Customer Equity (and Customer Lifetime Value)

Provider:  Blue Marble Enterprises [1] 

(using model developed by Yoo & Hanssens) [2]
customer lifetime value

A customer’s lifetime value (CLV) is measured as the net present value (NPV) of profit streams from the initial transaction (i.e., acquisition) and all future transactions anticipated by the customer (i.e., retention).  The CLVs of all customers are summed to derive a firm’s customer equity (CE). [2]

Source Data

3-year linked 10/12 static panel provided by Nielsen

How Derived

CE is obtained from future expected values of (1) number of buyers (purchases), (2) purchase quantity, and (3) contribution margin. A stochastic model is used to determine the probability that a consumer is still a customer at any point in time, based on purchasing history. [2]

CLVs are derived for “acquisition customers” defined as households with purchase probabilities of .50 or less and for “retention customers” with greater than .5 purchase probabilities. [3]

How Used/Activities

CE and CLV have been applied in contract-based industries. This pilot demonstrates the extension of these metrics to consumer package goods (CPG).


The Yoo & Hanssens CE model can be systematically applied to CPG. [3]

It is a stable metric (i.e., low volatility).
It is forward looking (different from sales or market share).
It estimates long-term impact of marketing actions relative to competition in category. [4]


The linked static panel demonstrated 3 limitations when used for this pilot study:

  • Panel fatigue in the 3-year period
  • Lack of new to category buyers during time frame
  • A model bias over the time frame [3]

When extending the approach to the marketplace, the first two can be resolved by using unlinked panel data and the third by enhancing algorithms that work with time since last purchase. [5]

Relationship to Financial Metrics

Not demonstrated because of limitations.

How Does It Meet the MMAP Characteristics of an Ideal Metric?

  1. Relevant . . . addresses and informs specific pending action
    May inform relative future 2 year trends in cash flows assuming brand (competitors & category) will behave as they did the previous year. Continue doing same (if trend vs category is acceptable) or change if trend not acceptable.
  2. Predictive . . . accurately predicts outcome of pending action
    Not demonstrated. Nor would it be if activities were to be different. . . i.e., impact of proposed changes pre-market.
  3. Objective . . . not subject to personal interpretation
  4. Calibrated . . . means the same across conditions, categories & cultures
    Not demonstrated with panel data
  5. Reliable . . . dependable and stable over time
    Not demonstrated because of limitations noted above
  6. Sensitive . . . identifies meaningful differences in outcomes
    Not demonstrated because of limitations noted
  7. Simple . . . uncomplicated meaning and implications clear
    General implications (change/don’t change) clear, derivation and specific implications toward action more complicated
  8. Causal . . . course of action leads to learning/improvement for decision making in competitive context
    Because of limitations noted above, does not inform specific action to be taken . . . just that it should be changed if relative trending not acceptable
  9. Transparent . . . subject to independent audit
  10. Quality Assured . . . formal/ongoing processes to assure 1-9 above
    Pilot (NA)

How Does It Fit Overall Guidelines?

Measures of return on marketing investment should:

A. Provide a specific link to financial performance; no measure or measurement system is complete without one.
While providing a financial projection, not yet demonstrated how it links to actual cash flow

B. Reflect the standard financial concepts of return, risk, the time value of money, and the cost of capital.
Yes, time value of money

C. Provide information for guiding future decisions by predicting future economic outcomes as well as provide retrospective evidence of the impact of marketing actions.
Forward trend relative to category if do what you did last year; additional modeling and interpretation required to guide future decisions

D. Recognize both the immediate, short-term effects of marketing actions and longer-term outcomes, as well as the fact that short- and long-term effects need not be directionally consistent.

E. Recognize the difference between total return on investment and return on marginal return on investment.

F. Recognize that different products & markets produce different rates of return.
Although different rates of return can used in the algorithm for different products and markets, to avoid proprietary concerns, the pilot used same rate of return for all products.

G. Distinguish between measures of outcome and measures of effort.
Measures project outcome.

H. Provide information that is meaningful and comparable across products, markets, and firms.
Relative trending is meaningful.

I. Clearly identify the purpose, form, and scope of measurement.

J. Be documented in sufficient detail to allow a knowledgeable user to understand their utility & make comparisons among alternative measures.
Pilot (NA)

K. Be assessed relative to generally accepted standards of measurement development and validation.

L. Be recognized as necessary investment for assuring sound decision-making, accountability, continuous improvement, and transparency for all stakeholders.
Although applied in contract-based industries, not generally accepted.  This pilot demonstrates capability of applying to consumer packaged goods.

Source Documents

1.  Blue Marble Enterprises, Inc., designs and implements customized databases to help manage specialized information, in this case, implementation of CLV/CE metrics.

2.  Marketing and the Evolution of Customer Equity of Frequently Purchased Brand, Yoo & Hanssens, submitted April 2008; revised and resubmitted in April 2011 by Yoo, Hanssens & Kim.

3.  Application of Customer Lifetime Value (CLV) to Consumer Package Goods (CPG), Hanssens & Parcheta, MASB white paper, August, 2014.

4.  Personal Communication, Mike Hanssens, 2012.

5.  Personal Communication, Debra Parcheta, 2012.

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