Yesterday’s post described key leverage points within the three major Lifetime Value components of original, renewal and cross sell orders. It further showed how each is related to total LTV. We want to use these to build a prioritized list of business opportunities—putting something behind the One Big Button in the LTV system.
Building this list three steps: finding where improvement seems possible; estimating the amount of potential improvement; and prioritizing the results. We’ll discuss these for each of the three LTV components.
- for original orders, the key leverage point is acquisition cost, and in particular, acquisition cost by source. The specific measure to use is the ratio of LTV to acquisition cost, which is essentially acquisition return on investment. (People who really worry about these things, like James Lenskold in his book Marketing ROI, might argue that revenues and costs of future discretionary decisions should be excluded. But we need those values so we don’t throw away an expensive source that brings in customers with high back-end value, or add cheap sources that attract low-value customers.)
To identify potential improvements, we’ll calculate Acquisition ROI for each source/product combination, for each product, and for the business as a whole. For source/product combinations that are performing below average, we’ll estimate the impact of reducing the marketing investment, therefore presumably improving results (because we can drop the least effective promotions within that source) and freeing marketing funds to spend more productively elsewhere. For combinations that are performing above average, we’ll estimate the impact of spending more.
In an ideal world, we’d have expert managers carefully estimate the individual results of changing the investment level for each source. Here on planet Earth, the resources to do that are probably not available. One approach is to use a shortcut such as the “Square Root Rule”, which assumes that revenue increases as the square root of advertising expenditure. (See excellent blog posts by Kevin Hillstrom and Alan Rimm-Kaufman explaining this in detail). To further simplify matters and keep results somewhat realistic, I would arbitrarily calculate the impact of a 20% increase or decrease in acquisition expense—even though the optimal change, based on the Square Root Rule, might be quite different.
We still need to translate the expected change in acquisition volume to total LTV. If we assume the acquisition revenue per customer stays the same, we can use the estimated acquisition revenue to calculate the change in the number of new customers. We can multiply that by the back-end LTV (renewal plus cross sell) per person to find the change in back-end LTV added. Combine this with the new figures for acquisition value and you have the total change in LTV. Finally, divide the change in total LTV by the change in acquisition spend to give the estimated Acquisition ROI for the change. The analysis would drop any opportunities where the change in ROI was below average.
Finally, we have to rank the changes. This can also be done using the change in Acquisition ROI. Since some opportunities involve a spending increase and others a spending decrease, total spending may go up or down. We might impose a further constraint that limits the recommended changes to opportunities that yield no net increase in acquisition spending, or a maximum increase of, say, 10%. This is another good candidate for a slider on the user interface. The analysis could be conducted at the level of the company as a whole and also for individual products. In companies with intermediate structures such as a division or product group, the analysis could be done at those levels too.
Well, that’s enough fun for one day. Tomorrow we’ll look at treatment of renewal and cross sell opportunities.
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