analysing and presenting customer feedback

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Analysing and presenting customer feedback

Published by the Institute of Leadership & Management and QMD Ltd © 2006Copied under licence

This session introduces techniques that can be used for analysing andpresenting all types of data.

Could you collect informal feedback from customers?


Can you analyse customer feedback and present it to your team?

In the BS2 session Collecting customer feedback , you learnt how im-

portant it is to collect feedback from customers. This can be informal

feedback or formal feedback. Formal feedback tends to come from

surveys of customers, using questionnaires or interviews, but can also

come from focus groups. Informal feedback comes from comments

and complaints made by customers and by observing their attitudes

and behaviour. In this session you will learn what you can do to make

sense of feedback and present it to your team so they can identify

ways of improving the products or services you supply to your custom-

ers.

During this session you will learn about how you can convert data into

information so that your team can convert it into knowledge. This

can apply to any data; in this case the data is the raw customer feed-

back that has been collected. By analysing it you can turn it into infor-

mation. Information tells you and your team something useful. It in-

forms them. Knowledge is what happens when you combine what you

have learnt with what you already know to get a clearer understandingof your customers and their requirements.





Calculate the mean of these figures, using a calculator. The

fifty numbers add up to 170. Divide this by 50. What answer

do you get?

Mean =

Start counting the numbers from the top left hand corner, go-

ing down the columns then up to next one. The first number is

1, the second is 1, the third is 2. Count up to the 25th num-

ber. What is it?

Median =

If you ask fifty people for their opinions of your organisation you will

get fifty different answers. As you saw in Collecting customer feedback

you can make it easier to understand what they think if you ask them a

standard question, such as: ‘How would you rate the quality of serviceyou received, on a scale of one to five, where one is awful and five is

excellent?’.

This is a closed question using a rating scale. It is closed because cus-

tomers have a limited range of answers and it is a rating scale because

they are rating the quality of service from one to five, which is a scale.

When fifty people have answered this question you will have fifty num-

bers, like these in the table.

What does this tell you about how people feel?Not a lot! This is raw data. What you want is in-

formation. There are two simple ways to get

some information from this data, both of which

are types of average. An average is the typical

value in a set of data (numbers) - it is representa-

tive of all the values. There are two averages that

you can use. They are called the mean and the

median. The mean is calculated by adding up all

the values (numbers) and dividing by how manythere are (in this case its 50). The median is cal-

culated by listing all the numbers into order,

from 1 to 5 (as we have already done in the table

here) and then picking the middle one.

Exercise

The first steps with numbers

1 2 3 4 51 2 3 4 5

2 3 4 5

2 3 4 5

2 3 4 5

2 3 4 5

2 3 4 5

2 3 4 5

2 3 4 5

3 4 5

3 4

3 4

3 4

3

3

3





The list of numbers on page 2 isn’t easy to read, so one way of mak-

ing it clearer and helping to analyse it more is to create a table. A ta-

ble is simply a way of putting data into columns and rows that are

easy to read. Columns go up and down, rows go from side to side. In

this table, we are going to see how many people gave a rating of 1,

how many of 2, and so on.

170 divided by 50 is 3.4. This means that the mean of the ratings

given by the customers was 3.4. The median is 3 - the 25th rating

when they are all listed in order is 3.

These are both quite similar, which is normal. It is only if some of the

values are right out at an extreme that the mean is far from the me-

dian. The median is the typical value. The mean is the one that is

mathematically more accurate, but nobody rated the quality of service

at 3.4, because it wasn’t an option.

You can use the two averages differently, to make a point about the

ratings. A typical customer would rate the quality of service at 3 out of

five, which is really only halfway up the scale. The mean tells you that

the ratings tend to be a bit above 3 but are not close to 4. If you

wanted to measure improvements in ratings then the mean would be

the best to use because you might see it creep up from 3.4 to 3.7, to3.8, whilst the median could still be 3. However, when the median

went up to 4 you could celebrate that a typical customer now rates you

at 4, not 3 any more.

Using tables

The table shows that two people rated the

quality of service at 1, and nine people rated

it at 2. Complete the table. Check you answerby adding up the right hand column. It

should total 50, as shown.

Then compare your table to the one on page

4.

Exercise

Rating Number

1 2

2 9

3

4

5

Total 50

Why does this make the data easier to read? Because the number of

people rating the quality of service at the different levels becomes a

lot clearer when they are all counted up in the table. It also means that

you can do other things with the data, as we shall see.





Compare the table and the bar chart. What advantage does each have

in presenting information to your team?

A table

A chart

Exercise

The set of 50 numbers (the data) has started to become

information now. We know that the mean rating is 3.4,

the median rating is 3, and we can see from the table

much more clearly how the ratings are chosen by the 50customers.

But it could be even clearer. We can make the informa-

tion more striking by creating a chart to illustrate the

data. What we are going to do is to create a bar chart. A

bar chart uses bars to show the size of something, in this case how

many people choose each rating scale. The biggest bar in this chart is

going to be 16 (we don’t include the total) so we need a chart that is

big enough to show that value.

The chart starts with two lines, like these below. The ratings in this

case will be shown on the vertical line (called an axis), and the number

of customers choosing each rating will be on the horizontal axis. The

bars will each be 5 mm high and each customer will be shown by mak-

ing the bar 5 mm long. So the 16 people choosing the rating 3 will

need a bar 80 mm long (5mm X 16 = 80mm).

Rating Number

1 2

2 9

3 16

4 13

5 10

Total 50

Data becomes information

Rating

5

4

3

2

1

2 4 6 8 10 12 14 16 Number





An alternative way of presenting the data on customer service ratings

is to use something called a pictogram. This makes the difference be-tween the ratings more striking still, but is less easy to read to get ac-

curate figures. A pictogram uses different sizes or numbers of pic-

tures to illustrate the numbers choosing each scale. In this diagram,

the picture is of a customer, repeated as many times as is needed to

show how many choose this rating .

The big advantage of a table is that the actual figures are clear. Team

members can see how many customers gave each rating. The bar

chart makes the relative size of each rating clear. You can see that the

majority were around 3 or 4. A bar chart is better at emphasising pat-

terns in data.

A bar chart is not always so easy to do by hand, and is best done on a

computer, using a spreadsheet (such as Excel). There are various train-

ing packages available to learn how to use a spreadsheet. It makes the

arithmetic and the charting much easier.

Pictures can be more striking

The pictures used should reflect what is being illustrated. In this case

it is customers so the pictures are of a typical customer, a young

woman. If it were showing sales of cars it could have a row of cars or a

series of longer and longer cars. (If you wonder why its longer not big-

ger cars, remember the bar shows the relative size by its length. If

you use bigger pictures you need to take account of the width of the

picture as well. That makes it much harder to produce, so stick to

making pictures longer, by repeating them if necessary, as we have

done.)

Rating

5

4

3

2

1

2 4 6 8 10 12 14 16 Number





Tables present the raw data in a way that is readable - they make it

into information. Bar charts make the information easier to see, al-

though the precise details may be a little less clear. A pictogram is

more striking but it’s even less easy to pick out the precise details.

You can see that as data gets processed, to a table, then to a bar chart

and then to a pictogram, it becomes more easy to see the pattern but

less easy to see the original raw data.

This is something you need to consider. What is more important for

the people seeing the information, how specific it is or how striking?

The next and final way of analysing and presenting data is concerned

with how it changes, especially over time. We saw in the original data

that the mean rating was 3.4. This isn’t enough for this organisation.

It wants to improve customers’ ratings of the quality of service, and

works on ways to raise standards. It repeats the survey of customers

at monthly intervals and calculates the mean for each. This is shown in

the table.

Because the data here is a series of numbers and has

been collected over time it is called a time series. Time

series data is valuable in helping organisations monitor

changes in performance. This data could be presented asa bar chart, but it is usual to present time series as a

line graph. This simply means that it is a graph where

the points are joined up with a line! You will be able to

see why this is preferred to a bar chart later.

The first thing you can see is that the mean ratings all lie

between 3.4 and 4.4. This means that in drawing the

graph we can ignore values much below 3.4 or much

above 4.4.

Compare the pictogram and the bar chart. What advantage does each

have in presenting information to your team?

A pictogram

A chart

Exercise

Showing changes in data

Month Meanrating

April 3.4

May 3.7

June 3.6

July 3.8

August 3.9

September 4.1

October 4.2

November 4.4

December 4.4





One way to estimate the trend is to lay a ruler along the line graph and

see what sort of pattern it shows. If you do that, what do you think the

rating in January would be?

The ratings in January are likely to have a mean value of:

Turn over the page for our estimate.

The pattern of change is quite clear, although the improvement may

have started to tail off. It’s hard to make a judgement on one month’s

data. After all, it dipped in June. This is something you should be

aware of with time series data. It takes several time periods to be sure

of any trend. A trend is a pattern in the change. Is it going up or

down, or levelling off? If it is going up or down, how fast is it chang-

ing?

Exercise

Mean rating

4.6

4.4

4.2

4.0

3.8

3.6

3.4

3.2

3.0

A p r i l

M a y

J u n e

J u l y

A u g u s t

S e p t e m b e r

O c t o b e r

N o v e m b e r

D e c e m b e r

J a n u a r y

Changes in mean ratings April - December





Our estimate is that the value will be about 4.6, but the flattening in

December could mean that the trend is changing and the increases

won’t be as great. This is likely as it is hard to get so many customers

to rate the service at 5. It would need to be very good to achieve that.

One of the most important reasons for collecting data is to inform de-

cisions. As data gets processed it becomes information. By making

sense of the information and using it to make decisions it becomes

knowledge. It’s important to collect data and analyse it because that

way it can become knowledge. Unfortunately, too many decisions are

based on opinions. Opinions are what people believe is true, not what

they have facts to prove is true.

If customers are complaining more, or returning more items, or simply

not coming back to buy again, it is often easier to find reasons that

avoid accepting any responsibility for their behaviour. Opinions are

useful because they don’t have to have any basis in reality. Don’t be

afraid to question people’s opinions. Ask how they know what they

know. If a team member says that customers don’t appreciate the

quality of your products and are buying inferior items, ask ’How do

you know?’ It could be that customers are judging the products on a

different basis. They may be looking at value for money - if your prod-

ucts cost twice as much, are they twice as good? The only way to make

informed decisions is to collect facts.

Of course, facts don’t only come in formal surveys. You may collect

lots of informal feedback from customers. This can come in comments

they make or by observation, seeing how they behave. It’s useful, if

you believe that there is a pattern to their comments and their behav-

iour, to look at ways of collecting your own data. Read this Case Study

to see how one team leader did it.

Facts or opinions?

Case Study

Nancy is the team leader in the Highways Department’s customer ser-

vice team. She has noticed an increasing number of complaints about

the way that contractors are behaving when roads are being repaired.

Residents have complained about loud noise early in the morning, in-

appropriate comments to women passing by, and rudeness to resi-

dents. Nancy decides to keep a record of the complaints.

(Continued on page 9)





Nancy draws a table and writes down the names of the county coun-

cil’s five main contractors along the top of the table, as column head-

ings, and the main types of complaint down the side. For the next

month she and her team makes

a simple record of the com-

plaints, as shown in the table.

At the end of the month shetakes the information to her

manager to show him. He sees

immediately what the problem

is and takes action.

A&P con-struction

RTSystems

Churchill& Sons

aXis plc

Loud noise

Sexistcomments

Rudeness toresidents

Excessivedelays

Total 28 5 4 1

Nancy has used a method known as a gate count to collect her data. Agate count uses one vertical line to indicate one event. These are

drawn parallel and the fifth event is recoded by using a diagonal line

across the other four, a bit like the way a wooden gate is built. The

completed gates are all in fives, making it easy to total up the data.

This is a simple but effective way of collecting data.

Nancy had decided the categories that she would use to collect the

data, based on comments the team had received. If a new one ap-

peared while she was collecting the data, that could be added on the

bottom of the list. Instead of telling her manager that she was getting

a lot of complaints about some contractors, she could say, ‘We have

had 38 complaints in the last month and 28 were about A&P construc-

tion!’.

As a team leader you should collect data and analyse it so that you

and your team are informed and that way you will be able to under-

stand you customers requirements better.





Complete the following exercises. Refer back to the session if neces-

sary.

A. Analyse the following data and process it so that it could bepresented to your team.

Customers have complained about how long de-

liveries are taking. You have collected data on

20 deliveries. The table shows how many days

each one took.

1. Calculate the mean delivery time.

Total the set of data:

Divide the total by 20: =

20

2. Reorganise the data into ascend-

ing order (from 1 to 8) and iden-

tify the median delivery time.

(The middle value is the tenth or eleventh.)

3. Complete the table to present the data more clearly.

Continued over the page.

Comprehension Check

3 4 2 3 5

1 4 3 6 4

2 3 5 4 6

8 5 2 3 5

1

8

Days Number

1

2

3

4

5

6

7

8





4. Prepare a chart or pictogram to illustrate the data.

Comprehension Check continued

Days

1

2

3

4

5

6

7

8

1 2 3 4 5 Deliveries





How well do you use the skills in this session?

Does your organisation collect customer feedback?

Is it analysed and used to make decisions?

Could you collect data from informal feedback, to help you

and your team understand what customers require and what

they think of the products and services you supply?

1. Read the list of skills. Tick the boxes to show your strengths and

weaknesses.

Skills strengths <- - - -> weaknesses

I’m

good

at this

I’m

quite

good

at this

I’m not

so

good

at this

I’m

quite

poor

at this

calculating means and medians

preparing tables

constructing charts, pictograms

and graphs

collecting and analysing informal

feedback from customers 2. Do you want to improve any of these skills?

3. How do you plan to improve the skills you listed in question 2?

(You might want to discuss this with your line manager or your tu-

tor/mentor/coach.)

Think and Apply

analysing and presenting customer feedback

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