Most companies operating in indirect sales environments are in the dark about POS inactivity, although studies show that it costs them on average 3% in revenue loss. Having little visibility at point-of-sale (POS) level, many sales managers basically let their sales reps cruise around regardless of POS value. Our research shows that focusing efforts on high value POS and identifying the optimum reactivation time threshold can result in an up to 10% increase in potential sales.

POS inactivity is not a side problem

We conducted a research on POS inactivity throughout a bunch of large telecom operators and discovered the following:

  • on a daily basis, 5% of POS are actually inactive
  • the majority of surveyed POS encounter 2 inactivity periods per month
  • those periods are on average 3 days long

Reducing inactivity to zero would imply a visit to every POS every single day (assuming that every visit is effective). This is, of course, impossible. Obvious limitation is the number of available sales reps and their average productivity, which leads to a maximum number of daily POS visits. Under that constraint, two types of objectives can be pursued: minimizing inactivity time or maximizing revenue recovery. Our research concludes that the second strategy is by far the most efficient.

The art of trading-off

There are two parameters that can trigger reactivation visits: the POS value (i.e. its average sales revenue) and the inactivity duration. By clustering the POS in function of their value we discovered that:

  • half of the POS account for more than 90% of total revenue
  • high value POS are more likely to naturally reactivate within three days of inactivity
  • after a couple of inactivity days, there is a timeframe where high and low value POS are roughly equally distributed

This suggests that there is no point reactivating too quickly, because the amount of POS to visit is too high and high value POS are more likely to naturally reactivate by the time of the visit. Within a timeframe of 3 until 7 days of inactivity, focusing on high value POS starts to be efficient. It allows to unlock reallocate unprofitable reactivation resources that can be used to reactivate sooner.

In our research, the optimum solution was found by reactivating the top-performing half of POS after 3 days of inactivity, which leads to:

  • a theoretical maximum of 10% total sales boost compared to random visits
  • of which it is likely to recover 2% (because lost sales at one your POS might just be transferred to another POS)
  • 30% to 50% remaining sales reps’ capacity that can be used for POS recruitment or further reactivation

The power of data-driven distribution

Managing the trade-off between the operational effort required for reactivation and the potential revenue recovery is a largely missing tactical competence among big companies operating in indirect sales environments. Addressing the inactivity issue with a data-driven approach has multiple advantages. It creates awareness of the issue, it allows you to size the issue, and eventually take the most efficient corrective actions. It should be part of a growth strategy even before considering acquiring new POS.