Defend
high potential, high share. The base no one may lose.
Station 1 · Potential Scoring
Your CRM knows the revenue.
But does it know the potential?
80 percent of long-term B2B value sits in the existing base. boostpilot.ai calculates the real buying potential per customer, so your sales team knows where the biggest lever is.
The blind spot
High revenue is not the
same as high potential.
A D-account with 2 percent of a large demand often carries more growth than an A-account where you already hold 24 percent. Revenue history says nothing about how much a customer buys in total. Rank by history and you work the biggest customers hardest, and miss the biggest opportunities.
Evidenced: McKinsey lists quantifying share of wallet per customer as a test for above-average B2B growth. Bain recommends shifting resources to where your share is small and demand is large.
The new axis
From revenue pyramid
to potential matrix.
Instead of ranking customers by what they bought yesterday, boostpilot.ai ranks them by what they could buy. Two axes, four fields.
Build
high potential, low share. The lever.
Hold
low potential, high share. Large and loyal, but maxed out.
Observe
low potential, low share. Service instead of field sales.
The calculation
Buying potential
× share of wallet.
boostpilot.ai brings together four sources: ERP, CRM, Dun & Bradstreet (more than 500 million companies) and its own crawling data. More than 360 market variables give two values per account: how much this customer buys in your product groups in total, and what share you hold.
Traceable down to every single criterion and every market variable.
The process
Five steps
to segmentation.
- Matching — your customer data is merged cleanly with external criteria (D&B).
- Market definition — together we define your target market, enriched with third-party and crawling data.
- Potential calculation — per existing and potential customer.
- Segmentation — build, defend, hold, observe, with share of wallet.
- Action planning — concrete measures per account, including churn warning.
The automated Validation Engine is built into the whole process — a dedicated crew member checks every result against fixed validation criteria.
Dormant customers
Wake them, but
the right ones.
No team calls every inactive customer. boostpilot.ai shows which dormant customers carry potential and come first, and which are not worth the effort.
Demo
See your matrix on your own data.
A customer list is enough. In 30 minutes we show you what your potential matrix looks like.
Book a demo