EXPERT RESPONSE
Customer lifetime value (CLV or LTV) represents the net present value of profits, coming from the individual customer, which creates a flow of transactions over time. Companies can look at their investments in terms of cost per sale, rate of customer retention and also conversion of prospects. CLV is then used as a convenient yardstick of performance, however, it has tended to become a bit too much of a 'holy grail' for corporate, marketing and sales executives, to the extent that entire conferences and seminars are often devoted to helping optimize it.
The inherent danger of over-focusing on customer lifetime value is that companies will invest in programs that try to wring profits from only the most active, heaviest spending customers. This neglects opportunities not only from customers who are 'growable,' but also former customers who could represent attractive profits, once recovered. The result of such an emphasis will inevitably be a steady increase in CLV from these customers, but at the same time, a steadily decreasing pool of customers and ever-declining overall company profit.
When companies make decisions around CLV, either combined with ROI analysis or in place of it, they tend to have a more narrow perspective of profits relative to investment. ROI facilitates investment decision-making at the micro level, around individual customer life stage and customer purchase scenario. It also allows for aggregated profitability estimation at the macro (corporate, department, and campaign or program) level.
ROI, simply, increases accountability. Any customer-related initiative by the overall company, or by groups like marketing, sales and service will have 'hurdle' rates established. These are minimum levels of return, against specific time periods, required to obtain funding. So, if a marketing group wants to acquire customers through certain media that have historically created higher customer lifetime value, the ROI approach will force a more in-depth investigation of alternative media, a determination of how many (profitable) new customers can be generated, and so on. Additionally, ROI analysis can be used to help assess returns from future customer-related investments.
One of the values of more advanced ROI software and models, for instance, is that they can help make investment decisions based on the anticipated response of each customer.
Beyond basic ROI analyses, discount rates (on the future value of money or rates of customer conversion) can be applied to alternative customer-related initiatives. This enables a group, or groups, to evaluate between multiple opportunities with respect to timing of expenses and projected profits. Discount rates are often used in retail funding decisions.
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