Collections are tricky but if your collection strategies embed analytics, use the analytics to create proper collection treatments, and allow for ongoing test-and-learn adjustments you will optimize your collections efforts. However, I do not want to focus on collection analytics at this time. Why? Because regardless of how well-oiled your collection efforts are, the single largest bad debt impact happens at the point of acquisition.
Setting up proper customer on-boarding treatments, based on predicted payment behavior and predicted customer value, will minimize bad debt on the back-end. As an example, a top 5 direct broadcast company implemented pre-payment and auto-pay strategies during the sign-up process several years back, based on out-of-the-box and custom credit worthiness models as well as predicted subscriber profitability models. The result: A significant decrease in bad debt and write-offs.
Their new on-boarding process essentially entices the subscriber to pay and stick around based on two dimensions:
- Subscriber predicted future value and
- Probability of payment over time
Those 2 dimensions, enabled by predictive models, are powerful if used within a proper treatment strategy. For example, one of the first questions posed, once the analytics were available, was whether to not allow subscribers to activate who have a high probability of not paying.
Answer: Absolutely not! You do not want to shut off the spigot altogether. How about asking those potential customers to provide a pre-payment, which may be applied to the ongoing monthly bill for a certain period of time so they are not paying more than they need to but then showing them good will as well by providing a prize at the end of the pre-payment time period (ie. a free pay per view)? Further, the pre-payment period should be determined by the level of creditworthiness and the prize at the end of the rainbow should be determined by future predicted value.
The key to a proper customer on-boarding process is the strategic application of the resulting treatments. The predictive models for the most part are straight forward … it’s how the analytics is converted into proper customer treatments and then tracked and optimized, that will provide a bottom line profit impact. Just with collection efforts, the acquisition treatment strategy, and ongoing tracking, is a key that unlocks incremental profit.
