Until recently, much of the discussion around CRM concentrated on how to make customer information available to the business whatever the interaction channel. Current CRM thinking is focussing more on the value of the relationship between the customer and the business, and how businesses can provide products and services to their customers which develop this relationship value. Value for the business is usually monetary, that is revenue and profit, whilst value to the customer can include convenience, a good deal even perhaps feelings of importance. However to manage the value relationship to mutual advantage, the business needs to have an excellent understanding of the customer requirements and to be able to quantify the value that the customer is bringing to the business now, and ideally in future years.
This approach may be obvious but it is clearly not easy to achieve as can be seen from the continuing practice of promoting the same offers to prospective customers regardless of the value range of the customer base. Although the analysis of customer behaviour and market segmentation has become increasingly sophisticated in recent years, the equivalent level of understanding of customer value has not in general been achieved.
At the simplest level, business value can be quantified as the number of subscribers. This yardstick has been used as one of the main measures of the performance of the UK mobile phone operators. However as the mobile market reaches saturation, the evaluation criteria are likely to move towards analysing the value profile of the customer base. The consequence of this increasing emphasis on customer value is the inclusion of the financial dimension to CRM best practice.
The focus of this article is the measurement of customer value, both the value today in terms of revenue and profit, but more importantly the Customer Lifetime Value (CLV). The justification for highlighting CLV as the key measure of customer value is that although there is an inherent complexity in the metric, as the following sections show, the CLV metric does pull together both the customer financial dimension and behavioural characteristics into one measure. The benefit is that the management of customer value is then closely associated with customer characteristics rather than being undertaken as a separate activity. This inclusion of CLV as a business performance metric is in line with the Balanced Scorecard approach of including the customer perspective as a Key Performance Indicator (KPI).
Customer Lifetime Value (CLV) is often expressed as being simply dependent on the churn rate and a factor which takes into account the value of future revenue discounted to present values. However, this is taking a very simplistic and one dimensional view of CLV which does not reflect the usefulness of CLV as a metric which can be used to tune the business. This section explores some of the components of a realistic CLV and suggests an approach to include the CLV as a business KPI.
The importance of the customer attributes of revenue and especially profit to the value metric can be seen from the picture below. This example shows a graph of cumulative profit against customer bands of decreasing profitability. The resulting curve is known as a Hook curve. The general shape applies to all industries and is relevant to both business to business and business to customer contexts. The curve can be viewed as having 3 main elements:
The management of a business is essentially the management of the Hook curve.
Obtaining customer revenue is relatively easy, after all the much of the detail is produced in the billing process. Determining the cost information is harder. However techniques such as Activity Based Costing (ABC) which analyse the costs associated with customer and product activities are being used increasingly to produce the individual customer level profitability information which is the starting point for producing CLV profiles. The importance of this activity is that equal spend but unequal cost customers, for example direct debit versus non-payers, can be distinguished and treated differently.
The additional benefits of producing a customer cost profile of the business using ABC is that high cost activities such as customer acquisition can be understood in sufficient detail in order to implement cost reductions by re-engineering the business processes.
The ABC analysis is used to evaluate the customer value today, but this value needs to be projected forward in order to arrive at a realistic lifetime value. The following sections describe some of the factors and trends that influence the CLV.
The response of the Telecoms industry to the effect of competitive pressures on charges is the development of products and services that deliver the added value around the basic telephony. The technology advances of WAP, GPRS and 3G provide a platform for the delivery of services to match the requirements of the mobile generation. The potential for services delivered via the networks is limited only by the depth of the customers' wallets.
Overlaid on the long term trends in the industry there are clearly short term discontinuities such as those introduced by regulation or for example the approaching saturation of the mobile customer base. We are already seeing a change in business strategy away from the acquisition of new subscribers to a concentration on developing the value of the customer base.
However there is a need to look beyond evolutionary changes. Overall we need to be aware that lifetime value really means staying in a relationship where the trading fundamentals of that relationship may profoundly change. A simplistic year on year rollup in a spreadsheet model will not do. The planning must allow for potentially dramatic discontinuities.
Churn is a highly complex metric but the impact of churn on CLV is too significant not to be analysed in some detail. The single measure of churn included in the annual accounts is generally regarded as a performance indicator with a 30% churn rate viewed as bad news. On the other hand a 5% churn rate would be regarded as excellent and representing the establishment of a loyal and profitable customer base. These conclusions may well be true but the single churn number masks an underlying complexity. For example the churn of unprofitable customers can lead to increased profits whilst defection of high value customers can erode the business profits disproportionately to their revenue contribution.
Churn rates are highly dependent on the characteristics of the customer segment and in particular on the length of the relationship. The highest churn risk period for mobile customers is around the time of the annual contract renewal but these risk peaks are superimposed on a more general trend that the longer the relationship the reduced probability of defection. Data on retention rates against time presented by Manchester University Business School illustrate that an average lifetime churn of around 20% is based on a first year defection rate of 40%.
Churn rates clearly vary across customer segments. Obvious examples are the differing churn rates of the fixed and mobile segments with variations even within the contract and pre-pay mobile segments. The key is to be in control of churn with both the knowledge of the customer and the impact, either beneficial or otherwise, of a defection.
That the CLV is dependent on lifestyle and lifestage is self-evident. What is harder to quantify is the value of a customer or customer segment as they move through the various styles and stages of their lives. A useful approach which is being practiced by a UK Telco is to research the level of disposable income throughout the lifetime.
Analysing the propensities of customers to buy particular products and services is a well established practice in Financial Services. The techniques apply equally well to the Telecoms market. The ability to predict revenue and profit from the customer base is clearly related to the sophistication of the segmentation capability. This kind of behavioural analysis will become increasingly important as Service Providers provide broader product portfolios and need to target those offerings in an increasingly competitive environment.
The previous sections have described a number of factors that to a greater or lesser extent have an influence on CLV. The challenge is to integrate these factors into a model which is enables the business to use the CLV metric throughout the business cycle from the strategic planning activity, monitoring CLV as a KPI, to forecasting future business value.
The aiming point is a software model of CLV with the capability to accept customer revenue and cost data and key parameters such as churn factors, market trends etc. and providing a simulation capability. However given the complexity of the CLV model, a pragmatic start is to simplify the model to focus on customer segments rather than individual customers and a limited number of the most significant CLV parameters.
A simulation capability is particularly important in a customer centric world. The CLV model can be used to investigate the business impact of managing the quality of the customer base, for example by increasing the population of the high value segments or of reducing the cost of servicing the unprofitable segments.
The more advanced CRM thinking is being driven by the vision of detailed customer understanding providing the platform for real competitive advantage. However, whereas most companies have data warehouses that capture the customer revenue and behavioural information there are few that use additional analytical tools that are dedicated to analysing the actual net profit from customers. Unfortunately revenue is largely taken as synonymous with value or profit but the truth is that net margin (true profitability) is a hidden figure. It doesn't appear in the accounts. It has to be determined and with a bit of effort. There is clearly a need to balance the customer behavioural understanding with a similar level of knowledge about profitability.
The traditional measures of the performance of a business tend to focus on the financial performance metrics such as ROCE, Profit and so on. We would advocate taking a broader view of performance to incorporate such aspects as 'The Customer Perspective' in order to factor in a longer term view of business performance. Customer Lifetime Value is a prime candidate as a business performance metric as it contains the elements of value and customer knowledge. Inclusion of Customer Lifetime Value as a business KPI automatically broadens the scope of CRM towards customer value management, which is the development of customer and business value for mutual advantage.