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 and interpret your commercial architecture, show you where it's leaking, and tell you what to do about it. The leak is often somewhere 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. Because the plan you take to the board, the next rep you hire, the number you commit to next quarter all rest on it. And the leak, once found, is where the growth is hiding: win rate you're leaving on the table, margin the price isn't capturing, revenue trapped in a stalled cycle.

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.

Start finding out See the nine questions →

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 nine questions

Nine questions that read your commercial system end to end. You probably can't answer them 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 in your own data

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 in your own data

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 in your own data

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 in your own data

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

Pipeline truth

Is the pipeline covering your number real, or a story the CRM is telling you?

What surfaces in your own data

Strip out the stale deals, the ones whose close date keeps slipping, and the ones too old to land in time, and the coverage on the board slide often halves. It looks safe right up to the quarter it isn't, because the report inherits the optimism of whoever filled it in.

06

The leak

You think you have a closing problem. Where does the funnel actually leak?

What surfaces in your own data

The close is the loud number, so that's where everyone coaches. The real leak is almost always earlier and invisible, because a deal that dies mid-funnel never becomes a loss anyone remembers. Fix the one stage that's genuinely binding and throughput moves without touching the rest.

07

Deliverability

Can the team you have actually deliver the number, and survive one person leaving?

What surfaces in your own data

A healthy-looking blended attainment usually hides two people carrying the quarter and a tail that isn't. Remove the top two and the plan collapses. The average is built to conceal the two things that decide whether the number is real: how concentrated it is, and how much rests on reps who aren't yet ramped.

08

Retention

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

What surfaces in your own data

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.

09

The join

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

What surfaces in your own data

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.

Why not just build it yourself?

A dashboard/report you can create in your CRM shows you the numbers. It can't tell you which one is lying.

Fair question, and the honest answer starts by conceding the point. Your CRM is genuinely good at showing current state to someone who already knows how to read it. That last clause is the whole game. A report reflects what is in the system. It cannot distrust it, benchmark it, or tell you which single thing to fix.

The objection

"Our RevOps lead can pull all of this out of the CRM in an afternoon. Why would we pay for it?"

Why it doesn't hold

A dashboard is a mirror. It reports the stage labels and probabilities your reps typed in, the dead deal marked live to dodge admitting the loss included. It can't audit its own inputs, because that would mean the system contradicting its own data. The instrument distrusts those inputs and re-derives the number from behaviour. A report reflects. It does not judge.

There is a second thing the report can't do: it only ever sees your company. An 85% attainment figure means nothing without knowing what healthy looks like across many companies at your stage, and that comparison is exactly what one company's data is blind to. The benchmark is the value, and it isn't in your CRM.

And a dashboard hands you twelve numbers of equal weight and leaves the "so what" to a human. The instrument names the one binding constraint and what to fix first. That human, the one who can look at the funnel and know the stage-two leak is the constraint, is precisely who a company between VP Sales hires doesn't have. The dashboard assumes that reader. That reader is the thing you're hiring.

So yes, you can already see your pipeline. What you're buying is knowing what it means, read and interpreted by someone who has seen a hundred of them.

The fit check

How much of your business can we read today?

Those nine questions have answers sitting in your own CRM. How many of the instruments can read yours right now depends on what your system lets you export. Pick your stack, tick what you can pull, and see exactly how deep the picture goes today, and what one export or connection would open up.

Step 1 · Your CRM

Which CRM do you run?

This decides how reachable your stage-change history is, which is the one piece of data that separates a partial read from a full one.

This is depth of visibility, not a menu. You are not choosing instruments off a list. Every instrument is part of one diagnosis; what changes with your data is how much of the picture comes into focus, and how fast.

The instruments you can run now are where a first Diagnostic starts. The ones a single export unlocks are the depth the Architecture phase works from. The last two, that a connection opens, are what the Monitored subscription runs on a cadence, watching the picture as it moves.

What the finding is worth

The leak isn't a problem to admire. It's growth you already own.

A constraint, once found, isn't a diagnosis you file. It's the specific place next quarter is leaking. The gain from relieving it isn't a promise we make. It's value already sitting in your numbers, unread.

Win rate

The win rate you're leaving on the table.

The deals you lose usually fail on one attribute you never think to screen for. Find it in your own closed deals, apply it as a qualification rule, and the win rate comes back. It was never a skills problem.

Deal-Level Discriminator · Segmentation Tree

Sales cycle

Revenue trapped in a stalled stage.

When deals sit in one stage before they die, the time held there is revenue you could pull forward. You fix the single binding stage, not the whole funnel, and the cycle shortens where it actually jams.

Velocity

No-decision losses

The deals written off as no-decision didn't vanish.

A deal lost to no-decision died at a stage nobody was watching, and it is almost never the close. That stage is findable in your own funnel, and it is usually the cheapest thing on this list to fix.

Velocity

Margin

Margin the pricing isn't capturing.

The gap between what your product is worth to the buyer and what you charge is margin left behind, deal after deal. The size of it is measurable before you touch the price.

Value Model

Compounding growth

Retention as a flywheel, not a leak.

A blended churn number hides one segment compounding and another haemorrhaging. Split it, sell into the segment that compounds, and growth stops fighting a leak it couldn't see.

Retention & Expansion

We don't promise these. We find which one is yours, and what it's worth, before you spend a euro fixing it.

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. What changes is what you can defend: a plan you trust because you've seen the numbers under it, spend pointed at what actually moves revenue instead of what you assumed did, and a board conversation you walk into with evidence rather than a story.

Step one

Read the data

Your existing CRM and billing exports, read properly. Each question is answered by a purpose-built instrument run against your own data, so there's no new tooling and no long implementation: just the numbers you already have, read the way you can't from the inside.

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.

René Appeldorn, founder of SALESSHARE

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.

How we'd work together

What you actually buy, and where it leads.

No mystery about the engagement. It starts small and only grows if the first step earns it.

First

A free diagnostic

No charge · one instrument

One question read from your own data, most often whether next year's plan is achievable. You get the finding whether or not we go further.

Then

A focused engagement

Fixed scope · weeks, not months

If the finding warrants it, a defined piece of work: the full read, the commercial architecture, the pricing or retention fix, the instrumentation to make your business legible.

Ongoing, if it fits

Fractional VP Sales

Monthly · until it runs without me

Where you need the operator, not just the architecture, I run it on a fractional basis, or find and brief the person who will.

You never commit to the whole ladder up front. Each step is earned by the one before it, and the first step is free.

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.

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

Thanks, that's with me. I'll be in touch shortly to set up a first conversation.