A Customer-Centric Approach to Community Bank Growth


{Click here to view this whitepaper in pdf format}
 

Customer-Centric Versus Product-Centric

Community banks are uniquely positioned to manage their customer portfolio in a focused
manner due to the very nature of their business. The market for community bank services
is usually well defined with a majority of their customers coming from the area immediately
surrounding the bank or branches. Community bank services also tend to appeal to a certain
segment of the population. This population is not interested in all the services a national or
regional bank offers and is typically seeking a more stable, personal banking relationship.
Conversely, some national bank customers are not interested in the limited services offered
by a community bank such as limited ATM locations. This very nature makes it possible for
the community bank to outmaneuver the big banks by better targeting customers in their
community.

Banks in general tend to be more product-centric than customer-centric. Their focus is on
launching new products and services versus focusing on how they can better manage or
serve their different customer segments. If you lined up the marketing collateral and
websites from several community banks and removed the bank name from each, you would
find that the messages are very similar across the board:

"…we are focused on the community…"
"…we put the customer first…"
"…we build solid relationships…"

The challenge then becomes how to get the message heard in a crowded marketplace offering
commodity products.

Organizations that focus on satisfying the customer’s needs will not only experience growth in
their customer portfolio, but a customer-centered approach also results in superior financial
performance for the organization (Footnote 1). This study only analyzes how information
can be utilized to influence the organization’s contact strategy, but a complete customer-
centric implementation also involves computing customer profitability and developing a
behavior-based customer segmentation schema for managing the customer portfolio.

A customer-centric approach to growth varies dramatically from a product-centric approach.
Based on Jay Galbraith’s Star Model (Footnote 1) an organization is comprised of five dimensions:

  • Strategy: the direction the organization is headed;
  • Structure: where decision-making is located throughout the organization;
  • Processes: how information flows through the organization;
  • Rewards: how people are motivated;
  • People: the mindsets and skills of the employees.

Some of the key differences between a product-centric organization and a customer-centric one
include (Footnote 1):

Table 1 – Galbraith Star Model Product-Centric Versus Customer Centric Organization Comparison

Dimension

Concept

Product-Centric Organization

Customer-Centric Organization

Strategy

Goal

Best product for customer

Best solution for customer

 

Main offering

New products

Personalized solutions

Structure

Organizational concept

Profit centers

Customer segments, teams, etc.

Processes

Most important process

New product development

Customer relationship management

Rewards

Measures

Number of new products

Customer share of wallet

   

Market share

Customer retention

People

Mental process

How many possible uses for products

What combination of products is best for customer

 

Culture

Open to new product ideas

Searching for more customer needs to satisfy

With a product-centric mindset so deeply ingrained in so many organizations, it’s no wonder why
many find it so difficult to make a change to become customer-centric.

For an organization to create the best solution for a customer, they have to focus on identifying
and satisfying the customer’s needs as opposed to how they can sell them a new product. This
starts with understanding who the customers are and marketing to them based on that information.
Only then can that organization deliver an effective ‘customer experience’. As previously mentioned,
this will result in improved profitability as the organization develops a deeper relationship with the
customer which leads to more products/solutions purchased. Additionally, the organization will
benefit from lower acquisition costs since marketing would be better targeted based on prospects
likely to respond to the message and not just anyone who lives and breathes. Lastly, the
organization will enjoy a longer lasting customer relationship since it would be focused on satisfying
that customer’s needs versus selling them a new product.

Customer Location Analysis

This study includes data and analysis from the metropolitan Chicago community bank market.
Chicago is a unique market at this time for several reasons:

  • it has one of the highest community bank growth rates in the United States;
  • there is a high incidence of national and regional banks also entering the market;
  • the market is still considered ‘underserved’ by several banking groups.

Consequently, the marketplace is focused on attracting new customers by offering ‘Free
Checking’ and other low/no margin products and services as the primary acquisition tool.

Branch Proximity Analysis

The first step in this process is to understand how community dependent the community bank
is. To discover this, a branch proximity analysis was performed. This analysis will determine what
percentage of the branches customers are located in their immediate and adjoining zip codes.
We utilized a stratified sample of zip code data for 10 branches of a community bank. For the
bank we studied, and based on conversations with other banks, most of a community bank’s
customers are concentrated in the branches’ zip code or adjoining zip codes. In particular, we
found that in 8 out of 10 cases, over 50% of the customers fit this criterion. For these 8
branches, the customer concentration ranged from a low of 62% to a high of almost 99%. The
two branches without customer concentrations over 50% where still significant, with respectable concentrations of 43% each. Branches A thru E are suburban locations, while Branches F through
J are urban locations.


Figure 1 - Customer Proximity Analysis

With this information, the bank can examine the census demographic data for the branch area
and focus their customer contact based of this information. The census data can be an effective
alternative to purchasing individual level demographic data. Additionally, it will help the organization determine if further analysis is required. If the census data did not reveal any significant variances
between branch areas, then no further work is warranted. But, as in this case, the census data
revealed considerable variances, further analysis should be performed and an investment in
individual level demographic data might be warranted.

The analysis found that there are significant differences in the demographic composition of
the population in these zip codes. Some of the key variables to focus on include household
income, household size (presence of children), rent versus own and race.

Table 2 – Branch Customer Demographic Comparison

Suburban Locations

Branch

A

B

C

D

E

% of Family Households w/Children

45%

46%

34%

39%

45%

 

 

 

 

 

 

College: Bachelor's Degree

38.30%

10.40%

7.10%

26.30%

21.40%

College: Graduate Degree

26.60%

5.80%

2.40%

12.40%

9.30%

 

 

 

 

 

 

Asian Population

6.80%

1.80%

2.20%

9.30%

1.30%

Black Population

0.60%

22.20%

0.90%

7.80%

2.00%

White Population

91.10%

65.00%

87.20%

77.50%

92.80%

Hispanic Ethnicity

2.90%

14.00%

9.30%

8.80%

6.00%

 

 

 

 

 

 

Median Household Income

$114,964

$48,337

$42,917

$62,944

$69,639

Per Capita Income

$52,397

$19,016

$18,341

$26,435

$27,030

 

 

 

 

 

 

Income Households by Income

 

   $150,000 - $199,999

14.70%

1.50%

1.50%

3.60%

3.50%

   $200,000 +

21.00%

1.20%

0.40%

2.60%

2.60%

 

 

 

 

 

 

Owner-Occupied Housing Units

91.50%

62.30%

73.50%

68.10%

82.60%

Renter-Occupied Housing Units

6.40%

32.40%

23.10%

29.00%

12.80%

 

 

 

 

 

 

Median Owner-Occupied Housing Value

$383,445

$120,696

$132,293

$159,515

$168,589

 

Urban Locations

Branch

F

G

H

I

J

% of Family Households w/Children

11%

37%

32%

19%

20%

 

 

 

 

 

 

College: Bachelor's Degree

44.20%

18.00%

7.80%

23.70%

24.20%

College: Graduate Degree

34.00%

10.00%

3.40%

15.10%

15.00%

 

 

 

 

 

 

Asian Population

3.70%

17.20%

0.70%

13.40%

12.50%

Black Population

4.80%

3.90%

8.00%

19.20%

18.10%

White Population

87.60%

55.50%

82.80%

52.90%

54.10%

Hispanic Ethnicity

87.60%

55.50%

82.80%

52.90%

54.10%

 

 

 

 

 

 

Median Household Income

$69,311

$40,212

$45,151

$33,264

$34,495

Per Capita Income

$63,791

$17,321

$19,604

$22,217

$21,027

 

 

 

 

 

 

Income Households by Income

 

   $150,000 - $199,999

7.20%

1.20%

1.20%

1.80%

1.00%

   $200,000 +

13.70%

1.80%

0.60%

1.70%

1.40%

 

 

 

 

 

 

Owner-Occupied Housing Units

38.60%

30.30%

76.20%

22.50%

30.60%

Renter-Occupied Housing Units

57.10%

65.20%

21.30%

71.40%

64.10%

 

 

 

 

 

 

Median Owner-Occupied Housing Value

$348,495

$199,033

$137,593

$184,177

$140,392

An examination of the census data reveals variances that should impact on a bank’s
communication strategy, customer management strategy and acquisition strategy. We’ve
highlighted the highest and lowest values for each data element. A discussion of how this
information might impact strategies follows:

  • Households with Children – Since bank product purchases are largely driven by
    lifestage events, it would make sense to communicate with the customers from
    Branches A and B about college funds versus customers from branch F or I.
  • College Degrees – Customers with college degrees tend to earn more and conse-
    quently will likely be more interested in CDs, retirement funds, etc.
  • Race – The marketing collateral, communication pieces and website should reflect
    the racial diversity of the bank’s customers. Creating marketing collateral for individual
    branch areas is probably not cost effective, but digitally printed communication pieces
    can be targeted to the population in the area.
  • Income – It should be no secret that a customer earning over $100,000 per year
    is going to be interested in a different set of products than a customer earning
    under $50,000.
  • Owner versus Renter Occupied – Renters will be at a different lifestage than a
    customer or prospect that owns their residence. Therefore, the products/solutions
    they will be interested in purchasing will be different.
  • Housing Value – Again, the customer with a $350,000 home is not typically looking
    for just a free checking account.

Share of Wallet

This data can also be used for a high-level share of wallet examination. For example, if a
customer only has a free checking account with your Bank A and the customer is located
in an area with high housing values, high income earners and high concentration of children,
that customer either hasn’t begun preparing for the rest of his/her life or their other accounts
are with other banks and financial institutions. It is up to the banker to find out which case
is true. Under either circumstance, it represents an opportunity for the bank. This is especially
true for long-term customers who haven’t gone past the original free checking account. Their
money is probably in other institutions.

Next Steps

This is an example of how a little bit of information can be very powerful if put in the right
hands. The proximity analysis is not very difficult. Start with a sample of data and if the
direction of the data supports customer concentration, then complete the analysis for the
entire customer population. Once concentration can be verified, use the free census data
to compare the demographics of the populations around the branch locations. Use the
demographic data to find the attributes that "stick out" or aren’t consistent with the data
around it. With this information, the bank can begin crafting communication strategies that
better fit their target audiences. This entire process is quick and inexpensive.

With this information as a solid foundation, the bank is on the path to customer-centricity.
Customers tend to spend more money at places they have an affinity to. Therefore, several
actionable can be taken by the bank, including:

  • changing the marketing collateral to reflect the diversity of the population the bank
    serves;
  • changing the pictures inside the branch to reflect the population the branch primarily
    attracts;
  • changing the website to reflect the population diversity and/or create customized
    landing pages and microsites that reflect the branch’s population demographics;
  • with the availability of digital printing, customized mailing pieces can be sent to
    each branches customer population;
  • understand the cultural differences of the population the branch is serving and cater
    to them. For instance, some ethnic groups treat going to bank as a family event and
    will bring the entire family in just to open a checking account. That represents a great
    opportunity to not only sell additional bank products/solutions, but also have staff prepared
    to capitalize on the situation with gifts for the children for example.
  • Next, is a deeper ‘dive’ into the data by examining customer profitability and segmentation.
    With a thorough understanding of who your customers are and which ones are more profitable,
    the bank can become a finely tuned, information rich customer-centric organization.

    (1) Galbraith, Jay R. Designing the Customer-Centric Organization: A Guide to
    Strategy, Structure and Process. Jossey-Bass, San Francisco, CA (2005)

    {Click here to view this whitepaper in pdf format}

     

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    Comments

    • 1/8/2008 3:20 PM Tom K wrote:
      I read the Customer-Centric Approach article and I liked it. I find that many companies still don’t understand the value of understanding their customers’ needs and wants before embarking on a new products study.
      Reply to this
    • 1/8/2008 3:25 PM Erick L wrote:
      Good information!
      Reply to this
    • 1/8/2008 7:00 PM M Redding wrote:
      Thank you for sharing this information. Being in the banking industry, the article truly resonated with me.
      Reply to this
    • 4/24/2008 7:36 PM Don Drews wrote:
      I had not seen the Star Model before, which was thought provoking. But the table comparing product-centric vs. customer-centric organizations on the five dimensions was excellent. Very clear contrasts--and it added richness to the idea of what customer-centric would really feel like. Unfortunately, it also confirmed Bryan's point about the magnitude of change required to get there. However, keep pushing!
      Reply to this
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