Sales pulls. Finance holds back. The quote is caught in the middle.

In nearly twenty years in tech, at Sopra, Oracle and then Salesforce, I’ve seen the same conflict play out across thousands of deals.

On one side is sales. Paid on revenue, the rep wants the deal, so they want to lower the price.

On the other side is finance, measured on margin, trying to protect it. And operations knows that a discounted price can mean an under-resourced project before it has even begun.

Each is right according to their own logic.

The problem is how the decision gets made. Not once through calculation. Always through escalation. The final price is management’s compromise, not necessarily the right one.

The false dilemma

Every quote puts the sales rep in an impossible position.

Hold the price. The price list is fixed. The deal desk caps discounts at 2%. The customer wanted 3%. They sign elsewhere. To protect €1,000, the company loses the entire deal. And the account.

Drop the price. The rep senses that “this could be a problem” and cuts 8%. The customer would have signed at 3%. Five points of margin gone. No record. No reason.

Both mistakes have the same cause. The right price existed somewhere between 0 and 8%. Nobody calculated it. They guessed.

And guessing is expensive. Take a €100,000 deal with a 20% margin. The rep gives up 5% to secure it. That is €5,000. It is also 25% of the deal’s margin. At company scale, McKinsey measured the leverage: a 1% change in price means an 8.7% change in operating profit, at constant volume. In either direction.

The problem is not new. As early as 1992, Marn and Rosiello (McKinsey) showed in Harvard Business Review that, for the same product, realized prices varied by as much as 60% from one transaction to another.

This conflict was solved in 1838

There is something unusual about this conflict: it was solved long ago. Not by consulting firms. By mathematicians and economists.

In 1838, Cournot expressed demand as a function of price and derived the price that maximizes profit against competition. In 1934, Lerner showed that the optimal margin depends on one thing: the customer’s price sensitivity. In 1956, Friedman formalized what every sales rep senses without calculating it: the right price maximizes margin multiplied by the probability of winning, estimated from competitors’ past offers.

Margin, competition, customer sensitivity, probability of signing. Each of the four variables in your quote has its own equation. The newest is nearly a century old.

So why, a century later, is margin still leaking away?

Because the equation never made it into the quote.

It stayed in the books. The quote remained a struggle of competing interests and escalations.

And the gap is measurable.

Bain, January 2025, 1,263 B2B companies. Those that know how to defend their prices earn 5 to 11 more points of margin than competitors in the same sector. For a company with €100 million in revenue, that is €5 million to €11 million a year. In the same market. With the same customers.

The same goes for win rate. Organizations negotiating with data-driven price guidance are 12 points more likely than others to report winning more deals than they lose. Their sales reps are twice as confident about holding their price.

And the ones that have done it? A $15 billion distributor gained 200 basis points of margin by calculating its prices. That is roughly $300 million a year. Then another 50 basis points in ten weeks with agents. About $75 million. In ten weeks.

That is the cost of the tug-of-war. That is the return on calculation.

Why nobody does it

Because the equation is simple. Its variables are not.

The cost of the deal. The account’s margin over three years. The price at which a competitor won the last tender. The win rate across the last hundred comparable deals. This quarter’s target, and where the pipeline stands.

Five variables. Four systems. And all of them move. Every day.

A person can solve the equation once, for a major deal, in a week. Not three hundred times a month, in ten minutes, for every quote that goes out. A spreadsheet cannot do it either: it freezes what is constantly changing.

So the rep builds the quote by hand. Salesforce reports in its State of Sales that sales reps spend 28% of their week selling. Quoting consumes part of the rest.

McKinsey confirms it: more than half of pricing executives cite data and integration as their biggest obstacle. Not the theory. Not the will. The data.

She negotiates. The squad calculates.

What we decided to do

At YBA, our mission is to decouple our customers’ sales from their margins. Growth should no longer come at the expense of margin. And margin should no longer come at the expense of lost deals.

So we set ourselves a challenge: run the equation on every quote. Not once a quarter in a committee. On every quote, in seconds, using data the company already has.

That is the job of our pricing agent.

It collects and analyzes thousands of data points across every dimension of the deal: volume, industry, country, margin, current contracts, stage in the sales cycle and account history. It compares them with similar deals already won or lost.

Then it recommends the pricing strategy that maximizes two things at once: this deal’s win rate and its margin. Not one discount policy for everyone. A range for this customer, on this day, with the reasons behind it.

And it does not stop at the recommendation. It builds the quote in the CPQ. The sales rep only has to make a decision within that range. The deal desk keeps governance. Sales keeps the relationship.

No more escalation. A calculated range before entering the room. And the quote is already ready.

Margin problems? Win-rate problems?

Contact us at yba@yba.ai

Reda El Messaoudi Aubert — CEO & co-founder, YBA.ai