Branding Banks For Shareholder Value 3.0 Customer Perceptions

Branding Banks for shareholder value Discussion Draft Section 3.0

Branding banks for

shareholder value

Section 3.0

How customer perceptions

develop

Planned series of papers

Discussion Release
Draft Version Date
Creating shareholder value - an outline 1.0 Mar-10
Knowing customers 2.0 Mar-10
How customer perceptions develop 3.0 Apr-10
Branding banks is vital TBA
Branding banks is hard TBA
Measuring customer perceptions TBA
Gaps analysis TBA
Bank structure and brand control TBA
Six Sigma and brand control TBA
Valuing bank brands TBA

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© Geoffrey Johns 25 March 2010


Introduction

This is the third in series of discussion drafts in which I attempt to trace the path from
customer perceptions to shareholder value. The first covers shareholder value as a goal
of the system and the analysis framework I use. The second is about knowing
customers through segmenting on key characteristics. This section deals with
understanding how customer perceptions develop. This understanding is crucial if banks
are to have influence over how customers and non-customers think of their brands.
Section 1.0 contains the general introduction to this series of papers.

Personal experience trumps all other
messages

My first and perhaps most important observation about the development of perceptions
in banking is that personal experience is more important than any external influence. I
have interviewed more than one person still fuming about a bounced cheque twenty
years ago.

Advertising communication
is accepted when it aligns
with favourable beliefs
The media is scanned for
messages that confirm our
The opinions of beliefs
trusted advisors,
colleagues, friends
and family are sought.
The perceptions of the
individual largely
shaped by experience

Individual Peers Media Advertising

2


Banking is not top of mind in most people’s day to day lives. Adverse experiences,
sometimes trivial to those who design bank processes, can sear themselves into people’s
minds. An impression of a bank can settle itself in the heads of customers quite early in
their lives.

People screen out messages that do not gel with their preconception based on their
experience.. They interpret messages that are not screened out to reinforce their
preconceptions. They actively seek confirmation of their preconceptions in the
environment about them.

Marketing communications

Media comment

Trusted advice

Contradiction Own Confirmation
filtered experience sought
reinterpreted
Information

Based on their experience customers construct stories in their heads where the elements
of the stories are self-reinforcing. They are slotted into a pattern of cause and effect in
which the customer justifies what is often a gut-feeling by a logic pattern imposed upon
it.

3


Customers create stories in their heads about their bank. The exhibit below is developed
from some of the attributes that are measured by the TNS Business Finance Monitor in
Australiai. It shows how my qualitative research indicates that people construct stories
that explain their perceptions. Tight knots are formed in people’s minds in this way. ‘My
bank values me as a customer therefore they take the trouble to understand my
business therefore they are (are able to be) helpful and supportive’. Sometimes
researchers are concerned that statistically they are unable to distinguish the relative
importance of such attributes in driving satisfaction. I suspect that this in part caused
by the fact that attributes are rarely mutually independent. They are strung together in
stories.

Primary
causality
Positive
feedback
Responsive and
flexible

They value me
Helpful and
as a business
supportive
customer

Helps
Understands my businesses
business achieve their
business goals

The knot tightens until an experience is powerful enough to cut through it cuts through it.

4


The process of disaffection is discontinuous

The following set of exhibits is taken from my qualitative research of the deterioration of
customer commitment in business banking. It illustrates the process of adverse
experience cutting the Gordian Knot of inertia.

You are a
danger to my
business
You are
Six steps to disaffection exploiting me

I don’t trust
you

I can’t rely on
you

You don’t
value my
business

You don’t
know me

5


Each step requires its own impetus. At any stage it is possible with the right actions to arrest
decline. But it takes an enormous management effort to put the process into reverse; there is
a ratchet effect at work. To do this requires inculcating a whole new thinking framework into
the minds of customers. You have to reach beyond responses to new experiences to attitudes
and beyond attitudes to beliefs. It seems that we cannot easily retrace our steps. By contrast
each step prepares the customer for the next one. In the story the customer is telling in his or
her head the logic builds as each step is taken. „You don‟t value my business because you
don‟t know me‟.

On one occasion I was told, on joining a bank, that management consultants had estimated a
net defection rate among business customers of 9% pa. I believe that what arrested this in the
short run was mandating visits to customers by senior management to assure them their
business was valued. However, improvement in measured satisfaction took two years of
effort including integrated rebranding.

You don’t You are a
You don’t I can’t rely on I don’t trust You are
value my danger to my
know me you you exploiting me
business business

Mutual lack of contact

Just being an account number

Untailored communications

21

„You don‟t know me‟ is a common early warning sign that that the situation is prone to
adverse surprises just around the corner

6


business business

Lack of access to senior bankers

Seemingly arbitrary account management decisions

No proactive solutions

Indifferent service

Inflexible application of rules

22

„How can you value me if you don‟t know me?‟ Business people, at work are at the centre of
their world. Do they feel that they are peripheral at best to the world of their bank?

business business

Bank mistakes
Inconsistent policies
Poor processes
These things relate more
to poor management than Gaps in product/service offerings
bad intentions Lack of banking skills
Bank actions hard to predict
Poor dispute resolution
Changes to management team
Inconvenient access
Not keeping up with the market

23

7


It is important to understand that right up to this point the bank need not have done too much
wrong. In a later paper, I shall discuss the importance to brand of relationship managers. For
now I will say that a relationship can have reached this point without being revealed in any
Key Performance Indicators.

business business

Decisions based on bank
not customer needs
This is driven by a build up of
the previous three. If you don’t Unprofessional
know me and you don’t value
my business and I can’t rely on Bankers lacking
you, then I don’t trust you. understanding of business

Media scandals

Poor performance vs. competitors

At this point, the bank is on the customer‟s „watch list‟. The bank, however, still might not
realise this. In terms of commitment, which I described in the last paper, the search for
alternatives is beginning.

business business

Aggressive pricing

Cost cutting This perception is
more easily triggered
Reduced functionality if the four previous
perceptions are in
No support place.

8


In the case uppermost in my mind is the case of Westpac Banking Corporation. In 1992
it came close to insolvency on the back of perhaps a dozen large property loan
delinquencies. Westpac’s management of its SME customers in the years leading into
the crisis had been among the best of banks. But at this point, increased pricing,
reduced lending, greater security demands, more rigid terms, conditions and covenants
were imposed on them. Sometimes relationship managers apologised to customers
explaining it was because of corporate lending gone bad. The key thing felt by
customers was that their account was being managed with no reference to or
understanding of their own business. They felt completely out of control of events vital
to them. On the spectrum of customer perceptions this is as bad as it gets.

business business

Arbitrary, irrational and
aggressive credit decisions

Major disruptions to business
processes

Fear of being at a significant
disadvantage to competitors that
have a better bank

The existence of the earlier perceptions
will mean that these issues are nearly
impossible to resolve.

26

Many customers will have defected or at least moved some of their business before this
point is reached. One of the most common reasons I have heard for switching banks by
business customers is not so much that that the reality of the situation was a rock
bottom. It was more like they felt they ‘couldn’t live with themselves’ if they continued
to let their bank treat them this way.

Obviously, these same six steps don’t happen to every customer and some customers
are more or less tolerant. Nevertheless it is a fair take out from my qualitative research

9


over many years. At each step the process becomes harder and less certain to reverse.
This is because the bank begins to be seen in the mind of the customer as ‘Well they
would do that, wouldn’t they, because that’s the people they are?’ In short it is a brand
killer.

Resistance to changing our minds

There are lags too in how we change our minds. I am not a psychologist but I offer the
exhibit below as a representation of how I think people test their perceptions in the
world of experience.

Beliefs

Reframing feedback

Attitudes
(Reusable decisions)

Needs

Contextualisation
feedback

Expectations

Choices
Realignment
feedback

Experience (feedback)

Outcomes

The key seems to me to be expectations. Up to a point outcomes will be evaluated to
confirm expectations rather than refute them. It is only when there is a rupture that a
process of accommodation to new experience begins. Changes in expectations can lead
to attitudes changing to contextualise the new experience. At this occurs before the
walls of belief can be breached. But then sometimes something that matters to the

10


person happens so out of line with expectations that the result can be a sudden
reframing that is all the more powerful.

The Conversion Model explaining discontinuity

Let’s turn again to the Conversion model™ which I described in Section 2 of this series.
The process of which the Conversion model takes a snapshot in time is in fact dynamic
and ongoing.

Loss of Need for new
business product /service
Lag

Lag Enhanced
perception of
Increased alternatives
ambivalence

Lag

Lag Increased
importance of
choice of bank
Dissatisfaction

Adverse
experiences

As dissatisfaction grows the customer’s search for alternatives intensifies. At the same
time the customer’s perceived importance of the choice of bank is likely to grow. This is
generally considered to be a stable characteristic; some people innately think this is
more important than others. But it is also something that people rarely focus on. When
they need to think about who they bank with the importance of the decision tends to
increase.

As the customer evaluates alternatives to their bank and these are seen positively
dissatisfaction with the bank tends to increase. It may even be that the test alternatives

11


to the extent of actually having dealings with them. They are likely to meet with other
bankers and to consult friends and business associates ii. The resulting increase in
disposition to alternatives and increasing dissatisfaction with their bank heightens their
level of ambivalence. Usually, what is then needed for the next step to be taken is a
new banking need. People relatively rarely switch banks altogether. There is more a
seepage as new needs arise.

The picture tends to be one of rising disaffection leading to a mental break with the bank
that may not be immediately apparent. The bank may not become aware until value
shifts. Even then, if value shifts on a new product the bank may still be unaware of the
relationship breakdown.

Customer inertia in banking

Much is said about customer inertia in banking. People tend to rarely move from one
bank to another. In Australian business banking the ‘churn’ is less than 5% a year and
of these, I guess that perhaps one and a half percentage points are pushed for reasons
of risk or under-pricing for riskiii. In personal and business banking value seeps rather
than switches. This usually happens when a new product is required or some life event
(e.g. moving to another employer or town) occurs. There are several reasons for inertia.
People have more important things to think about than banking. They tell themselves
that all banks are the same. They think that if their bank compares unfavourably in
some area (e.g. online banking) it will soon catch up. They tell themselves ‘if it isn’t
broke don’t fix it’. They have life routines they are reluctant to change. They have got
used to their bank and can predict how it will deal with them. There are lots of reasons
for inertia and some of them are based on good sense. In a later paper in this series I
shall offer a dollar quantification of its value to a bank. But strong as these ties are they
can mask, until it is too late deep underlying reasons for change.

The following exhibits draw some causal connections from a few qualitative studies I
have done that touch on inertia. There has been an event that cast some light on
inertia. As I say in Section 1.0 of this series there tend to be few breakthrough products
in banking. However online banking was an instance where the breakthrough in
customer needs was significant and where banks did not move simultaneously or with
equal competence. The key events were roughly these. Banks offered some form of

12


electronic banking first to corporate customers and then to the SME market. This was
because the customers were valuable and had a strong need. Next, online banking was
offered to the personal market. There were economies of scale in development and
reduced transaction costs. Development activity was channelled into the personal
market. Meanwhile business online banking increasingly seemed out of date and clunky
as customers compared it to their personal banking experience. Also business
customers had often experience of dealing with more than one bank online and could
make comparisons. Banks therefore began to reassign ICT resources to the business
market but they were not all able to do this immediately. The illustration below
describes the logic of inertia.

Business
customers are
reluctant to
The service change their ‘If it aint broke
element of a new
product is difficult banking don’t fix it’ -
people learn to live
to evaluate in arrangements
with minor defects
advance of
and work around
purchase

Often any changes
are hard to reverse There is a belief
if they don’t work among businesses
out that all banks are
There can be a the same
high opportunity
cost in diverting
effort from the
core business to
banking issues

There are cogent reasons why customers are reluctant to change banks as shown in the
exhibit above. Especially customers are reluctant to shift their transaction accounts as
illustrated in the exhibit below.

13


Transaction accounts
are important to
business people and Transaction
very sticky to shift accounts carry
with them risks of
fraud and default

Transaction
Day to day cash accounts are
flow management An overdraft complicated and
is the life blood of Often cash flows facility is highly messy to switch
business are unpredictable prized by from bank to bank
and volatile – businesses but
many businesses tightly controlled
are living on the by banks. Without
edge one, cash flow
control is of vital
importance

A window of opportunity opened and then closed again as laggard banks caught up but
not before some loss of value.

The window of
opportunity
closed again
as inertia First movers have
A window of many advantages
reasserted opportunity even with less than
itself opened perfect products

On-line / internet
It takes a seismic
banking has
shift to create
irresistible appeal
opportunity to
to many
switch customers
businesses
to new products

Business
customers are
reluctant to change
their banking
arrangements

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I see this as an example of a situation favouring customer inertia suddenly becoming
more liquid but then refreezing. What loosening of inertia we can expect to see in
banking is most likely to come from ICT developments or from financial crises. I see
these as always being temporary followed by the reassertion of inertia.

Kano analysis and its implications for
measurement

Around 1980, Noriaki Kanoiv threw a sizeable spanner into the works of measuring
satisfaction. In doing so he adds another layer of complexity to my analysis.
Perceived satisfaction

Neither satisfied nor dissatisfied

Actual needs fulfilment 22

Kano distinguished between the varied ways in which different aspects of a product or
service cause our satisfaction level to respond in different ways. In the exhibit above
the green line shows satisfaction to rise in line with the extent to which we perceive our

15


needs to be met. This can be considered the norm. The more you meet customer needs
the happier they are.

Actual needs fufilment

But in other aspects of the product or service there are some things (the orange line in
the exhibit above) that are expected. Customers are not satisfied when they are well
performed but become angry when they fail. A while back I worked with a firm that
provided pension funds with administrative service such as filing financial statements
and also high level tax and investment advice. Failure to lodge financial statements with
the supervisory authorities on time could result in fines for the fund trustees. These
expected parts of the service if they were unfulfilled would leave their clients highly
dissatisfied. Correspondingly those parts of the service that were intended to add value
the supported funds and which could have delighted their clients would never get off the
ground in their clients’ perceptions.

Kano analysis also identifies elements of the product or service that delight customers.
They are not expected and are all the more powerful in their effect. As an example
there is the relationship manager I knew who drove out to the airport at night to
personally deliver a replacement MasterCard to a client about to board a plane.

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There are some important implications for measuring satisfaction. The first is that you
cannot simply add up or average the ratings of a number of attributes where some are
expected, some are normal and some ‘delight’, in Kano’s termsv. They are different and
in a sense exist on different scales measuring quite different things. Moreover, they are
connected. Failure in an expected part of the product or service can lead to a completely
different view of performance in a ‘delight’ factor. In effect this means that a group of
customers that were distinct in that a bank had failed them on the expected factors
when compared to a group of customers where this was not so would have given
different ratings to the delight factors. The implication of this is that, for example, to
derive customer ratings of attribute importance statistically as opposed to customer
stated importance can be misleadingvi.

An experimental retro-fit of Kano analysis

Sadly, I have never been asked by a client to conduct a Kano analysis. Were I to do this
it should ascertain the Kano classification of attributes by a qualitative study, ideally
supported by a quantitative study before the main study. However, Gary Lembit
(already recognised in Section 2.0 of this series) and I did attempt to assess how Kano
analysis might reinterpret an analysis of the business banking sector. I am aware that
such a retro-fit after the event is, in multiple ways unsatisfactory but, nevertheless, i
found the results interesting and will share them with you here.

The attributes listed below are similar to but not identical with those used in the TNS
Business Finance Monitor cited in Section 2.0. We then classified them according to
Kano analysis as sown in the table below. We used a separate classification for price
because, candidly, we didn’t know where to put it.

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Pricing Expected Satisfiers Delighters

a Understands my future needs
b Flexible solutions
c Recognition for my business
d Provides ideas on financial management
e Understands my business and history
f Outcome adds value to my business
g Responds quickly
h Knowledge and expertise
i Offers sound advice
j Helps me avoid risks
k Comprehensive product range
l Value for money
m Prepared to negotiate
n Accurate
o Access to specialists
p Efficient branch network
q Latest electronic services
r Easy to use systems
s Competitive pricing

Next, using the results of the work already completed. We created a matrix of scores
given for each attribute against statistically derived importance. Note here my earlier
caveat concerning statistically derived importance. Here we had no option, of course.

The matrix below shows the outcomes. The data points are cloud coded:

 Pricing
 Expected
 Satisfiers
 Delighters

Pricing as might be expected fall into the low performance quadrant but it is also the low
importance quadrant. Customers didn’t like it but it did not matter to them that much vii.

The high performance / low importance quadrant contain nearly all the ‘expected’ (the
satisfier) attributes. As Kano would predict, they were done well but this was not seen
as important. Kano would also predict that they would become important if they were
done badly but our data didn’t give us a data point to verify this with.

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a. Understands my f uture LOW PERFORMANCE HIGH PERFORMANCE
needs HIGH IMPORTANCE HIGH IMPORTANCE
b. Flexible solutions
c. Recognition f or my
business a b
d. Provides ideas on
f inancial management
e. Understands my c
business and history
f. Outcome adds value to d e
g.
my business
Responds quickly
f
h. Knowledge and
expertise
g
i. Of f ers sound advice h
j. Helps me avoid risks
j i
k. Comprehensive
product range
k
l.
m.
Value f or money
Prepared to negotiate mo l n
n.
o.
Accurate
Access to specialists
p q
p. Ef f icient branch r
network
q. Latest electronic
services
r. Easy to use systems
s. Competitive pricing

s
LOW PERFORMANCE HIGH PERFORMANCE
LOW IMPORTANCE LOW IMPORTANCE

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In the low performance / high importance quadrant we find most of the ‘delighters’ they
unexpected features that come as a nice surprise to the customer. Customers are
responding to the survey with – ‘yeah that would be good – I don’t get it though’.

Finally, the ‘satisfiers’ the routine things that are part of the expected service fall in the
high performance / high importance quadrant. This is doing well at getting the basics
right.

Overall, while I am fully aware this is by no means a definitive study on the application
of Kano, I do believe that it offers a strong suggestion that Kano analysis does have
something important to say. It should be deployed more often in banking studies.

19


Lags in management response

I have talked about lags in terms of the how people respond to their experiences. Lagsviii
also occur in how banks respond to customer disaffection. Chief Executives in banking
talk often about it being like changing course on an ocean liner.

2008
New regime operating
2008 2009
Implement most clients experience improvement

2007 2009
prepare inplementation all clients experience improvement
2010
2007 results noticeable in surveys
decide what to do
2006
Recognise problem
2006
Problem occurs

2007 2008 2009
2006 2010

The exhibit above is based on my experience of major change programmes in a couple
of banks. It is of course illustrative. If anything I think it understates the time lag. It
also assumes that the change is successful. This isn’t always the case.

Measurable client responsiveness to improvement in the business system lags for several
reasons. First, even improvements can have adverse short term consequences. From
about 2003 all Australian banks began to improve the incidence of relationship
management. Generally smaller portfolios lead to greater customer satisfaction and
eventually commitment. However, in the short term several adverse consequences
arise:

 Some customers must be moved to the portfolios of new managers. If the
average portfolio size is being reduced from 100 to 80 this means 20% of them.
Qualitative research shows customers rarely like this and the results can be
expected to show in surveys.

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 Some relationship managers are promoted prematurely and find trouble finding
their feet. Some customers can be expected to perceive deterioration in service
because of this.
 Some managers are new hires from outside the bank and they take time to learn
how the system works. Some of them may not be good recruitments anyway.
 The management style among the next tier of managers has to change this
transition if quite difficult as senior managers have to become more hands on ix.
 Times of change often involve new initiatives coming at front line managers from
different directions. For example if the Chief Risk Officer wants portfolios cleaned
up at the same time as the sort of initiative I have described above the difficult of
change management is compounded. Similarly, new front line ICT systems may
be introduced.
 Customers can interpret good intentions unkindly, especially if they tend already
to disaffection. Increased intensity of account management meant to strengthen
relationships can easily be seen a intended to promote tighter risk control.

Going beyond the unintended adverse consequences of improvement there are other
reason why change seems slow to achieve results:

 Customers take a while to become aware that a change has occurred. Customer
reviews are often infrequentx.
 New customer needs are often infrequent so the satisfaction experience by a
product / service need being well handled takes a while to come through as does
the financial measurement of the sale.

Let me conclude this discussion with a vignette from my own experiencexi that illustrates
a couple of the point made above.

At one time I was closely involved in a major switch towards relationship
management. I ensured through direct mail that each customer knew who
their relationship manager was, how to contact them and what their role
was i.e. to solve customer problem. Meanwhile the branch network was
also undergoing change as part of the same overriding initiative. One
outcome intended or otherwise was that the branch network was shifting
its focus away from small business towards home mortgage lending. It’s
amazing what changing objectives and rewards can do in a well-disciplined

21


work force. So newly appointed relationship managers were inundated
with complaints, questions and problems connected with branch service
over which they had no control. I was inundated by complaints from
relationship managers! All of this was pretty much unforeseen and all of it
was completely unavoidable within the commonly accepted world view of
the organisation.

So lags, discontinuity and volatility are natural to the system and we have a new system
element to consider. I illustrate this below.

The system displays unpredicted
lags and volatility

Lag Lag

Management tampers with the
system

I am fairly certain that I witnessed more than one purposeful management change that
would have succeeded had the corporate suite shown more patience and wisdom. In the
words of one top executive I have known.

If they (divisional heads) can’t do it we’ll find someone (management
consultants) to help them and if they still can’t do we’ll find someone who
can!

Well good luck! I should say. Because that process takes about three years in my
experience and that’s time you never have.

22


The word ‘tampering’ in the exhibit above, I have taken from Edwards Deming xii. To
quote him at greater length:

We may now formulate two sources of loss from confusion of special causes
with common causes of variation:

1. Ascribe a variation or a mistake to a special cause when in fact the
cause belongs to the system (common cause);
2. Ascribe a variation or a mistake to the system (common causes)
when in fact the cause was special.

Over-adjustment is a common example of mistake No. 1. Never doing
anything to find a special cause is a common example of mistake No. 2.

To my mind this is one of the most profound statements on the subject of management
that has ever been made. I have, in this paper described a number of sources of
variation in the development of customer perceptions of a bank. How management
respond to these in business system design can bring the system under control or can
exacerbate the volatility. In responding to perceptual feedback to management change
making the wrong choices great damage can be done to brands as I shall discuss in the
forthcoming section on brands and bank structures.

The exhibit below outlines some of the connections between the models I have used in
this paper.

Business and personal customers

Most of my illustrations above have been taken from business rather than personal
banking. That is where the majority of experience has been. I should say that my view
is that personal banking displays much the same behaviour except that it is more muted.
I can tell you that almost exactly two thirds of business customers (from a Business
Finance Monitor sample of over 10,000 respondents) rated the importance of the
banking relationship as a 1 or 2 on a scale of 1to 5 where 1 means very important. I

23


don’t know what the figure for personal banking is but I’d guess slightly lower. The
comments I have made above I think would also be true for personal bank customers
but perhaps somewhat muted.

Where should we look for signs of sea change?

I have argued that management failure to detect improvement in response to
investment can lead to vacillation. What then can be done? First measuring process at
a detailed level helps. Also it helps to measure activity and responses rather than only
financial outcomes.

For the Conversion Model I should look at three key transitions illustrated below.

Customers Non- customers

Committed Uncommitted Open Unavailable
3

Entrenched Average Weakly Strongly
Shallow Convertible Available Ambivalent
committed committed unavailable unavailable

1 2

I would expect to see early signs coming in roughly the sequence shown. It doesn’t
have to be in that order. But you do need to dig for signs quite deep in the detail of
whatever data you have.

Next I should look at the attitudinal group we identified in section 2.0 that we then called
leaders. Their perceptions of change may be more acute than the mass of customers.
Therefore you might see changes in their commitment presaging that of customers as a
whole. This follows a line of thinking that I was introduce to by Eric von Hippelxiii In
Appendix 1, I reproduce my 2006 outline of how to deploy von Hippel’s ideas in research
for innovation. They apply as much to understanding response to brand.

24


The role of brand

What then is the role of brand in customer perceptions?

A major theme of this paper has been that perceptions are strongly based on personal
experience. Marketing communications are seen as have a weaker role. I shall discuss
how such communication can be made effective later in this series of papers.

BRAND

Customer expectations

The objective Customer
quality of the perception of
experience the experience

I want to conclude this present section, however, by suggesting that a key role of
banking brands is to modify the customer’s interpretation of experience. This is
achieved by a cyclical process through which expectations themselves are modified.

The secret of life is honesty and fair dealing; if you can fake that, you've
got it made. Groucho Marx

But, alas, contrary to the view of Mr Marx, it can’t be faked.

25


A tentative overview of this section

Primary
causality
Positive
Responsive and
feedback People create logic to justify the outcome of experience Marketing communications
flexible
Media comment

They value me Trusted advice
Helpful and
as a business
supportive
customer

Contradiction Own Confirmation
filtered experience sought
Helps
Understands my businesses
business achieve their

reinterpreted
business goals

Information
It takes powerful experiences to change beliefs You are a
danger to my
business
You are There are hurdles to changing beliefs
Six steps to disaffection exploiting me
Beliefs
I don’t trust
you
Reframing feedback

I can’t rely on
you Attitudes
(Reusable decisions)
You don’t
Could reinforce good and mitigate bad experience value my
Needs
business

You don’t Contextualisation
know me feedback

Actual needs fufilment

Expectations

Choices
Realignment
feedback

Experience (feedback)
There are cogent reason for inertia
Minds are changed
Outcomes
Business
customers
are reluctant
to change
BRAND The service
element of a new their ‘If it aint broke
don’t fix it’ - Measurement is hard
product is banking people learn to
difficult to arrangement live with minor
evaluate in
advance of s defects and work
around
Customer expectations purchase

Often any There is a belief
The objective Customer changes are hard among
quality of the perception of to reverse if they businesses that
don’t work out all banks are the
experience the experience There can be a
high opportunity same
cost in diverting
effort from the
core business to
banking issues 2008
New regime operating
2008 2009
Implement most clients experience improvement

2007 2009
prepare inplementation all clients experience improvement
2010
2007 results noticeable in surveys
decide what to do
2006
Recognise problem
2006
Inertia is overcome Problem occurs

2007 2008 2009
2006 2010
The bank responds
A brand that conditions experience.....
The system displays
unpredicted lags and volatility

But evidence can be inconclusive
Lag Lag
Customers Non- customers

Committed Uncommitted Open Unavailable
3

Entrenched Average Weakly Strongly
Shallow Convertible Available Ambivalent
committed committed unavailable unavailable

1 2

Management tampers with the Leading to floundering
system

Summary and conclusions

A main theme of this series of papers is that branding banks can only be attempted
through a consistent pattern of decisions taken throughout the organisation at a process
level of detail. In the first paper in this series I argued that:

 shareholder value should be the goal of the system;
 process design should take into account measurement of how changes in
customer perception affect shareholder value; and
 this can occur through disciplined process design in a systems context.

26


In the second paper, I argued that:

 customer’s should be managed as ‘segments of one’;
 customer behaviour, commitment and value should be independently measured
by systematic but flexible segmentation strategies;
 commitment, as defined by the Conversion Model™, is the primary measure of
customer satisfaction that should be used by a bank;

In this paper, I describe how:

 personal experience if the main driver of perception of a bank;
 customer banking behaviour is affected by discontinuities in their perceptions that
are sometimes difficult to understand, measure and predict; and
 these discontinuities are caused by breaking inertia in the mindsets of customers.
 management response can easily allow the natural variation in perceptions of the
brand;

My conclusion is that this kind of issue is inevitably part of the nature of banking
unless deeply held mental models are changed. Part of the purpose of this series of
papers is to contribute towards that change.

In the next paper in this series I shall focus on brand itself and why effective
branding is essential for banks.

27


Appendix 1

Research for Innovation
Geoffrey Johns January 2003

"Business has only two basic functions: marketing and innovation.
Marketing and innovation produce results. All the rest are costs."
Peter Drucker

Does Market Research have a Part to Play in Innovation?

We often hear of successful product innovations that took place without any market
research. Akio Morita, The Chairman of Sony, is quoted as saying that the Walkman
would never have been launched had they relied on market research. Probably, this
would go for many other product innovations from fax machines to mobile 'phones.
Nobody saw the need until they were out there in the market.

The magazine "Fast Company" tells the stories of many firms with "skunk works" or
"chief ideas officers". Mostly, they work towards innovation from an understanding of
the developing capabilities of technology. Firms try to generate as many viable projects
as possible while limiting the role of users in development to the sifting and evaluation
technology process. Indeed this is how the market research is traditionally seen in the
product development cycle.

The exhibit below sets out a traditional view of the product development cycle. Users
are traditionally involved in the testing stage. Once a prototype has been developed,
potential users evaluate it. This has some sense to it. It is difficult, in many cases, for
existing users to predict how they will react to circumstances that are barely on the
radar screen. For example, 1970s users of landline telephones would not readily have
predicted text messaging.

The product development
OPPORTUNITY
IDENTIFICATION cycle
Market definition (Source: Urban and Hauser)
Idea generation

Professor Eric Von Hippel‟s
DESIGN commentary
Consumer
measurement
Perceptual
mapping
Product positioning TESTING
Forecast sales Advertising and
Marketing mix product testing
Pretest market
forecasting
Test marketing INTRODUCTION
Launch planning
Tracking the launch

Innovative Innovative Traditional PROFIT
customer MANAGEMENT
customer customer
involvement Decision support
involvement involvement system
Market response
analysis
Innovation at
maturity
Profit portfolio
Management

28


How then can market research help managers in the innovation process? The answer, or
part of the answer, lies in lead user research.

Lead User Research

Lead users (sometimes called "lead steers" because they are the people who both
predict and guide the movement of the "herd lead the followers towards new concepts
and ways of meeting their needs. Lead User research was pioneered by Eric von Hippel,
Professor of Technology at the MIT Sloan School of Management in 1986. I have
developed this work for use as a market research tool that offers a systematic approach
to innovation.

This is not the only approach for every business. Some businesses will launch many
products and invest in developing the ones that work. Others will watch the success of
smaller and nimbler competitors and buy the ones that succeed. Still others will bet the
business on a single bright idea. Having said that, the approach we describe in this
paper should be considered by many businesses. This is especially of businesses that
have a powerful brand that must be nurtured. They have less scope for constant
experimentation. It is also true of complex, multifaceted businesses where the
management functions of control and coordination make a freewheeling corporate
culture harder to integrate.

Who are lead users and why do they matter?

The Exhibit below is based on Everett Rogers' conceptual illustration of the diffusion of
an innovation in the marketplace (Diffusion of Innovations 1995). To Rogers' diffusion
segments I have added Von Hippel's concept of Lead Users. It is important to
understand that Lead Users differ from Early Adopters in important ways. An Early
Adopted will see an innovation and think "Yes, that's for me!" A lead User, however, has
already begun to develop the product in his or her own mind. Indeed often they will
have developed a prototype or perhaps a "work around" solution to their needs. The key
fact about a Lead User is that their need for a solution is so great that they have already
begun to imagine solutions. They have "one foot in the future" already. Note: it is the
need that matters more than they specific solution. But it should be a need that can be
articulated so strongly that the passage towards the solution becomes almost seamless.

29


Early
adopters

Mass
market
Adoption

(followers)
Laggards
Lead
users

Time

Lead users matter for two reasons:

 What they want today Early Adopters may want tomorrow and the Mass Market the
day after; and

 They can help us build a viable solution.

Often we can survey the traditional market broadly and find that a big majority are quite
happy with what they have now. The trick is to home in on those that demand
something more.

Why not ask all users what they need?

Most importantly because they don't know. They great majority of people cannot
imagine the products and services that they will require in the future. In research
studies, people will mostly try to be helpful. However, they will think within the box of
what they get now. If they articulate requirements at all it is along the lines of - the
same but faster, cheaper, better. That road leads to commoditisation and trench
warfare against competitors trying their hardest to do pretty much the same.

Shortly, we will describe how to discover Lead Users and deploy their skill and
understanding. Before this, however, we must introduce the concept of "commitment"
based on TNS's proprietary methodology The Conversion Model™.

30


Introducing Commitment Segments into the Innovation Research Model

Do Lead Users tell the whole story? No, not if we want to understand the rate of take up
of the new offering. Understanding the needs of Lead Users can help us design a
product. However, financial evaluation requires that we make some estimate of the
spread from the small number of Lead Users to Early Adopters and from them to the
Mass Market. The rate of take up is crucial. Rogers' stylised adoption curve shown
above is only a generalisation of the experience of some typical markets. In any given
case we know little about how take up might spread from Lead Users to Early Adopters
and from them to the Mass Market. We need to understand the responses of committed
and uncommitted customers to measure and manage take up.

Commitment is a concept used in the TNS Conversion Model. This is a methodology
used to measure the shift in customers between alternative brands and products. In this
model a committed customer is one that:

 is satisfied with the brand they use at present;

 does not rate alternative brands highly;

 show no ambivalence between brands; and

 is involved in the decision, in that it matters to them which brand to choose.

The exhibit below illustrates the segments into which we group a brand's customers and
non-customers according to their commitment. While we usually focus on brands we
have also analysed other aspects of a category, for example, various distribution
channels. Two questions are relevant here.

 If users want the innovation, do they want it from your brand? And

 How quickly will take up spread from more to less committed customers.

Customers

Committed - Committed - Uncommitted - Uncommitted
entenched average shallow convertible

Weakly Strongly
Available Ambivalent
unavailable unavailable

Non customers

31


A committed customer is more likely to:

 stay with the brand longer;

 be less price sensitive;

 buy more of the brand's product / service set; and

 be more aware of and give more consideration to the brands marketing
communications.

For our present purpose, a committed customer is more likely to accept an innovative
product.

In the present context, therefore committed customers are more likely to accept the new
product offering. Moreover, they are more likely to accept the new product offering
under the brand under consideration. We need to include both high committed and
uncommitted customers in our focus groups. Committed customers are likely to be early
adopters of the proposed products but may be unrepresentative of other customers. By
using the Conversion Model to segment existing and potential customers by their level of
commitment, we can better predict rates of take up.

Committed followers will
Committed

be influenced by
If this group accepts the
commited leaders. The
concept they will be the
rate of penetration will
earliest adopters
depend on the leaders'
span of influence
Uncommitted

Acceptance by
committed leaders will
allow some penetration
Uncommitted followers
of uncommitted leaders.
are likely to be laggards
The rate of penetration
will depend on the
strength of the offering

Followers Leaders

32


Each of the groups illustrated above will have a different rate of "take up". Each will be
influenced by the others. To get a better view of the rate of take up, we need to
understand the unique perceptions and behaviour of each.

Digging deeper into rates of take-up

I have developed a conceptual model to help us organise research information about the
commitment segments. The framework is shown in the exhibit below.

Attractors

Triggers Behaviour Enablers

Repellers

Attractors are factors that draw users towards an innovation. They can include, for
example:

 Superiority over existing offerings.

 Fit with lifestyle, aspirations, self-image.

Repellers are factors that drive users away from an offering. They can include, for
example:

 Perceived risk.

 Switching costs, including time, money and perceptions of sunk costs.

Triggers are factors that can prompt adoption. They can include for example, for
example:

 Opportunities to trial.

33


 Opportunities to observe successful users.

Enablers are things that must be available to the potential user for them to adopt the
innovation. For, example, in the case of on-line banking, these include ready access to
an Internet connected PC.

Research into this adoption model fleshes out the drivers behind the commitment
segments and allows take up rates to be modelled more effectively. The forces we
describe above are not necessarily objective reality. We are concerned only with the
users perception of them.

The search for Lead Users

How do we select the sample? There is no one answer for every study. We need to
redefine the selection criteria a little differently each time. As a guide, however, Lead
Users meet the following criteria. They are:

 Successful.

 Respected by their peers.

 Opinion formers.

 Good networkers.

 Sophisticated users of products in the category in question.

 Early adopters of new products.

 able to think outside the square.

 people who seem to have one foot in the future already.

 demanding and driving clients.

And, for business users. also

 highly in touch with the needs of their own clients (where they are businesses).

 committed to their own success and the growth of their businesses.

 people who are building an organisation rather than just running a business.

But, above all else, what we are truly seeking are users who:

 Have needs that foreshadow general demand - that is to say they are pushing the
envelope of what the existing products offer them.

 Expect to get high benefit from solving those needs so they are inclined to invest
their time, energy and money in innovative solutions.

“It was something I needed at my work” Tim Berners-Lee

34

Branding Banks For Shareholder Value 3.0 Customer Perceptions

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