


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A mix of methods will provide you with a complete picture. If you use quantitative techniques, dontforget the great value-added of qualitative ones. The survey will give you quantified, representative dataon your clients satisfaction and loyalty. However, to use the data effectively you will need to understandwhat drives it and why certain things matter or dont matter to your clients. To maximize use of the data

it is necessary to complement quantitative work with qualitative information and vice versa. Qualitativemethods will help you to get your questionnaire right, quantitative methods will give you representativestatistics. Then probe the meaning of the statistics using qualitative methods.10

Draw your sample right! General tips on sampling11

To obtain results relevant to all your clients you do not necessarily need to interview them all.12 If

your sample is correctly drawn, you will be able to use statistical tests to extrapolate your results onto

the entire population of your clients.

Define your sampling framework well. You need to decide who is of interest to you and what are

the characteristics of the population to be surveyed.

Get a representative sample. There are different sampling methods. Random sampling guarantees

that every client has an equal chance of being selected. Any differences between the sample and thepopulation are only due to chance and not to selection bias; There are three main types of random

sampling you can use: simple, stratified, and systematic sampling.

Determine the right size. The bigger the sample, the more sophisticated analysis you may conduct

and the more sure you can be that the results from the sample truly reflect the situation in the whole

population. But bear in mind, the bigger the sample, the higher the cost of the study13.

Questionnaire is just a tool. That is why it is important to clarify your information needs and assesscapacities to satisfy those needs, and focus on your research objective throughout the process of thequestionnaire design.

Which type of survey to choose? There are different methods of collecting data and administering a

questionnaire (mail survey, telephone survey, face to face interview, self-completion form, etc.

14

) andthey affect the information you obtain. In this note, we will focus on a face to face survey.

Stick to the KISS rule. Keep It Short and Simple to obtain precise information. Translate yourobjectives into the questions and avoid including questions that are not directly linked to the informationyou need. Ask yourself what you will do with the information from each question. If you cannot giveyourself a satisfactory answer, leave it out.

Make the most of existing information. The most common mistake during the questionnaire designphase is neglecting information which already exits. Using secondary data15 will aid your questionnairedesign and help you formulate the right questions.

Get your questions right.16 Follow some principal rules on designing questions

Avoid threatening questions or statements. A respondent should not have the impression he/she is

being evaluated. Use neutral questions or statements.

Dont ask for too many things at once ask one question per issue.

Avoid emotionally charged words or leading questions.

10This paper focus solely on presenting a quantitative survey. However, there is a need to remember that each tool, method, technique is able to

provide you with somewhat limited results. The mix of tools allows to get a wider picture of an issue. You may use focus group discussions, partici-

patory rapid appraisal tools, individual interviews to unpack some of the complex issues underlying descriptions used in the survey. E.g. Product

Attribute Ranking can be very helpful in obtain the most important characteristics of your service in a client-language as well as provide you

with the understanding why they are less or more important. Relative preference ranking and Financial Sector Trend Analysis will help you identify

your competitors and understand what and why make your and their competitive advantage. More information on PRA tools and other qualitativemethods can be found in MicroSave Marketing Research for Microfinance Toolkit and at www.MicroSave.org .11For more information on sampling please see the references as well as the annex in the end.12However, in the case of smaller programmes (or not so frequent occurrence of the phenomenon) it is also possible to interview all the clients so

called census sample.13There are various guidelines or calculators you may use to determine your sample size taking into account your objectives, population characteris-

tics and capacities available in the relevant literature and accessible in the Internet (e.g. at http://www.surveysystem.com/sscalc.htm).14See the annex for more information.15Secondary data is information that already exists somewhere, having been collected for another purpose. There are various sources of secondary

data i.e. loan applications, client passbooks, MIS information, any previously conducted research, etc. (source: Market Research for Microfinance,

MicroSave).16The same concerns the answer categories both good phrasing and order are important (see the annex for details).

Questionnaire

design basics


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Define words clearly - make sure your questions can accurately tell you what you want to learn. The

way you phrase a question can influence the answers you get. Try to make sure the wording is clear

to the respondent and does not favour one choice of answer over another.

Do not use abbreviations or unfamiliar words this is particularly important for setting productattributes. In microfinance, there is a lot of jargon which microfinance clients may not understand.

Make sure that all terms used are well understood either by pre-testing the questions or/and discussion

with frontline staff. Very often using descriptions to present certain product characteristics can help

clients understand what we mean.

To avoid automatic responses to questions, try to use different formats or mix the questions

throughout the questionnaire (see tips on questioning order).

Watch out -score or rating scale questions are a particular problem. There are different kinds ofscales, and their type and sensitivity can influence the results. You can choose from dichotomous andmulti-point scale. The fewer the points, the easier it will be for a respondent to provide you with ananswer. However, it will be less able to capture differences of opinion among respondents.

Another decision you need to make about a scale is whether it will be of even or odd number of points.Having even number will force people to choose between negative and positive options and help youavoid the central tendency that is very natural for people to choose. However, with a good intervieweryou should be able to get the real answer from the respondent and still leave the middle option for thosethat are real ly indifferent to certa in issues.

The questions order matters. The order of questions and answer choices can encourage people tocomplete your survey. It can also affect its results. Here are some general rules that will help you to usethe question order in the most effective manner:

Start with easy questions. These will encourage people to continue the survey and help build rapport

with the interviewer.

Group together questions on the same topic to make it easier for the respondent to answer.17

Move more important questions to the beginning of a series or rotate the order to counteract the

habituation effect. People tend to think more about their answers to questions earlier in the series

and so give more accurate answers. With later questions they tend to give the same answers.18

Leave difficult or sensitive questions for the end. Any rapport that has been built up will make it

more likely that people will answer these questions. If people quit at that point anyway, at least they

will have answered most of your questions.19

As a rule, move from general to specific first ask about a general issue than move to details. Move

from spontaneous to supported questions ask an open-ended question first to get spontaneous

answers and only later ask about the same issue using closed questions.

Follow the logical flow - an appropriate order of questions helps you to reduce certain biases and

increases the likelihood of obtaining more accurate answers on sensitive topics. For example, tolearn whether your client uses other sources of credit first ask about the extent to which his/her

needs for additional money are satisfied by your loan and then move on to asking about how he/she

provides for this additional money that is not available from your institution.

17As mentioning something (an idea, an issue, a brand) in one question can make people think of it while they answer a later question (event though, they

might not have thought of those issues if they had not been previously mentioned), such grouping also helps to reduce the bias of influencing the answers of

one question by another one.18Another way to reduce this problem is to ask only a short series of similar questions at a particular point in the questionnaire. Then ask one or more different

kinds of questions, and then another short series.19For more information on open and closed ended questions please see the annex.


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Dont forget about demographicinformation. They will help you toidentify people of similar character istics.The best timing for this information

(age, gender, income, education, etc.)is at the end of the questionnaire. Bythen the interviewer should have builta rapport with the interviewee that willallow honest responses to such personalquestions. Exceptions to this rule areany demographic questions that qualifysomeone to be included in the survey.Obviously, these questions must come nearthe beginning. Some of the informationyou may be able to extract from the MISinstead of asking the respondent, in orderto save time.

Pre-testing the questionnaire willreduce the costs of the survey andincrease data quality. During the pre-test, make sure the questionnaire respondsto the research objectives and check it isproperly designed, in terms of language,length, order of questions by examiningthe reactions of your experimentalrespondents.

How the interviews are conductedis crucial to the quality of data.Interviewers need to be carefully chosenand properly trained.20 At the verybeginning, consider the characteristics

required of interviewers and analysewhether your institution has the capacity to supply the interviewers. Then decide whether touse external or internal interviewers. External interviewers are less familiar with the topic, butrespondents might be more honest with them as they are not representatives of the institution.Internal interviewers will know the institution and its clients, but their links with the institutionmay influence the way respondents answer the questions. Surprisingly, the costs of using externa l orinternal interviewers may not be dissimilar.

Training is a must as it is a tool increasing data credibility through building interviewers buy-in and education. First of all, the research objectives have to be explained in-depth to interviewersand you must ensure they understand them clearly. Each question has to be elucidated in the contextof research objectives otherwise there is a possibility that some questions will not be properly posedby interviewers. There should be common understanding of aspects so that interviewers make surethat answers provided are adequate to the researched topic. Interviewers should practice posingquestions and dealing with potential problems.

Visual aids and instructions. As the human memory is elusive, it is reasonable to provide theinterviewers with hard copies of instructions. For face-to-face interviews it is highly advisableto present possible answers to the respondent using response cards. Such a visual aid makes theinterview more eventful and makes the interviewers job easier.

How useful are quality checks? You need to check with the randomly chosen respondentswhether the interviewers actually visited them to conduct the survey to make sure that the answersprovided are from the clients themselves, rather than the interviewers.21 In addition, look throughquestionnaires for exceptions and unusual answers, which can be discussed with the interviewerand verified.

Avoiding mistakes in the future. After fieldwork, discuss the process of collecting data with theinterviewers. Use their knowledge to identify mistakes and ways of preventing them in the future.

20Thanks to the good choice of interviewers you reduce likelihood of biasing situations.21According to the ESOMAR guidelines, minimum 10% of questionnaires should be re-interviewed for data quality reasons. ESOMAR, founded

in 1948, is an organization unites 4000 members in 100 countries, both users and providers of opinion and marketing research. The society facilitates

the exchange of experiences between suppliers and users of research in order to optimise the integration of research results into the decision making

process. ESOMARs mission is to promote the use of Opinion and Market Research for improving decision making in business and society world-

wide. More information on ESOMAR can be found at www.esomar.org.

How to

Ensure

Quality data

Individual characteristics i.e.:

Sex

Age

Place of residence

Education

Etc.

Describing household situation:

Number of household members

Number of children

Number of dependants in the household

Indicators for income

Etc.

Describing experience with the institution:

Time with the programme

Number of loans taken / cycle

Cross - usage

Size for each loan taken

Etc.

Describing the business situation

Type of business

Place of operation

Registration status

Number of workers

Etc.

Box B. Example of demographicinformation


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Get the most from your data. If your survey design was driven by your research questions and youensured the data quality, the data analysis will be rewarding.23 It is wise to prepare the data analysisframework before the research implementation so that you will get all the data you need (Table 1). Thereare several tools you may use for the analysis, starting with Excel and ending with more specialized

statistical software, such as SPSS, Statistica, Quantum.

How satisfied are your clients? Questions on overall satisfaction only indicate the first reaction tothe product or service and does not provide you with accurate information on overall satisfaction.24

One of the ways toobtain meaningfulinformation onoverall satisfactionit is to constructa satisfaction index(see chart 2).25

How loyal areyour clients?As with the

s a t i s f a c t i o n ,we can look atdifferent aspectsof loyalty.26 To findout about clientloyalty we need totake into accountits differentdimensions, usingloyalty indices.In the presentedexample, we haveconstructed asecondary loyaltyindex. The positive

answers providedby respondentsto the questionson client intent torepurchase, pastrecommendationand likelihood torecommend weresummarized andallocated to thedefined categoryof secondaryloyalty.

To get a loyalty rating it is important to construct an index that will be a combination of all the mentionedvariables.

22The sample should cover your clients and your competitors clients. The satisfaction and loyalty questionnaire has to be the same for the two groups.23For more information on statistical analysis, see the annex and relevant references in the end.24As we discussed earlier to get a satisfaction rating score we need to look at the satisfaction with detailed aspects of performance areas. The way to do it is

to calculate a satisfaction index using satisfaction results from the detailed characteristics evaluated.25There are different ways to construct an index. In the case presented on chart 2, points were allocated only for top answers allocated to each aspect and then

summed. 4 categories were defined : not satisfied (0 max.value/4), poorly satisfied (max.value/4-max.value/2), satisfied (max.value/2 *max.value), very

satisfied (* max.value max.value).26As we discussed, loyalty is considered through such dimensions like breadth, depth, width and secondary behaviour.

What to do with

the data?

Table 1.Example of a Data Analysis Framework

Research objective Survey questions Analyses

* To determine the

overall and detailed

satisfaction level

1. About overall satisfaction

2. About detailed satisfaction

Frequencies

Descriptive statistics

Satisfaction index

* To identify strengths

and weaknesses

1. The same questions as above

2. The question about importance of

aspects

Frequencies


Correlation analysis

* To determine the level

of loyalty

Questions covering all aspects ofloyalty:

Breath

Depth

Length

Secondary behaviour: intent

to repurchase, likelihood to

recommend

Type of loyalty (emotional

attitude)

Frequencies


Loyalty indices

* To identify groups of

lower satisfaction and

loyalty

The same questions as above


(means and standard

deviations)

Pivot tables

* To segment clients

based on loyalty and

satisfaction

The same questions as above

Factor analysis

Cluster analysis

* To segment

clients based on the

profitability and target

characteristics

MIS

Profiling

Factor analysis

Cluster analysis

* To benchmark

satisfaction and loyalty

performance against

other players on the

market22

1. About overall satisfaction

2. About detailed satisfaction

3. Questions on relative performance

of the competition

Frequencies


Satisfaction indices

Correlation analysis


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How well are you performing?To assess this, you will need tocompare your results to thoseof your competitors, using

benchmarking analysis as it wasdescribed earlier on.

How do clients evaluate yourperformance in different areas?Using top answers (the percentageof definitely satisfied in eachcategory) to the question on clientsatisfaction with various aspects ofyour performance and calculatingthe adjustment threshold27 willallow you to identify two maincategories: programme elementsthat clients are satisfied with andthose that they are less satisfied

with.

Clients expectations. Clients do not attach equal value to all aspects there are aspects of high impor-tance and aspects that no attention is paid to. High satisfaction with the former leads to higher overallclient satisfaction and in case if improvements are needed, these are the attributes the change of whichwill bring the highest return. There are two ways to identify important aspects.

First approach (chart 6): is to rank the aspects of performance by asking clients about the importanceof each. Using a multi-scale question we are able to calculate frequencies and find out which aspectswere rated as the most important ones (top answers). The calculated adjustment threshold 28 enables thedivision of different attributes into categories of less importance and more importance for clients. Thelimitation of this approach is that a questionnaire becomes too long and thus tiring for a respondent, andconsequently the quality of results may decrease.

27The adjustment threshold is a sum of all definitely good answers divided by the number of all aspects.28The adjustment threshold is calculated as the mean value of percentage of definitely important answers for all aspects.


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Second approach (chart7): work out the level ofeach aspects influenceon the overall satisfaction

level through a correlationanalysis. Using the generalsatisfaction question anda multi-scale questionabout satisfaction withdetailed aspects, we runa correlation analysis toidentify the influence ofeach aspect on the overallsatisfaction. The limitationof the second approachis that answers have tobe diversified (differentrespondents have to choose

different answers) in order to differentiate between the aspects relative importance.

Performance vs. client expectations. To find out how this evaluation of institutional performancein certain aspects of its operations (client satisfaction) relates to client expectations, it is necessaryto compare satisfaction and importance results. This will enable you to identify priority areas for anorganization to improve.To do this am u l t i p l e - s c a l equestion ons a t i s f a c t i o ndetailing variousaspects of theprogramme, as wellas a question onclient expectations,

should be used.The findings canbe presented as inchart 8.29The crossing pointdivides the chartinto 4 areas:

1. Improve (low satisfaction and high influence) an institution should prioritise those aspects, as they

are important for clients.

2. Maintain or improve (high satisfaction and high influence) an institution is doing well in these

areas, so further improvements will not have much influence on overall client satisfaction.

3. No action needed (high satisfaction and low influence) this area is highly evaluated and not so

important. If there is a need to look for cost savings, then look here.

29We use axis X to present influence on overall satisfaction of each aspect (or a declared importance of each aspect), and axis Y to present the mean value

(or percentage of top answers) of satisfaction.


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4. Less important (low satisfaction and low influence) this is an area of low priority for improvement.

Even though the aspects are not highly evaluated, they are not important. Institutions can ignore

those aspects and focus on priority areas.

Short-cuts to segmentation. You should already have an idea of client overall satisfaction and loyaltyrating; which aspects are better or worse evaluated, less and more important to clients and whereimprovements are needed. However, it is important to consider who will benefit from these improvements,since MFI services serve different people with different needs.Simple descriptive statistics can be used to get this information - mean and standard deviation canbe calculated for each aspect using the multi-point question on satisfaction with detailed aspects. Thisanalysis will help you to understand how consistent opinions are across your client base. The findings canbe presented as illustrated in chart 10.

The point of crossing of the axes divides the chart into four areas: 30

1. H o m o g e n o u s

satisfaction (high

mean of satisfaction

with the aspectand low standard

deviation) aspects

in this area are

consistently highly

evaluated by a

majority of clients;

2. H o m o g e n o u s

d i s s a t i s f a c t i o n

(low mean and low

standard deviation)

aspects in this area

are consistently given a low by a majority of clients;

3. Dispersed satisfaction (high mean and high standard deviation) even though a majority of clients

are satisfied with the aspects, this opinion is not consistent. There are some respondents less satisfied

with the aspect;

4. Dispersed dissatisfaction (low mean and high standard deviation)- even though a majority of clients

are not satisfied with the aspects, this opinion is not consistent. There are some respondents satisfied

with the aspect.

Identifying aspects of dispersed satisfaction or dissatisfaction gives you an indication that further clientsegmentation is needed. However, further exploration of segments will be possible only if the sample isbig enough (about 300).

The analyses are also supportive in verifying information on the priority areas to improve.

For example, when you analyse the previously presented chart 9, you find out that the reactions tosuggestions and complaints is an aspect that doesnt require improvement. However, when you lookat chart 10, this information is characterized by dispersed satisfaction. This tells us that there are somegroups dissatisfied even though overall, the majority of respondents are positive. Being equipped withthis information, you may identify who those people are.

Client profiles. To identify more or less satisfied groups, you may use pivot tables to study thecharacteristics differentiating the groups. In such an analysis, you may notice e.g. that people who takesmaller loans are generally less satisfied with office location and loan officers professionalism thanthose taking medium size and higher loans. Further in-depth analysis can provide you with additionalinformation upon which you may decide to change your priority areas for improvement.

As we can see, analysis of the entire database will provide you with a rather general, superficial picture.To get more precise information you will need to conduct analysis in sub-groups of respondents.

Such profiling as presented above will provide you with more in-depth information on different clientpreferences. However, it is not powerful enough to identify client groups taking into account severalindicators simultaneously. To obtain such information you will need more sophisticated statisticalmethods for segmentation.

30In the presented graph the X axis represents standard deviation and the Y axis - mean.


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Comprehensive segmentation. To be able to further prioritise and better direct your improvementprogramme, it is important to distinguish groups of clients with relatively similar characteristics,behaviour and attitudes.

This involves more sophisticated statistical methods such as cluster or factor analysis. In the examplepresented, cluster analysis was conducted using three previously calculated indices31: satisfaction,loyalty depth and secondary behaviour. Based on the analysis, four segments were distinguished:

1. Lost clients: relatively low satisfaction, low secondary loyalty, low loyalty depth

2. Searching clients: relatively high satisfaction, low secondary loyalty, high loyalty depth

3. Waiting clients: relatively low satisfaction, high secondary loyalty, high loyalty depth.32

4. Happy faces: relatively high satisfaction, high secondary loyalty, high loyalty depth.

31For calculating loyalty depth index - % needs satisfied with loan , using other source of credit, for secondary loyalty index - intent to take a follow on loan,

willingness to recommend to others were taken into account.32The identified client segments were named in a way to characterize each segment clients potential behaviour based on the information on satisfaction

and loyalty. Lost clients are those clients that are dissatisfied and disloyal so keeping them will be the hardest task; searching clients are those that are

relatively satisfied but also relatively disloyal (they are probably already searching for a better solution) and are likely to exit the programme in the future;

waiting clients can be characterized by low satisfaction but high loyalty those clients are bound to our institution today (maybe because they have no

alternative or they give us a chance to improve, etc.) even though they are dissatisfied; the happy faces category includes all satisfied and loyal clients.


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General Background

Churchill F.C., Halpern S.S. (2001), Building Customer Loyalty, Technical Guide No.2, Microfi

nance Network.

Fink A., The Survey Kit (2002), SAGE Publications.

Gitomer J. (1998), Customer Satisfaction is Worthless, Customer Loyalty is Priceless, Bard Press.

Market Research for Microfinance Toolkit (2000), MicroSave Africa, www.MicroSave.org.

Reichheld F. (1996), The Loyalty Effect, Harvard Business Scholl Press.

Reichheld F. (2003), The One Number You Need to Grow, Harvard Business Review, on-line

edition, December issue.

Questionnaire design:

Walonick D. S. (2000), Survival Statistics , StatPac.

Converse J.M., Presser S. (1986), Survey Questions: Handcrafting the Standardized Questionnaire,

Sage Publications.

Fowler F.J. (1995), Improving Survey Questions: Design and Evaluation, Sage Publications.

Data analysis and presentation:

Pallant J. (2003), SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for

Windows, Open University Press.

Nicol A.A.M., Pexman P.M. (1999), Presenting Your Tables: A Practical Guide for Creating Tables,

American Psychological Association.

www.microfinancegateway.org/impact/method/iss4_3.htm

References


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Technique Short description Pros Cons

Face to Face

Interview

A trained interviewer conducts a

structured interview at the respondents

place. Answers are noted on the paper

and then entered into a data-base.

1. A questionnaire can be longer

(up to 30 minutes);

2. A questionnaire can contain

open-ended questions;

3. Observing the situation of an

interview (body language, etc.)

an interviewer is able to say

whether a respondent is telling

truth;

4. The interviewer can verify that

the right person is answering the

questions;

5. The response rate is higher than

in the case of other techniques;

6. The process of fieldwork

is time-consuming and

consequently costly;

7. A respondent may be biased

and over-report his/her

situation because of the

interviewers presence.

Therefore an interviewer

has to be very sensitive;

8. A respondent may feel

very uncomfortable with

the circumstances of the

interview.

Self-completed.

Interview left by

the Interviewer

A trained interviewer gives a

respondent a questionnaire to fill out

with some instructions on how to do

it. A questionnaire is completed either

in the interviewers presence or the

interviewer comes back to pick it up

the same day after some time.

1. A respondent gives more honest

answers as he/she is not under

interviewers pressure;

2. The questionnaire can be

filled out at the respondents

convenience;

3. There is also possibility to

verify some answers;



1. A questionnaire cannot be

too long and should be as

simple as possible;

2. There may be a lot of

missing answers as

respondents fill out only

those questions they want;

3. Time-consuming and costly

process;

4. If the questionnaire is left to

be filled out, the danger is

that someone other than the

designated respondent may

fill in the answers;

Phone Interview A trained interviewer conducts a

structured interview by phone. The

interview technique is similar to that of

the ]face-to-face interview. There are

two alternatives for entering answers

into the data-base.

The first method, which is more time-

consuming but less vulnerable to

mistakes, is where answers are noted

on the paper and than entered into a

data-base. The second one is to enter

answers at once into a data-base during

the interview.

1. A respondent may give more

honest answers because he

retains more anonymity outside

the face-to-face situation;

2. The situation of interviewing is

more convenient;

3. Process is time-saving and

relatively cheap;

4. Interviewers may be less

sensitive to biasing;

5. Another person can monitor the

interviews.

1. Very limited number of



too long (10-20 minutes);

3. Response rate tends to be

lower than in the case of

face-to-face interviews;

4. The sample is limited only

to those who have phones;

Self-completed.

Interview sent by

mail

There are several alternatives for

conducting this interview:

1. The classic one is that an

interview is sent by mail to

an interviewer with the return

stamp and an envelope and sent

back by mail.

2. An interview is sent by mail

to an interviewer with the

information that the interviewer

will come to get a completed

questionnaire after some time.

3. The interviewer leaves a

respondent a questionnaire to fill

out with the return stamp and an

envelope. A questionnaire is sent

back by mail.

1. A respondent gives more honest

answers as he is not under the

interviewers pressure;

2. The situation of interviewing is

more convenient;




too long and should be as

simple as possible;

2. There may be a lot of

missing answers as

respondents fill out only

those questions they want;

3. Another person than

the respondent can fill a

questionnaire out;

4. There is no possibility to

verify the answers;

5. Time-consuming and costly

process;

6. This has the lowest response

rate (about 5%) of all

available techniques;

Annex I. Techniques of satisfaction and loyalty surveys


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1) Basic Sampling methods (Walonick 2000)

Simple Random sampling is the purest form of probability sampling. Each member of the populat ion

has an equal and known chance of being selected. It is akin to pulling names out of a hat. Essentially,

you start with a list of clients in the population and the number of clients you want to sample. The

real question is how to select the clients randomly. You could mix the names up in a hat and pull

them out until you have the number you want. You also could assign a number to each name on the

list and select respondents using the random number function found on calculators or in spreadsheet

programmes or by using the random number table located in the back of many statistics textbooks.

Systematic sampling is often used instead of random sampling. After the required sample size has

been calculated, every Nth record is selected from a list of population members. As long as the

list does not contain any hidden order, this sampling method is as good as the random sampling

method.

In stratified sampling, the researcher first identifies the relevant stratums (subsets of the population

that share at least one common characteristic) and their actual representation in the population.

Random sampling is then used to select individuals from each stratum until the number of individuals

in that stratum is proportional to its frequency in the population. Stratified sampling is often used

when one or more of the stratums in the population have a low incidence relative to the other

stratums. When a population consists of many subgroups, simple random sampling may not ensure

that all subgroups are represented equally in the sample. Say you want to draw a random sample of

100 clients using agricultural loans to represent all of the clients that use this product. You know

that 75% of the clients are served by branch A and 25% by branch B. If you picked the names of 100

clients out of a hat, it is possible thatby chance alonemore of the clients in the sample are from

branch B. Using stratified sampling, you separate clients into strata, their subgroups, and randomly

sample clients from each strata. You select either the same number of clients from each strata

(disproportionate stratified sampling) or different numbers proportional to the size of the groups in

the population (proportionate stratified sampling). Randomly selecting 50 clients from branch A and

50 from branch B would be an example of disproportionate stratified sampling. Randomly selecting

75 of branch A and 25 of branch B would be an example of proportionate stratified sampling becauseagricultural clients from branch A make 75% of all agricultural clients.

2) What Kind of Question to Ask? Closed and Open Ended Questions.

In open-ended questions there are no predetermined set of responses, and the respondent is free

to answer however he/she chooses. Open ended questions are good for soliciting subjective data,

capturing unexpected and insightful suggestion, or when the range of responses is not tightly

defined. However, those are more difficult and costly to analyse, open to the influence of the reader

and tiring for the interviewer. Generally, we dont use them much in this kind of research most

often the questionnaire ends with open ended questions to solicit some unabashed ideas for changes

and improvements.

Closed ended questions usually take the form of a multiple-choice question. By restricting the answer

set, they easily allow to calculate percentages and other hard statistical data over the whole group or

over any subgroup of respondents. They make it easier to track opinion over time by administering

the same questionnaire to different but similar respondent groups at regular intervals. Finally closed

format questions allow you to filter out useless or extreme answers that might occur in an open

ended question. Multiple choice questions can allow for one or multiple answers to choose from.

While multiple answer questions help you to save paper and avoid a long series of very repetitive

question and answer choice lists, they are also a bit harder than the repeated lists for some people to

understand.

3) Designing Answer Categories

Make sure that the categories are understood by the client this particularly concerns product

attributes and characteristics areas you are looking at. Make sure they are in a respondent-friendlylanguage. If necessary use descriptions instead of phrases/words.

Answer categories need to be adequate to the question make sure that that the way you ask for

answer will really lead a client to provide you with the information you require.

Annex II.

Sampling,

Questionnaire

Design and Analysis Further Tips


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Make sure you include all the relevant alternatives as answer choices. Leaving out a choice can give

misleading results. Add the category other (specify) in case a respondent provides an answer not

included in the provided list or none of the above in case you want to limit the choice to the listed

answers. If you expect a single answer, make sure that the choices you have provided do not overlap with one

another.

Keep a logical or natural order of presenting answer categories. Answer choice order can make individual

questions easier or more difficult to answer. Always present agree-disagree choices, positive to negative

and excellent to poor scales in that order. When using numeric rating scales higher numbers should

indicate a positive answer and low numbers should signify more negative responses.

Remember that people tend to pick the last answer when they hear a list of choices read to them and

the first ones when they see them (e.g. on a respondents card). The answer choice order is more likely

to affect which choice is picked in the questions about preference or recall or questions with relatively

long answer choices that express an idea or opinion. That is why it is good to rotate the answers while

reading it to the respondent.

3. Data Analysis General Tips

Before starting the analysis make sure that your data is representative of your studied population. If you

used the sampling methods that do not reflect the variations in clientele, you will need to weight your data

to make it representative.

Clean the data base by looking at distributions and leaving out the outlying cases, recode the missing

values. When analysing questions exclude exceptions. These answers are of interest to you as they may

indicate those clients that face some phenomena not characteristic for the majority, however, to obtain

meaningful statistical results, first focus on your typical clientele.

To analyse satisfaction and loyalty data you dont need to know any sophisticated analytical techniques.

It is enough to be able to use descriptive statistics such as mean, standard deviation, maximum and

minimum value, frequencies, quartiles, mode, etc. Simple correlation analysis will be of help. However, to

segment your clients you will need to be able to apply more sophisticated methods such as cluster or factor

analysis.

You also need to learn about statistical tests that you may use to test significance of your results. Significance

tests enable you to extrapolate with certain likelihood the findings from the study sample onto the whole

client base from which the sample was drawn.34

When you analyse satisfaction questions with multi-point scales, use the frequency results with caution.

As discussed earlier people tend to over-report or underestimate certain answers. It is better to be very

conservative in your interpretations, which is why it is better to consider only top answers (answers that

pinpoint the highest possible evaluation or importance, i.e. definitely satisfied) as indications for client

satisfaction.

If the distribution of data is skewed use rather positional statistics such as mode, median and quartiles, as

mean and standard deviation will not be very meaningful in such cases

Pay attention to the percentage of hard to say or/and missing answers. They should be excluded from

analysis. However, if their percentage is big (exceeds 20%) they may indicate the respondent had a problemwith answering the question (either didnt feel comfortable with answering the question, could have been

dissatisfied, the question could have been not clear/understood, interview was badly conducted).

Statistical significance. To extrapolate results obtained through your analysis on the sample of clients,

you need to test them for statistical significance. If this is not done, you cannot claim that the results are

representative of all your clients

As the sample is heterogonous and clients differ in their preferences and evaluation, the results should be

analysed in sub-groups in order to capture characteristics of groups of satisfaction and loyalty.

When comparing current with previous studies remember about including background information on the

internal and external changes that have happened in the meantime as those may have influence on your

client satisfaction and loyalty. Relating results to competitors will help you to incorporate external changes

factor to some extent. Keeping record of internal changes is easy and will give you good insights for your

interpretation. Be objective and rely on figures and facts rather than your subjective opinion and prejudices while

analysing data.

34The following test would be of use: for checking differences between groups nominal and ordinal variables (chi square); for checking statisti-

This paper was published with the support of the Open Society Institute.

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