Customer Lifetime Value (CLV or CLTV) has a central strategic importance for a company, and more and more managers are discovering that their most important asset is not the company's inventory but its customers. Products and services may be easy for competitors to copy, but a company which is good at creating customer loyalty is less vulnerable to attacks from competitors.
Loyalty is more difficult to copy than a product or a service. So, for this article, we've drawn insights from The Loyalty Guide 4 (pub. April 2010, The Wise Marketer) to help introduce the sixteen key business benefits of calculating - and monitoring - your Customer Lifetime Value.
There are sixteen business-critical reasons why a marketer should know the value of any given customer or segment - and the best way to understand customer value is to examine that value over the whole period of a customer's lifetime with your brand.
To calculate CLV, a company has to measure different customer and market data. In this section we show examples of how to measure and use CLV and customer lifetime in practice. A company that systematically calculates CLV will gain significant advantage:
- CLV can provide an exact figure for the company's largest asset, which is rarely mentioned in the Annual Report. The calculations enable management to follow the progress over time and to intervene if events start moving in the wrong direction.
- The company will be able to evaluate the profitability of various marketing strategies including the effects of different loyalty programmes. Usually the costs connected with a loyalty programme are not difficult to calculate: it is more difficult to predict the income. Combining costs and income over a number of years (defined from the company's perspective) will give an idea of CLV with and without a loyalty programme.
- A company is able, using CLV, to evaluate whether a customer database is optimal. By using CLV the company will be able to classify different customer groups and different potential customer groups by long term profitability and thus decide whether to change market strategy or not.
Here are a few examples of how managers can use CLV in their decision process:
- Defining objectives
In the same way as defining a company objective in terms of growth, turnover, new sales and net profit, it is possible to define company objectives using CLV. It could be stated that CLV has to be increased by 10% from $100 million to $110 million over the next three years. This objective is a more exact measure of the company' economic development than the traditional objectives like the annual turnover. This does not mean that a company shouldn't choose to use both kind of objectives. For one thing, it has to publicise in the annual report standard results like turnover.
- Alternative market strategies
CLV could be used to calculate the profitability of an unchanged acquisition strategy compared with an alternative future strategy based on customer retention and development. The consequence of different target groups, different market budget allocations, different pricing policies, different customer retention rates, different sales channels, different segments and marketing with or without a loyalty programme could also be evaluated using CLV.
- CLV for different segments of customers
Different segments and customer types have different CLVs. It follows that CLV could be used to calculate a changed customer profile. A company with an up-to-date data base could develop a system of defining CLV for individual customers and then use this form of index on a customer page. The employees would then be able to adapt their daily contacts with customers according to the individual customer's CLV. It could be to do with a claim, discount, invitation to an event etc. In addition, CLV could be used to decide whether to follow up on individual customers who have a higher risk of churn. It might also be used to trigger special services for new customers with a high potential CLV.
- Forecasting with customer satisfaction
A large number of companies analyse customer satisfaction, company image, buying intentions and so on. The problem is, however, to convert research conclusions into predictions of consequences, and into decisions based upon those consequences. For example, what would the consequence be if customer satisfaction decreased from 90% to 88%? How would that affect the customer retention rate? How would it affect cross-selling opportunities? How would it affect customer profitability?
- Market communication
There is an old saying: "I know that half of my advertising costs are wasted. I just wish I knew which half". There is still some truth in that today. Nowadays, it's probably more than half of the communication budget that is wasted. This is odd, seeing that nowadays it is possible to precisely measure the results of marketing communications, especially when using direct marketing media like mail, the telephone and internet. A company can achieve much better results (such as awareness and image) by choosing target groups, communication channels, and even the message to be delivered using CLV. Instead of allocating 80% of the marketing communications budget to mass communication, 80% could be allocated to direct customer communication.
- Customer service
Generally it is most profitable to invest in customer services in areas where there is the highest positive correlation with customer satisfaction. Services like hotlines, upgrading and invitation to events could be defined and targeted to customers who have the highest CLV (and not the highest actual turn over).
- Loyalty programmes
The future profit from an investment in a new loyalty programme including the results of different forms of customer rewards (discounts, exclusive offers, special service, upgrading etc.) could be learned by calculating CLV, both with and without a loyalty programme. This could be further refined by calculating CLV as a result of two different loyalty programmes.
- Early warning systems
CLV models can be used as an early warning system to detect increasing defection rates or cross-selling. The predictive method is most suitable for this, because it is based on the most recent patterns of buying. It will identify in which segment the problem originates, and action can be taken to correct the cause.
- Managing the sales force
CLV could be used to help decide which sales districts to focus on (what is the potential CLV in a given district?), how to allocate sales resources, how to reward sales agents (say a higher bonus for selling to customers with a high potential CLV or acquiring new customers with a high CLV), how to run sales competitions (say rewarding the sales agent with the highest number of total customers instead of the highest annual sales) and so on.
- Marketing campaigns
Generally it is most profitable to invest the marketing budget in campaigns that focus on customer groups, potential customer groups and a group of defected customers with an above-average CLV. Cross-selling campaigns can be targeted at customers who have been defined and selected using CLV.
- Reactivating inactive customers
Instead of trying to reactivate all inactive customers the efforts should be directed toward those customers whose CLV is potentially above average.
- Complaint management
If a customer complains about a serious problem then a simple CLV index (or preferably an individual CLV score) will help front-line employees to decide what action to take immediately and how much to invest in solving the problem. The index (rating individual customers or groups of customers) might be shown on the computer customer page in a call centre.
If a customer is about to defect (for example, is calling to cancel a subscription or policy), a 'score' based on his CLV could be displayed on the customer page of the operator's computer screen. This would help the operator to decide what action to take. Some customers are not worth following up. Other customers could be offered some incentive not to cancel or, if they go ahead, be followed up immediately with a view to getting them to withdraw the cancellation. If possible, past customer data and the profitability score would be kept with the information about the cancellation, to improve the quality of defection analysis and to increase the effect of future win-back efforts.
A customer often has a different CLV before defection and after recovery (win-back), the second CLV frequently being better than the first CLV.
- The annual report
Except for general statements like: "We are a customer centric company", "Customers are our most valuable asset", "We expect increasing numbers of customers in future" etc., the Annual Report seldom informs shareholders about the future value of the company customer base. It does inform you about past data; it informs you about economic deals with customers; it informs you about annual income and net profit - but usually mentioning brands and product groups, not customers. The day is yet to come when chairmen or CEOs proudly announce their company's total CLV.
- Mergers and selling or buying companies
If a company calculates its CLV for all its customer groups (potential customers, existing customers and defected customers) - or at least its CLV for existing customers - it will have an exact picture of its most valuable assets: its market position and its existing customers. Those figures could be used as part of the valuation that's needed for mergers, company purchase and company sales. For example, to establish a value for a telecoms company, part of the business case is the calculation of the customer capital based upon numbers of customers multiplied by an average value. However, this value will often be an estimate more than the real future customer value. A concrete calculation of the value of the customer base is a better indicator of how much to pay, particularly if the calculation includes the risk of a higher defection rate because of the prospective sale of the company. In the same way CLV is useful in the business case for the merger between two companies. The merger will influence both the acquisition rate and the retention rate.
The Loyalty Guide, our comprehensive guide to customer loyalty, explains every aspect of loyalty programmes, best practices, concepts, models and innovations, all backed up with case studies, original research, illustrations, charts, graphs, tables, and presentation material. Find out about the principles, practicalities, metrics, analysis, and bottom-line effects of loyalty, and gain the expert guidance of dozens of loyalty and relationship marketing thought-leaders, worldwide.
It will show you exactly how to use customer data to increase profits, reduce churn, and increase frequency, spend, and share of wallet. See how and why others have already succeeded, what works, and - more importantly - what doesn't work. The report's full executive summary, table of contents, downloadable samplers, and pricing/ordering are all available online - click here.