SUHAS ARADHYE

Module 2010

CRM – Section 3A(Customer Based Value Metrics…

Traditional, Primary & Popular)

SUHAS ARADHYE

Module 2010

Introduction to Customer Based

Marketing Metrics

SUHAS ARADHYE

Module 2010

Marketing Metrics

Marketing Metrics

TraditionalPrimary

Customer-based

Market Share Sales Growth Customer

Acquisition

Customer

Activity

Popular

Customer-based

Strategic

Customer-based

SUHAS ARADHYE

Module 2010

Traditional and Customer Based

Marketing Metrics

Traditional Marketing Metrics

Market share

Sales Growth

Primary Customer Based metrics

Acquisition rate

Acquisition cost

Retention rate

Survival rate

P (Active)

Lifetime Duration

Win-back rate

Popular Customer Based metrics

Share of Category Requirement

Size of Wallet

Share of Wallet

Expected Share of Wallet

Strategic Customer Based metrics

Past Customer Value

RFM value

Customer Lifetime Value

Customer Equity

SUHAS ARADHYE

Module 2010

Traditional Marketing Metrics

Market Share

&

Sales Growth

SUHAS ARADHYE

Module 2010

Market Share (MS)

• Share of a firm‟s sales relative to the sales of all firms –

across all customers in the given market

• Measured in percentage

• Calculated either on a monetary or volumetric basis

– Market Share (%) of a firm (j) in a category =

Where j = firm, S = sales, Sj = sum of sales across all firms in the market

Information source

Numerator: Sales of the local firm available from internal records

Denominator: Category sales from market research reports or competitive intelligence

Evaluation

Common measure of marketing performance, readily computed

Does not give information about how sales are distributed by customer

J

j

jj SS1

100

SUHAS ARADHYE

Module 2010

MARKET SHARE AND GROWTH

Market share, in strategic management and marketing is, the percentage

or proportion of the total available market or market segment that is being

serviced by a company. It can be expressed as a company's sales revenue

(from that market) divided by the total sales revenue available in that

market. It is generally necessary to commission market research(generally

desk/secondary research) to determine , although sometimes primary

research) to estimate the total market size and a company's market share.

Increasing market share is one of the most important objectives of

business.

Market Growth , An increase in the demand for a particular product or

service over time. Market Growth can be slow if consumers do not adopt a

high demand or rapid if consumers find the product or service useful for

the price level. For example, a new technology might only be marketable to

a small set of consumers, but as the price of the technology decreases and

its usefulness in every day life increases, more consumers could increase

demand.

SUHAS ARADHYE

Module 2010

Reason For Market Share

Reasons to Increase Market Share

Market share often is associated with profitability and thus many firms seek

to increase their sales relative to competitors. Here are some specific

reasons that a firm may seek to increase its market share:

Economies of scale - higher volume can be instrumental in developing a

cost advantage.

Sales growth in a stagnant industry - when the industry is not growing,

the firm still can grow its sales by increasing its market share.

Reputation - market leaders have clout that they can use to their

advantage.

Increased bargaining power - a larger player has an advantage in

negotiations with suppliers and channel members.

SUHAS ARADHYE

Module 2010

INDIA’S FOREIGN TRADE TREND

India's Foreign Trade (April-May 2009) in Rs Crore Exports during

May, 2009 were valued at Rs. 53435 crore, which was 18.4 per cent

lower in rupee terms than the level of Rs.65506 crore during May, 2008.

Cumulative value of exports for the period April-May, 2009 was Rs.

107214 crore as against Rs. 129846 crore, registering a negative growth

of 17.4 per cent over the same period last year.

Imports during May, 2009 were valued at Rs.78682 crore, representing a

decrease of 30.0 per cent over the level of imports valued at Rs. 112405

crore in May,2008. Cumulative value of imports for the period April-May

2009 was Rs. 157514 crore as against Rs. 211752 crore, registering a

negative growth of 25.6 per cent over the same period last year.

(Rs Crores)

SUHAS ARADHYE

Module 2010(Rs Crores)

Exports and Imports : (Provisional)

May April - May

Exports (incl.re-exports)

2008-2009 65506 129846

2009-2010 53435 107214

%Growth 2009-2010/ 2008-2009

-18.4 -17.4

Imports

2008-2009 112405 211752

2009-2010 78682 157514

%Growth 2009-2010/ 2008-2009

-30.0 -25.6

Trade Balance

2008-2009 -46899 -81906

2009-2010 -25247 -50300

SUHAS ARADHYE

Module 2010

Sales Growth

• Compares increase or decrease in sales volume or sales

value in a given period to sales volume or value in the previous period

• Measured in percentage

– Indicates degree of improvement in sales performance between two or more time

periods

– Sales growth in period t (%) =

where: j = firm, ∆ Sjt = change in sales in period t from period t-1, Sjt-1 = sales in period t-1

Information source

Numerator and denominator: from internal records

Evaluation

-Quick indicator of current health of a firm

-Does not give information on which customers grew or which ones did not

1100 jtjt SS

SUHAS ARADHYE

Module 2010

Primary Customer Based Metrics

Customer Acquisition Measurements

&

Customer Activity Measurements

SUHAS ARADHYE

Module 2010

Primary Customer Based Metrics

• Customer Acquisition Measurements

– Acquisition rate

– Acquisition cost

• Customer Activity Measurements

– Average inter-purchase time (AIT)

– Retention rate

– Defection rate

– Lifetime Duration

– Survival rate

– P (Active)

– Win-back rate

SUHAS ARADHYE

Module 2010

Customer Acquisition Measurements

Acquisition Rate

&

Acquisition Cost

SUHAS ARADHYE

Module 2010

Acquisition Rate

• Acquisition defined as first purchase or purchasing in the first predefined period

• Acquisition rate (%) = 100*Number of prospects acquired / Number of prospects

targeted

• Denotes average probability of acquiring a customer from a population

• Always calculated for a group of customers

• Typically computed on a campaign-by-campaign basis

Information sourceNumerator: From internal records

Denominator: Prospect database and/or market research data

EvaluationImportant metric, but cannot be considered in isolation

SUHAS ARADHYE

Module 2010

Acquisition Cost

• Measured in monetary terms

• Acquisition cost ($) = Acquisition spending ($) / Number of prospects acquired

• Precise values for companies targeting prospects through direct mail

• Less precise for broadcasted communication

Information source:

• Numerator: from internal records

• Denominator: from internal records

Evaluation:

• Difficult to monitor on a customer by customer basis

SUHAS ARADHYE

Module 2010

Customer Activity Measurements

Objectives

Managing marketing interventions

Align resource allocation with actual customer to demonstrate how knowledge

of customer activity adds to shareholder value behavior

Key input in customer valuation models such as Net-present Value (NPV)

SUHAS ARADHYE

Module 2010

Average Inter-purchase Time (AIT)

SUHAS ARADHYE

Module 2010

Average Inter-purchase Time (AIT)

• Average Inter-purchase Time of a customer

= 1 / Number of purchase incidences from the first purchase till the current time period

• Measured in time periods

• Information from sales records

• Important for industries where customers buy on a frequent basis

Information sourceSales records

Evaluation:Easy to calculate, useful for industries where customers make frequent purchases

Firm intervention might be warranted anytime customers fall considerably below their AIT

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Module 2010

Retention Rate

& Defection Rate

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Module 2010

Retention and Defection

• Retention rate (%) = 100* Number of customers in cohort buying in (t)| buying

in (t-1) / Number of customers in cohort buying in (t-1)

• Avg. retention rate (%) = [1 – (1/Avg. lifetime duration)]

• Avg. defection rate (%) = 1 – Avg. Retention rate

• Avg. retention rate (%) = 1 – Avg. defection rate

• Avg. lifetime duration = [1/ (1- Avg. retention ratet)

• Assuming constant retention rates, number of retained customers in any

arbitrary period (t+n) = Number of acquired customers in cohort * Retention

rate (t+n)

• Given a retention rate of 75%, variation in defection rate with respect to

customer tenure results in an average lifetime duration of four years

SUHAS ARADHYE

Module 2010

Retention and Defection-Example

• If the average customer lifetime duration of a group of customers is 4 years,

the Average retention rate is 1- (1/4) = 0.75 or 75% per year. i.e., on an

average, 75% of the customers remain customers in the next period

• The effect for a cohort of customers over time – out of 100 customers who

start in year 1, about 32 are left at the end of year 4

Customers starting at the beginning of year 1: 100

Customers remaining at the end of year 1: 75 (0.75*100)

Customers remaining at the end of year 2: 56.25 (0.75*75)

Customers remaining at the end of year 3: 42.18 (0.75*56.25)

Customers remaining at the end of year 4: 31.64 (0.75*42.18)

Assuming constant retention rates, the number of retained customers at the

end of year 4 is 100*0.754 = 31.64. (Number of acquired customers in cohort *

Retention rate (t+n) )

The defection rate is 1-0.75 = 0.25 or 25%

SUHAS ARADHYE

Module 2010

Life Time Duration

& Survival Rate

SUHAS ARADHYE

Module 2010

Customer Lifetime Duration

• Average Lifetime duration = Customers retainedt * Number of periods / N

Where: N = cohort size, t= time period

• Differentiate between complete and incomplete information on customer

– Complete information - customer‟s first and last purchases are assumed to

be known

– Incomplete information- either the time of first purchase, or the time of the

last purchase, or both are unknown

T

t 1

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Module 2010

• Customer relationships

– Contractual (“lost-for-good”): Lifetime duration is time

from the start of the relationship until the end of the

relationship (e.g.: mobile phone contract)

– Non-contractual (“always-a-share”): Whether

customer is active at a given point in time (e.g.:

department store purchase)

– One-off purchases

Customer Lifetime Duration (contd.)

SUHAS ARADHYE

Module 2010

Customer Lifetime Duration when the

Information is Incomplete

Buyer 1

Buyer 2

Buyer 3

Buyer 4

Observation window

Buyer 1: complete information

Buyer 2 : left-censored

Buyer 3: right-censored

Buyer 4: left-and-right-censored

SUHAS ARADHYE

Module 2010

Variation in Defection rate with respect to

Customer Tenure

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Customer tenure (periods)

# o

f cu

sto

mers

defe

cti

ng

Plotting entire series of customers that defect each period, shows variation (or

heterogeneity) around the average lifetime duration of 4 years.

SUHAS ARADHYE

Module 2010

Change in Customer Lifetime Duration

with Retention Rate

0

4

8

12

16

20

50% 55% 60% 65% 70% 75% 80% 85% 90% 95%

Retention rate

Av

erg

ae C

usto

me

r Lif

etim

e

(peri

ods

)

Note: increasing the marginal retention rate is likely to be increasingly expensive

SUHAS ARADHYE

Module 2010

Survival Rate

• Measured for cohorts of customers

• Provides a summary measure of how many customers survived between the

start of the formation of a cohort and any point in time afterwards

• Survival ratet (%) = 100*Retention ratet * Survival ratet-1

• Number of Survivors for period 1 = Survival Rate for Period 1 * number of

customers at the beginning

SUHAS ARADHYE

Module 2010

Survival Rate Computation-Example

Number of Customers starting at the beginning of year 1: 1,000

Retention rate Survival rate Survivors

Period 1: 0.55 0.55 550

Period 2: 0.62 0.341 341

Period 3: 0.68 0.231 231

Period 4: 0.73 0.169 169

Number of Survivors for period 1 = 0.55 * 1000 = 550

Survival rate for period 2 = Retention rate of period 2 * Survival Rate of Period 1.

Therefore, Survival rate for period 2 = 0.62 * 0.55 = 0.341 (=34.1%)

SUHAS ARADHYE

Module 2010

Projecting Retention Rates

• To forecast non-linear retention rates,

Rrt = Rrc * (1-exp(-rt))

where: Rrt is predicted retention rate for a given

future period,

Rrc is the retention rate ceiling

r is the coefficient of retention

• r = (1/t) * (ln(Rrc) – ln(Rrc – Rrt ))

SUHAS ARADHYE

Module 2010

Actual and Predicted Retention Rate for a

Credit Card Company

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Period

Re

ten

tio

n r

ate

(%

)

Actual

retention rate

Predicted

retention rate

Rrc = 0.95 means that managers believe that the maximum attainable retention rate is 95%

The known retention rate in period 9 is 80% while the one in period 10 is 82%.

The parameter r for period 9 is (1/9)*(ln(0.95)-ln(0.95-0.8)) = 0.205. The r for period 10 is (1/10)*(ln(0.95)-

ln(0.95-0.82)) = 0.198. --for both periods r approximates the value 0.2.

SUHAS ARADHYE

Module 2010

Actual Retention Pattern of a

Direct Marketing Firm

1.Period

since

acquisition

2.Actual

retention rate

3.Predicted

retention rate

4.Defection

rate%

5.Survival

Rate

6.Expected

Number of

active

customers

7. Number

of

Active

periods

1 32.0% 68.0% 32.0% 2400 2400

2 49.1% 50.9% 15.7% 1178 2357

3 63.2% 36.8% 9.9% 745 2234

4 69.0% 31.0% 6.9% 514 2056

5 72.6% 27.4% 5.0% 373 1865

6 76.7% 23.3% 3.8% 286 1717

7 77.9% 22.1% 3.0% 223 1560

8 78.5% 21.5% 2.3% 175 1400

9 79.0% 21.0% 1.8% 138 1244

10 80.0% 20.0% 1.5% 111 1106

11 79.7% 20.3% 1.2% 88 969

12 79.8% 20.2% 0.9% 70 844

13 79.9% 20.1% 0.7% 56 730

14 79.9% 20.1% 0.6% 45 628

15 80.0% 20.0% 0.5% 36 538

Cohort of 7500 customers at the outset, maximum retention rate is 0.80 and the coefficient of

retention r is 0.5; after period 10, the company retains approximately 80% of customer base

SUHAS ARADHYE

Module 2010

P ( Active)

SUHAS ARADHYE

Module 2010

P (Active)

• Probability of a customer being active in time t

• P(Active) = Tn

Where, n is the number of purchases in a given period

T is the time of the last purchase (expressed as a fraction of the

observation period)

• Non-contractual case

For an advanced application see:

Reinartz, Werner and V. Kumar (2000): On the Profitability of Long-Life Customers in a

Noncontractual Setting: An Empirical Investigation and Implications for Marketing. Journal of

Marketing. 64 (4), October, p. 17-35.

SUHAS ARADHYE

Module 2010

Estimation of P(Active)-Example

Customer

1

Customer 2

Observation period Holdout period

Month 1 Month 12Month 8 Month 18

An x indicates that a purchase was made by a customer in that month

To compute the P(Active) of each of the two customers in the 12th month of activity

For Customer 1: T = (8/12) = 0.6667 and n = 4

P(Active)1= (0.6667)4 = 0.197

And for Customer 2: T = (8/12) = 0.6667 and n = 2

P(Active)2= (0.6667)2 = 0.444

SUHAS ARADHYE

Module 2010

Maggie Noodles

For Maggie

Noodles :

N= 4 times a

Month

T = 4 Months

SUHAS ARADHYE

Module 2010

Meaning

SUHAS ARADHYE

Module 2010

Win Back Rate

SUHAS ARADHYE

Module 2010

DEFINITION

• What is WBR !!!

A structured process for

regaining the most loyal and

profitable of the lost customers

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Module 2010

STRUCTURED PROCESS

– Analyzing of the situation (defection causes etc)

– Making a business case for Win Back (including reporting international best practice)

– Defining Win Back objectives

– Creating a Win Back strategy

– Planning the implementation (including organizational development and Win Back processes)

– Evaluating the economy and resources needed

– Measuring results

SUHAS ARADHYE

Module 2010

BENEFITS

• Realize potential sales/profits by rebuilding customer relationships

• Minimize new customer acquisition costs

• Reduce negative word-of-mouth

• Better understand the customer process for relationship termination so that appropriate intervention and recovery steps can be taken

• Develop a profile for lost customers that can help detect „at risk‟ customers

• Build customer recovery into the customer-focused culture

SUHAS ARADHYE

Module 2010

• Realize potential sales/profits by rebuilding

customer relationships

• THE CUSTOMER LIFETIME VALUE

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Module 2010

• Minimize new customer acquisition costs

COST OF AQ. NU.

CUS.>

COST OF RET. OLD

ONE

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Module 2010

• Reduce negative word-of-mouth

• NEGATIVE Word – Of – Mouth SPREADS

FASTER IN THE INDUSTRY/ CUSTOMERS

THAN POSITIVE.

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Module 2010

• Develop a profile for lost customers that

can help detect „at risk‟ customers

• DECREASE IN SALES

• Negative feedback

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Module 2010

• Build customer recovery into the

customer-focused culture

• Helps build reputation which is important

during M & A.

SUHAS ARADHYE

Module 2010

Popular Customer Based Metrics

Size of Wallet

Share of Wallet

Expected Share of Wallet

Share of Category Requirement (SCR)

SUHAS ARADHYE

Module 2010

Size of Wallet

Share of Wallet

SCR

SUHAS ARADHYE

Module 2010

Share of wallet

• % Share of a customers expenses (of wallet) for a product that goes to the firm by selling the product.

• It helps the manager to understand the amount of business a company gets from specific customer.

• Different firms fight over the share they have of a customers wallet, all trying to get as much as possible.

SUHAS ARADHYE

Module 2010

How to increase the sow

• Cross selling

• Invest in those activities which prompt

customers to do more business with the

company and every time they select your

product/service

SUHAS ARADHYE

Module 2010

Key tasks after knowing the SOW

• Exploring new means to increase the

budget and their spending.

• Profile the ideal/main customers.

• Places that need to be focused for

improvement to get competitive edge.

• To retain the best customers.

SUHAS ARADHYE

Module 2010

Calculation of SOW

• A given brand‟s share of purchase in its

category, measured solely among

customers who have already purchased

that brand.

• Share of wallet (in units)= BRAND PURCHASED/TOTAL CATEGORY

PURCHASED

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Module 2010

Example

• Category-sunscreen

• BRANDS :

LAKME,LOTUS,HIMALAYA,GARNIER,L‟OREAL

• Calculate SOW for lakme.

• If customers have purchased 1000 bottles

of lakme sunscreen and total

category(sunscreen) purchases are 2000

bottles then………………

SUHAS ARADHYE

Module 2010

• SOW= brand purchased(lakme)/total

category purchased(sunscreen)

=1000/2000 =50%

So the sow for lakme is 50%.

SUHAS ARADHYE

Module 2010

Size of Wallet

• Size of wallet =

• Assumption: Firms prefer customers with large

size of wallet in order to retain large revenues

and profits

56

J

j

jS1

jS Sales to focal customer by firm j

SUHAS ARADHYE

Module 2010

Applications of SCR and SW

• SCR -for categories where the variance of customer expenditures is relatively small

• SW - if the variance of consumer expenditures is relatively high

• Share-of-wallet and Size-of-wallet simultaneously – with same share-of-wallet,

different attractiveness as customers:

Example:

Share-of-Wallet Size-of-Wallet Absolute expenses

with firm

Buyer 1 50% $400 $200

Buyer 2 50% $50 $25

Absolute attractiveness of Buyer 1 eight times higher than buyer 2

SUHAS ARADHYE

Module 2010

Segmenting Customers Along

Share of Wallet and Size of Wallet

High

Share-of-wallet

Low

Size-of-wallet

The matrix shows that the recommended strategies for different segments differ

substantively. The firm makes optimal resource allocation decisions only by

segmenting customers along the two dimensions simultaneously

Hold on

Do nothing

Target for additional selling

Maintain and guard

Small Large