ROI Isn't the Only Factor to Consider

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Acquisition or retention? That is the question. Should you put more money or less into retention? A recent survey claims that more companies spent additional money on retention last year, a swing from previous years when acquisition spending was king.


The problem many marketing managers face is that budgets traditionally are based on a percentage of last year's revenue or budget. This ignores the relationship between marketing spending and profitability effectiveness, and it has a short-term focus leading to limited success. While marketing and database executives may focus on optimizing databases and lists, few optimize the total marketing budget.


Yet optimizing the marketing budget can be a valuable strategic tool to improve long-term success. With fewer than a dozen statistics, the optimal budget can be determined through computer modeling. Once the total budget is calculated, the division between acquisition and retention is optimized.


While executives try to figure out the best marketing budget and how to split it between acquisition and retention, computer models point the way. Several basic principles provide the foundation: diminishing return market response curve, customer lifetime value and customer equity.


The diminishing return market response curve is based on a commonly accepted principle that no matter how much money is spent, not every prospect will be converted to a customer. As spending reaches this "ceiling rate," the next dollar spent will have less effect than the last dollar spent. Using historical data, executives can calculate their market response curve.


Customer lifetime value is the net present value of a customer's current and future contributions to profit. Customer equity is the net present value of contribution of all current and future customers.


While certain executives still calculate return on investment for marketing spend, others focus not on campaign ROI, but rather on customer equity.


For example, you offer a promotion on a product and you generate two times the amount spent, which appears to have a very positive ROI. But let's say that none of those customers buys again. You did not retain one customer for a second purchase. Your customer lifetime value is low, there is little contribution to customer equity and your retention rate is in the pits with this group of customers.


On the other hand, you offer another promotion in which you only break even. But every one of those customers orders again and again. And they continue to order for years. Your retention rate is high, your customer lifetime value rises and your customer equity is high as well. However, your ROI is very low.


Which is better? Most executives probably would opt for the high ROI. But that metric is not optimal. The better metric is to optimize customer equity, which will increase long-term revenue and profit. The short-term view might be to focus on immediate ROI. But the firm's long-term value is diminished.


Optimizing on customer equity will dictate how much budget should be spent on acquisition versus retention. This figure can be statistically calculated rather than using a guesstimate. The shift of budgets between acquisition and retention should not result from the economy or campaign ROI or popular trends. The shift should occur when maximum customer equity can be achieved by reallocating the budget.


Before computer modeling, it would be nearly impossible to calculate the optimal marketing budget and the optimal amounts for acquisition and for retention. However, using the principles of diminishing return market response curve, customer lifetime value and customer equity as the foundation for calculation, the budget with its acquisition and retention allocations can be optimized.


After the acquisition and retention budgets are optimized, the cross-sell, segment and channel marketing budgets also can be optimized. Requiring additional inputs and using more sophisticated concepts, these optimizations can help firms maximize marketing performances. n


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