Expert Opinion

What is Customer Profitability Management (CPM)?

Customer Profitability Management (CPM) focuses upon an organisation’s most profitable customers and products with the aim of improving “bottom line’ performance. According to Marko Seppanen and Jouni Lyly-Yrjanainen (2002) of the Cost Management Centre at the Tampere University of Technology, over the past decade the focus of management accounting has shifted from product based costing towards customer profitability management. The authors cite a Connolly and Ashworth (1994) statement that profitability analysis in its development has moved through three distinct phases i.e.:

An understanding of customer profitability can provide a valuable opportunity to better manage cost structures and the quality of customer revenue streams. The resources used to serve customers typically have a degree of flexibility enabling them to be reshaped relatively easily to serve different customer groupings.

Building Loyalty Programmes for CPM

Effective loyalty programmes target both customer attitudes and customer behaviour. These programmes utilise customer profitability management to drive the desired behaviours from targeted customer segments. Carlos Dunlap (2004), Director of Strategic Services for Maritz Loyalty Marketing, describes the following eight steps towards building customer loyalty programmes designed to nurture an organisation’s most profitable customers:

• Situation Analysis; conduct a thorough examination of the present environment in order to provide a sound foundation from which to commence. Questions to ask include:
• What is the organisation’s long-term vision and goals?
• How is business conducted on a daily basis, and how are profits earned?
• What customer data is currently captured, and how is this achieved?
• What market and competitive drivers affect current loyalty programmes?
• What is the current brand recognition, and how is this promoted?
• How many lines of business exist in the organisation, and do these have different business models, products, and target customers?

This data can be used to build profiles of the organisation’s best customers and to identify gaps existing between the current and the desired positions.

• Projected Earnings; profiles for the organisation’s most profitable customers may used to project earnings based on established loyalty marketing models. The lines of business envisaged, and targeted key customer segments may also be identified.

• Program Impact Assessment; profitability goals may be set for the proposed loyalty programmes. At this point programmes may be designed which aim at changing customer behaviour. Potential cross-selling and up-selling opportunities can be identified, along with opportunities for segment migration, customer retention and acquisition.

• Building the loyalty programme; the structure, payout levels and reward systems associated with the loyalty programme may then be constructed; the intention being to drive desired behaviour from the organisation’s most profitable customers.

• Estimating the costs to establish proposed loyalty programmes; the costs to build, maintain and improve the loyalty programme should be ascertained.

• ROI Model; this model should record investments, incremental profit expected, unredeemed rewards, and liability projections over time. By measuring ROI on an ongoing basis, organisations can ensure that their loyalty programmes continue to reward profitable behaviour. As a rule of thumb a well-crafted loyalty programme should break even in its first year and cover the set up/implementation costs. It is estimated that a well-designed programme should cover internal rates of return in the second year, and continue to improve in the third year and beyond.

• Testing; prior to the full implementation of the programme it is advisable to carry out testing using a select group of customers or special focus groups.

Data Mining

Data mining can provide a better understanding of customer behaviour and provide insights into ways of reducing customer defections and churn rates. Gordon Linoff (2004), founder and principal of Data Miners, describes graphical techniques for plotting “hazard probabilities” which reveal the patterns underlying customer churn rates for subscription paying customers. By correctly stratifying the available data, the clarity of the output was greatly improved. Linoff described, as an example, a scenario where it became evident that customers who paid by credit card were the most likely to continue on the books of the organisation. Other patterns revealed were:

• Initial spikes in the dropout rate of customers which were due to matters such as poor customer information being gathered at the point of sale, or perhaps by buyer's remorse.

Grading

John I. Coffey and Gene Palm (2005), principals of Profit Resources consulting company, give examples of CPM in a banking environment. To effectively assess the value of particular customers, decisions need to be made concerning how these should be graded e.g. as individual customers or by household. The standard by which to assess a customer’s value also needs to be ascertained. Customers can then be ranked according to profitability, and placed into quartile ranges, with the “A” range being the top group and “D” being the lowest group. It is beneficial to grade customer behaviour in a number of ways, and a wide variety of variables can be used to achieve this e.g.:

• Total profits;

• Total deposits;

• Total loans;

• Date first account opened

• Total account;

• Total services; and

• Various demographics:

By assigning weights to variables, an econometric formula can be constructed allowing the effective grading of customers. It is then possible to determine who the best customers are e.g. those that have been with the organisation the longest; those that purchase a variety of profitable services, or those that maintain the highest balances. Grades can be used to identify those customers that have the potential to be shifted for example from the B to the A quartiles through cross-selling. These categories may also be intelligently used on a day-to-day basis by sales representatives and other staff as they interact with customers. Special attention can be given to “A” level customers, whilst “D” level customers may be treated courteously although not given the same privileges as the bank’s most valuable clients.

Total Cost of Ownership

Customers are becoming more interested in the lifetime costs associated with their intended purchases. The total cost of ownership, particularly for high priced items, may have a significant bearing upon the value that a buyer perceives concerning that item. Robert Hall, group executive for EnAct (2004), says that customers are becoming increasingly aware of costs e.g. shipping, hidden fees, poor service, unanticipated maintenance and low resale value. All of these drive up the cost of ownership. Customers search the internet for factual information, which they can trust, and which is devoid of sales hype. Important decisions are made using this information; hence the provision of good comparative metrics can form an important key for managing customer profitability.

Customer Lifetime Value and Customer Equity

CPM has an impact upon (a) customer relationship management, (b) product promotion and (c) pricing. In addition CPM embeds a greater degree of customer behaviour modelling and metric analysis which can lead to a better ability to make informed customer service decisions. Customer lifetime value (CLV), customer equity (CE), and activity based management (ABM) are relevant tools used in association with customer profitability management practices.

Roland Rust, director of the Centre for E-Service at the University of Maryland, Katherine Lemon, assistant professor at the Wallace E. Carroll School of Business, and Valarie Zeithaml, professor of marketing at the University of North Carolina, wrote (2001) that an understanding of customer profitability is an essential component of modern business marketing. In this regard customer lifetime value (CLV) and customer equity are two key metrics which enable organisations to calculate the expected ROI of their marketing initiatives. CLV is defined as the total net income a company can expect from a given customer, and customer equity is the total future value anticipated from all, or part, of the organisation’s customer base. Rust et al believe that to improve an organisation’s customer equity requires the building up of three central drivers i.e., value equity, brand equity, and relationship equity.

• Value equity is related to a customer’s perception of the price, quality, and convenience of purchasing products or services. Value equity is most important when:
• There are discernable differences between competing products;
• Complex decision making with trade-offs between costs and benefits is involved in purchases;
• Options involve long-term business partnerships and high costs;
• Innovative products and services are offered leading customers to seek out detailed information from web sites etc.;
• Mature products are being revitalised with the introduction of new benefits and features.

• Brand equity is associated with customer awareness and attitudes towards brands. Brand awareness is particularly influenced through marketing communications. Customers’ attitudes towards brands are related to the close connections, or emotional ties, created by organisations. The importance of brand equity rises to prominence in the following situations:
• For low-involvement purchases with simple decision processes, including frequently purchased consumer packaged goods;
• When the use of the product is highly visible;
• When experience associated with the brand can be passed on between generations and peers;
• When it is difficult to ascertain and evaluate quality prior to consumption.

• Relationship equity is associated with the things that tie customers into a brand e.g., frequent buyer programmes. Specifically, relationship equity may be defined as the tendency for customers to stick with the brand, above and beyond their objective and subjective assessments of that brand. Key levers which can enhance relationship equity are loyalty programs, special recognition and treatment, affinity programs, community-building programs, and knowledge-building programs.

In essence customers choose to do business with an organisation because (a) it offers better value, (b) it has a stronger brand, or (c) switching away is too costly. By using this information organisations can identify key opportunities for growth and improvement.

CLV analysis can assist with forming the right decisions concerning the acquisition and retention of customers. In the customer classification scheme below (Niraj et al, 2001) the customers in cell 4 are candidates for divestment, those in cell 3 require the most nurturing. Customers in cells 1, 2, and 5 could be lifted to more favourable characteristics with greater profits. Customers in cell 6 are possibly the backbone of the organisation’s profitability but not its growth.

Unprofitable customers may be handled through changing incentives and prices by adopting service-based, or menu based, pricing as a means of improving profitability. The authors cite a United Kingdom survey (Innes and Mitchell 1995) in which the most important use of customer profitability analysis was found to be for pricing policies

An analysis of customer service costs and customer profitability can enable the revaluation of business processes and practices. Product lines can be rationalised leading to cost savings. Business practices can be streamlined and sales force incentives can be restructured to create a better understanding of costs and profits which can help management and salespeople in their pursuit of additional revenue, or in offering special services.

Value Based Accounting

Randall Payant, Director of Research.

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