
Price negotiation
Sceptical head of procurement
Knows your competitor and their pricing
Industrial supplier, 1,200 employees
Your team talks to a counterpart that pushes back, deflects and probes. Afterwards it is on the record what landed and what did not.

Price negotiation
Knows your competitor and their pricing
Industrial supplier, 1,200 employees

Discovery call
Saw the demo, thinks it is too expensive
Software company, mid-market

Escalation
Second escalation this quarter
Retail group, 40 locations

Feedback conversation
Strong performer, difficult in the team
Insurer, inside sales
Every session starts from a situation, not a role card. That is the difference between amateur dramatics and training.

Sceptical head of procurement
Knows your competitor and their pricing
Industrial supplier, 1,200 employees
Price negotiation
Situation
You are talking before the final internal decision. Your counterpart believes your offer is nearly three times the price of the product they trialled, and needs a logic that makes the cost of the status quo visible.
Goal of the conversation
Not to defend the price with “higher quality”, but to build a calculation together that they can carry internally. The call succeeds if a firm follow-up is booked and they leave with a number rather than a feeling.
Not a score out of nowhere, but measurements taken from the conversation — and two sentences on what to do next.
Measured
Recording
5:55
Held by voice, in the browser or over the phone.
Done well
You de-escalated early and did not take the objection personally — the thread of the conversation never broke.
Room to improve
The close failed because no verifiable evidence arrived while a great deal was being said. Three levers for next time:
Every sales training knows the exercise: two colleagues sit opposite each other and one plays the customer. After two minutes both are laughing, because it is silly. And even when they are not — the colleague playing the difficult buyer does not want to win. They want the exercise to go well.
That is exactly where it fails. A counterpart that gives way trains nothing. The skill in question only forms against resistance: when somebody probes, deflects, does not accept the price, and after the third evasion is still holding their position.
Then there is frequency. The conversations that cost the most when they go wrong are the rarest ones: the escalation, the termination, the framework negotiation. You cannot wait for experience when the opportunity comes round twice a year.
Three things, and the colleague in the seminar room has none of them.
After the conversation you have what nobody in a seminar room writes down: share of talk, speaking pace, questions asked, filler words. None of those numbers is a grade — they are observations somebody can act on.
The difference from a score matters. "You spoke for 56 percent of the time" is a sentence a person can respond to in their next conversation. "72 out of 100" is not.
Seven answers that come up before every demo.
For the first minute, yes. After that no, because the counterpart does not give way: it probes, deflects and remembers what you said two minutes ago. That is precisely where roleplay with a colleague fails.
Spoken. In the browser or over the phone. Practising in writing trains phrasing, not speaking under pressure — and the conversations in question are not typed.
From your material and your situation. You describe the position, upload the playbook, price list or recordings, and counterparts with a position and a goal come out of it — not generic role cards.
As often as they like. That is the point: the highest-stakes conversations are the rarest, and waiting for experience does not work when the opportunity comes round twice a year.
Audio is not stored by default. What remains is the read-out and the distance to the standard.
No. The Coach belongs to the person, not to their manager. What flows upward is aggregate progress against the standard, not the conversation itself.
Sleak is DSGVO-compliant with EU data residency, an AVV per Art. 28, and no customer data used for AI training. No emotion recognition, no biometric profiling.
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