Last week I argued the merits of good CV (current value) and PV (potential value) data collection for every customer. Collecting and then grading customers for sales team targeting on CV alone is doing half of a whole job…….a job that is vital to sales team optimisation and RoI. In the case study I outlined last week, where full CV line of sight is not available, PV data becomes even more critical.
You must define a proxy model featuring criteria that is manageable for your sales team to score each customer and systematically collect the data. In a sense, this is nothing more than best practice B2B sales process customer profiling anyway. Let’s look at the specifics in the case study example from last week. When it comes to a PV proxy model for the sales team to score each customer against, it is useful to develop a good-better-best model. This should ensure that there is at least one PV data point for each customer- Sales exec scenario, to accommodate scenarios where “best” is not attainable.
Our case study manufacturer sells its products into nationally deployed healthcare practitioners. They have PV graded each centre on the number of practitioners working within. This is (only just!) “good”. More than 90% of centres will feature 1-4 practitioners. This is not granular enough for classification differentiation. Enter a proxy for number of end user/customers who are regularly “enrolled” at the centre. “Better”. Then a proxy for number of appointments between practitioners and end user customers. “Best”.
Now we need a mechanism to accommodate all possible scenarios whereby one form of data is collected for a given centre……two forms…….or all three. Come back again next week and we will show you how.
Stay tuned for next weeks post: How to develop your B2B sales process with PV (customer potential value) proxy models – and why you MUST! (part 3)
Want more? Check out part one here