Fractional VP Sales · European B2B SaaS & Enterprise AI scaleups

AI absorbed the operations. What's left is judgement.

Territory design, forecasting, qualification. AI is already taking the operational layer of B2B sales. What it can't do is read your commercial architecture and tell you where it's actually leaking, which is often something you wouldn't expect and can't see from the inside. That's the work: not another opinion about your sales, but a reading of what your own data already says.

What the deck says

"Our ICP is mid-market logistics. That's where we win."

What the records say

The deals you win share something you don't screen for: a compelling event already on the table before you engage. Without one, the win rate collapses, whatever the segment. You've been qualifying on who fits the profile. The data says qualify on timing.

Most scale-ups can't tell whether the customers they actually win are the ones their ICP says they should, because they've never read it out of their own records. Finding out is where we start.

The six questions

Six questions about your own business you probably can't answer today.

Not problems to nod along to, but questions with real answers sitting in your CRM and billing data, unread. Each engagement starts by pulling those answers out. Sometimes the finding is that your systems can't answer at all yet, which is itself the most useful thing to learn.

01
Feasibility

Is next year's revenue plan actually possible on the numbers you already have?

What surfaces

Once you account for onboarding time, average rep tenure, win rate per rep and real pipeline coverage, most plans quietly require a multiple of what the team has ever produced unaided. And the date to create the pipeline for it has often already passed.

02
Pricing power

What is your product actually worth to the buyer, conservatively enough that a CFO won't dismiss it?

What surfaces

The gap between that number and your price is usually a pricing decision hiding as a messaging problem.

03
Win factors

Of everything you record about a deal, what actually predicts whether you win it?

What surfaces

Your win rate more than doubles when a second stakeholder joins before the proposal, and single-threaded deals are where the pipeline quietly dies. That's not luck; it's a move your team can make on every deal, and mostly doesn't.

04
Interactions

Which combinations of factors win, and do they hold up when you re-check them?

What surfaces

A factor can matter enormously in one context and not at all in another: it only works above a certain deal size, or only through one channel. Averages hide it; your team acts on the average.

05
Retention

Does the revenue you win actually stay, and is it worth what you assumed?

What surfaces

Churn reaches you as a single blended number, the most misleading figure in the business. It's a mix of segments moving in opposite directions, one compounding while another haemorrhages, and you're usually selling hardest into the leaky one.

06
The join

Does the way you win a deal predict whether you keep the customer?

What surfaces

When it does, a single qualification rule raises win rate and stops you signing revenue that leaves. No acquisition or retention view sees this alone.

How it works

The finding is the start. Decisions are where the work begins.

The reading is fast and it's honest. What comes out of it is a specific, quantified problem you now own, plus a clear view of what to do about it.

Step one

Read the data

Your existing CRM and billing exports, run through a set of instruments that test each of the six questions. No new tooling, no long implementation: the data you already have, read properly.

Step two

Find out

We read the data and surface the finding: the constraint, the leak, the mispriced segment, the factor you weren't tracking. Or, honestly, the questions your systems can't yet answer, and what that blindness is costing.

Step three

Decide

From the finding, the work: designing the commercial architecture, fixing the instrumentation, translating what the data shows into language your sales team can carry into a room, or placing the operator who runs it. Evidence sets the direction; the decisions are where it gets built.

When the data isn't there. Plenty of scale-ups can't answer these questions from their own records, because the fields were never captured or there's no CRM discipline behind them. That isn't a dead end. It's the first finding, and fixing it, by installing the minimum instrumentation to make your own business legible, is often the most valuable place to start.

The operator

Two decades of judgement, now backed by your own data.

I am René Appeldorn. For twenty years I've sold and built enterprise sales in European B2B software, at Oracle, Salesforce, SugarCRM, Coupa, Seal Software, and Ivalua, across traditional SaaS and the new wave of enterprise AI vendors.

The instruments don't replace that judgement; they ground it. Instead of telling you what I think is wrong with your commercial architecture from the outside, I read what your own data says, and we start from there. That's the difference between an opinion and a finding.

I work on a fractional basis with founders who aren't ready for a full-time VP Sales, designing the architecture first, then finding or becoming the operator who runs it, until it runs without either of us in the room.

Start with one question

Is next year's plan even possible? The first read is on me.

Send me the numbers you already have and I'll run the first instrument at no charge: whether your revenue plan is arithmetically achievable, or exactly where it quietly breaks. If it's useful, the deeper work is where we'd go next. That part isn't free, but this is.

Start with the free diagnostic

One instrument, no charge · confidential · a clear read back within the week