Imagine you are a key Sales & Marketing stakeholder in a B2B organisation that manufactures and supplies your suite of products into your specifically targeted market sector. You “go to market” largely directly, but still rely on distributors for a reasonable portion of volume outflow. Your market dynamic is such that, by and large, when it comes to your customers, you are either all or nothing. Customers will typically use one supplier, rather than share “the love” across multiple suppliers. BUT……….the big growth opportunity/challenge is in increasing penetration (uptake/usage/consumption) of your products within each customer. Customers tend, to varying degrees, to under utilise your products and systems.
Given the mix of direct vs indirect sales to end users, your “line of sight” in terms of current value of all/any customers is partial, as the channel cannot/does not provide end user sell-through data. Your sales system capability therefore to classify customers, even on CV alone, for sales team targeting is compromised. This forces your hand in a sense, and raises the ante on importance of PV data gathering. Many B2B sales orgs stop at CV if they have good line of sight, for the purposes of customer base classification for sales team targeting. This is not best practice. The gathering of PV data for each customer (and prospect for that matter) is critical. But it is usually harder to gather than CV data, and so that is why many organisations don’t. This is literally doing half of a whole job…….and job that is vital to sales team optimisation and RoI. In this type of case study, where you don’t have full CV line of sight, 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 sales system customer profiling anyway. Let’s look at the specifics in this case study example next week.
Next post : How to develop your sales system PV (customer potential value) proxy models – and why you MUST! (PART 2)
Want to learn more? Check out The discipline of PV (potential value) data collection…why you and your sales process cannot avoid the challenge Part 3