Most retention is implicitly based on the idea that the best people to target are those most likely to leave. This is rather like trying it improve an exam pass rate by directing most attention to the lowest achievers: it may be heroically worthwhile, but it probably isn't the easiest way to achieve the stated goal.
Churn and attrition models prioritize customers whose probability of leaving is highest. Such customers tend to be dissatisfied, so are usually hard to retain. To make matters worse, in many cases, the only thing currently keeping them is inertia, and interventions run a serious risk of back-firing, triggering the very defections they seek to avoid.
It is more profitable to focus retention activity on those people who are easiest to save—those most receptive to our retention programmes. Like focusing effort on students who are otherwise likely narrowly to fail the exam, this is generally the most efficient strategy for improving the measured outcome.
The customers who generate a positive return on investment from retention activity investment are those in red—the people will leave without an intervention, but who can be persuaded to stay. Uplift models allow you to target them, and them alone. At all costs, you want to avoid targeting the group in black, (so-called Sleeping Dogs), whose defection you are likely to trigger by your intervention. Again, uplift models can direct you away from those customers.
In contrast, standard approaches based on churn or attrition scores tend to direct attention towards the wrong groups, including, in many cases, the Sleeping Dogs. Targeting them is a disaster, as the organization actually spends money to drive away business. Even where this is avoided, traditional targeting inevitably focuses attention on customers who are hard to save, while overlooking those who are more receptive.
Stochastic Solutions has unparalled experience in helping companies to build uplift models that predict the incremental impact on retention of targeting each customer. Standard stats packages and methods simply cannot build uplift models, so you need a specialist approach. By using such incremental models, you align your targeting with the outcome that you measure (the net increase in retention achieved by your campaign) and the very metric that determines the value of the retention activity.
Contact Stochastic Solutions on +44 7713 787 602 or at info@StochasticSolutions.com, and let us help you increase sales by targeting the people whose behaviour is actually positively influenced by your marketing.
You probably already use a control group to measure the net impact of your marketing. You do this because you know that some of the people who buy after being exposed to your marketing would have bought anyway. The control group allows you to measure the incremental impact or uplift.
But unless you're very unusual, when choosing who to target, you don't use an incremental approach: you just use a response model, or a propensity model, to try to people who are likely to buy, with no regard to incrementality.
The only prospects that generate a return on marketing investment are those in red—the people who buy only when they receive your marketing. Uplift models allow you to target them, and them alone.
In contrast, standard approaches based on response or propensity models direct the bulk of their effort at those shown in white (people unaffected by the marketing), and possibly even at the group shown in black (people negatively affected by your marketing), while sometimes missing some of the persuadable reds. This is doubly bad, resulting in wasted spend, targeting people who would have bought anyway; and missed opportunities, failing to target people who may not be very likely to buy even if you do target them, but are almost certain not to if you don't.
Stochastic Solutions has unparalled experience in helping companies to build uplift models that predict the incremental impact on sales of targeting each person in your prospect pool. Standard stats packages and methods simply cannot build uplift models, so you need a specialist approach. By using such incremental models, you align your targeting with the outcome that you measure (the lift of your cross-sales campaign) and the very metric that determines the volume of sales you make.