industrial segmentation and how to segment in matured markets

7/29/2019 Industrial Segmentation and How to Segment in Matured Markets

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Value analysis, as developed by General Electric, involves a step-by-step

procedure:

1. Selection. A product that is ripe for improvement is selected for valueanalysis.

2. Information gathering. Drawings, costs, scrap rates, usage forecasts,

and operations sheets are collected by the team coordinator before the

team first meets. Team members are asked to send in whateverinformation they have.

3. Function definition. The team meets and defines each function of the

product. A function is defined in two words, a verb and a noun (e.g., a

flower pot contains soil). Only essential functions are included. Next theteam determines the present cost of each function. This reveals which

functions represent major expenditures.


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4. Generation of alternatives. Team members suggest ideas for new and different

ways to accomplish the functions. This is known as brainstorming. All ideas

are recorded and later culled to a list of manageable size.

5. Evaluation of alternatives. Alternatives are evaluated or various factors,

including feasibility and cost. This further reduces the list to one or two

good ideas.

6. Presentation. The final alternatives are refined and presented to a management

into an analysis change proposals.

7. Implementation. The approved value analysis change proposal is translatedinto an analysis change order and implemented.


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MAJOR SEGMENTATION VARIABLES

FOR INDUSTRIAL MARKETSDemographic

Industry : which industries that buy this product should we focus on ?

Company size ; what size companies should we focus on ?

Location : what geographical areas should we focus on ?

Operating Variables

Technology : what customer technologies should we focus on?

User/non-user status : should we focus on heavy, medium, light users or non-users?

Customer capabilities : should we focus on customers needing many services or few services?

Purchasing Approaches

Purchasing function organization : should we focus on companies with highly centralized ordecentralized purchasing organizations?

General purchase policies: should we focus on companies that prefer leasing ? service contracts? systemspurchases? sealed bidding?

Purchasing criteria; should we focus on companies that are seeking quality? service ? price?

Situational Factors

Urgency ; should we focus on companies that need quick and sudden delivery or service?

Specific application : should we focus on certain applications of our product rather than all applications?

Size of order: should we focus on large or small orders?

Personal Characteristics

Buyer-seller similarity: should we focus on companies whose people and values are similar to ours?

Attitudes toward risk: should we focus on risk-taking or risk-avoiding customers?

Loyalty: should we focus on companies that show high loyalty to their suppliers?


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SUPPLIERS BUYERS FACILITATORS MARKET SEGMENTS

Company

Manufacturers

Distributors

Dealers

Competitors

Manufacturers

representatives

distributors/dealers

Transportation firms

Advertisingagencies Marketing

research firms Banks

and insurance companies

Government

Users

Commercial

Market Enterprises OEMS

Industrial

distri-

butors

Institutions

Labor

Capital

Raw materials

Component parts

Equipment


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Market Segmentation Target Marketing Product Positioning

1. Identify measurable,

relevant, and operational

variable for segmenting the

market.

2. Define macro profiles of

resulting segments.

3. Define micro profiles of

resulting macrosegments

1. Evaluate resulting

macro/micro segments:

a. Profitability analysis

b. Competitive analysis

2. Decide on market coverage:

a. Undifferentiated

b. Differentiated

c. Concentrated

3. Select the target

segments(s).

1. Develop product/ marketpositioning for each

target market

selected.

2. Develop marketing mix

for each target market

selected.

FIGURE B-1 A Market segmentation and product positioning Model


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TABLE 8-1 Some Macro Variables Used to Segment the Industrial Market

Variables Examples

Industry Agriculture, mining, construction, manufacturing,

transportation, wholesale, retail, finance, services

Organizational characteristics

Size characteristic Size of customers parent company, size of customers

business, and number of plants sold

Plant characteristics Size of customers plant, age of customers plant,

inventory turnover, and degree of automation

Location Distance from plant, state of plant, and suburban/

urban/ rural location


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Economic factors Cyclicality of customers industry

Customers industry Growth rate of industry and customers growth stage within

the industry; ultimate customer of customers product

Competitive forces Degree of competition in customers industries, ease of

entry in to customers industries, and ease of customer

switching

Purchasing factors Decentralized versus centralized, and number of levels of

purchasing authority

End-use markets Residential/ commercial contractors, coal/ore miners, foresters,

federal/ state highway maintenance departments, banks/insurance/ brokerage houses

Product application Small appliance, computer, television, and airplane

manufacturers


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Segmenting Customers in MatureIndustrial Markets : An

Application

Segment is the art of identifying distinctive customer groups that

exhibit homogeneous needs. The point of segmentation is to be

able tailor the marketing mix to address the unique needs of the

various segment. A Number of bases for segmentation have beenoffered in the literature, including.


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Demographic descriptors such as geography, standard

industrial classification code, and account size;

Product end-use or application;Buying situation;

Customer decision-making style;

Customer buying behavior ; andCustomer benefits


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Figure 1: Potential Buying Behavior Segment

High

Price

Low

Low High

Value

Axis

Market

PowerAxis

Cost-to-Server


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SEGMENTATION VARIABLE

FOR KEVLARFor potential fishing boat owners: Kevlers lightness

promised fuel savings, increased speed, and the ability to

carry fish weight.For aircraft designers: Kevlar had a high strength-to-

weight ratio.

For industrial plant managers: Kevlar could replace the

asbestos used for packing pumps.


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Buying Behavior Variables From

In-House Documents1. Relative Pricewas a measure of the higher of the lower

price that an account paid relative to Signodes other

national account. Average discount ranged from 0% to as

much as 11.3%.

2. Relative Service was a measure of the higher of the lower

service that an account received relation to other national

account. Signodes managers identify three important

component in service 1)field sales calls, 2) unbilled parts,tools, and repair work and 3) application and engineering

service.


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3. Account Size: While various aspects of account size

have been identify as influencing buying behaviors. Wemeasured account size simply as the total purchase

volume of all Signode products in the most recent 12

month.

4. Market Share: A deferent measure of dependency is asingle suppliers proportion of business in the buyers

total purchase of a product catalog. We measured this

as Signodes share of dollar sales volume for each

account .Knowing Signodes actual sales to the

account, we computed Signodes market share- an

indicator of the buyers preference for, as well as

reliance on, Signodes product.


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Buying Behavior Variables FromNational Account Reps and NAMs

5. For decrease in price

6. For increase in price

7. For decrease in service

8. For increase in service

9. Product importance : Depending on theapplication

extent of usage, the importance of steel strapping

varied over Signodes national accounts.


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10. Switching potential: Over the years several customers

had built a trusting relationship with Signode because of

the product of the product or the service or both

11. Market knowledge: Regardless of the stage of market

maturity, customers very substantially in their knowledge

of competitive product and prices, they search forinformation in varying degrees.

12. Decision-Making Process (DMP): The complexity of the

buying decision-making process is a reflection not only of

product and vender characteristic but also of the buyingorganizations priorities and purchasing strategies.


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Mean values of the buying behavior variables are shown for each

microsegment in Table 2

Table 2 Group Means

Behavior

Surrogates

Segment 1

# of

Accounts =54

Segment 3

# of

Accounts =22

Segment 4

# of

Accounts =11

Segment 2

# of

Accounts =65

0. 0%

3. 6

$122,000

54. 2%

5. 6

15. 5

-7. 9%

4. 9

$472,000

67. 8%

8. 9

27. 9

-10. 1%

5. 6

$1,100,000

71. 9%

8.7

24. 5

-11. 3%

7. 1

$2,100,000

68.3%

11.8

22. 7

1. Relative price

2. Relative service

3. Account size (sales)

4. Market share

5. Percentage increase in sales

for price drop

6. Percentage decrease in sales for

price raise


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Behavior

Surrogates

Segment 1

# of

Accounts =54

Segment 3

# of

Accounts =22

Segment 4

# of

Accounts =11

Segment 2

# of

Accounts =65

5. 1

1. 2

2. 5

3. 8

4. 0

3. 2

9. 2

3. 0

3. 0

4. 4

4. 5

3. 6

12. 5

5. 2

3. 5

4. 5

4. 6

3. 3

12. 3

7. 3

3. 5

4. 6

4. 7

3. 4

8. Percentage increase in sales for

services raise

7. Percentage decrease in sales

for services drop

9. Product importance

10. Switching potential

11. Market Knowledge

12. DMP complexity

Notes: Of the 161 complete data records, the clustering algorithm omitted nine cases as

outliers. 5 and 6: this is percentage increase or decrease in sales for a 7% price change. 8 and

9 this is percentage increase or decrease for a unit of service change.


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Decreasing price is unprofitable for Signod because the estimated

increase in sales is far below the required 20% for every microsegmentin Table 2 (see row 5 in Table 2).

Increasing price is profitable programmed buyer microsegment-

sales decrease of only 15.5% compared with a break-even of 20%. It

exceeds the break-even number for all other microsegments (see row 6

in Table 2).

Decreasing services is profitable programmed buyer microsegment

because the estimated sales drop in 5.1%. It exceeds the break-even of

8% in all other segments (see row 7 in Table 2); and

Increasing service is barely profitable in the bargain huntermicrosegment-sales increase of 7.3% compared with a break-even of

8%. It is far below this number for all other microsegments (see row 8

in Table 2)


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Buying Behavior Microsegments

1. Segment 1:Programmed Buyers. Customers in themicro segment were small and viewed the product as a

routine purchase item. They had the lowest average sales

of any group and were not particularly price or service

sensitive. Compared to those in the other three microsegment, these customers had the lowest market share of

Signode products.

2. Segment 2 :Relationship Buyers. Customers in this

micro segment were also relatively small. The product itself was moderately important in their operations, and

unlike the programmed buyers of segment 1, they were

more knowledge about competitive offerings.


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3. Segment 3 :Transaction Buyers. Customer in themicro segment were, on average, twice as large as the

relationship buyer. They received price discounts

averaging about 10% and an above-average service

level; they had the highest sensitivity to decreases in

services.

4. Segment 4 :Bargain Hunters. Customer in the

micro segment were large-volume customers that

received the largest price discount (averaging 11.3%)

as well as the highest level of services.


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Figure 2 : Segment Profile

0%

(discount)

Relative

Price

-11.3%

(discount)

Value

Axis

Market

Power

Axis

Segment # 2Relationship

Buyers

Sales = $31 million

Segment # 3

Transaction

Buyers

Sales = $25

million

Segment # 4

Bargain Hunters

Sales = $ 23million

Core Product

Buyers

Augmented

ProductBuyers

0 2.5 5 7.5 10

Segment !


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ConclusionFollowing the analyses at Signode, we believe that even a simple framework,

such as the two-dimensional plot of price versus cost-to-server in Figure 1, is

capable of unearthing a rich subsegment of behaviors in industrial accounts. As

can be seen from the figure, the diagonal equates the price to cost-to-server for

the seller. We hypothesize that the sellers profit would be roughly equal for

accounts located on this axis- when customers want services (augmented

product), they are welling to pay higher prices. The cross diagonal, howeverrepresents an axis of product differentiation. Clearly, customer who demand

and get high level of services for low prices must have alternatives, just as

those customer who pay high prices most find the product attractive even

though they do not receive the full battery of services. Obviously, the sellers

profit are likely to be higher in the northwest and lower in the southeastquadrant compared with the diagonal axis. Understandably, the segment

descriptor variable and dimensions are likely to very across applications, but

nevertheless a few variables could provide rich diagnostics for management

actions.