Feature · Objective Scoring

A score that measures everyone the same way.
Backed down to the line in the transcript.

The same rule for every call, no matter who makes it. Every score shows the line in the transcript it came from. You choose the scoring framework yourself; eight are available.

Three training sessions freeNo credit cardData stored in Germany

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How the score is produced

Three runs. One rule. No black box.

The path from recording to score: on the server, not inside the language model.

Scored three times, not once

The model scores the same call three times, independently. The median counts, and the spread is reported. Outliers show up instead of deciding the score.

Combined by a fixed rule

A fixed weighting turns the five dimensions into an overall score from 0 to 100. The server does the math, not the language model. Anyone can recheck it.

Backed by the line

Every sub-score names the line in the transcript. You see not just that something was missing, but where.

Transcript · Line 47 Dimension: Objection Handling −12 points

Prospect: "Honestly, that's too expensive for us." Rep: "I understand. Let me show you the next feature …"

The price objection was sidestepped. Better: narrow the objection first ("What exactly is too expensive, the price or the value for the money?"), then frame the value. The score hangs on this moment, not on a blanket judgment.

The scale

The same bands apply to every score: training and real call, German and English.

  • 30–45complete miss / no substance
  • 55–67serviceable with clear gaps
  • 68–80solid and competent
  • 82–90strong
  • 90–100excellent
The five dimensions

Five dimensions that carry a call.

No catch-all grade. Each dimension is scored on its own, against the chosen framework.

01

Needs Analysis

Was the real need uncovered? Open questions, consequences, depth instead of monologue.

Discovery questioning · Qualification · Budget check
02

Objection Handling

Was the objection recognized, narrowed, and resolved, or talked over?

Pain-first · Closing Mindset
03

Value Selling

Feature or value? Scored on whether the benefit ties back to the customer's need.

Teach & Lead · Value
04

Closing Strength

Commitment instead of stalling: next step, closing question, agreement.

Qualification Framework · Closing Mindset
05

Conversation Control

Talk ratio, listening, pace, structure. Who leads: rep or customer?

all frameworks
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Numbers from the transcript

Counted, not estimated, alongside the AI score.

Talk ratio Question rate Filler words Hedging language Vocabulary diversity
Selectable scoring frameworks

You choose the framework. The scoring follows it.

Eight scoring frameworks, switchable per training session. The scoring sets its expectations by the chosen framework instead of treating every call the same.

Discovery Questioning Method with Qualification Framework

default

The default: discovery questions plus qualification of buyer, criteria, and process. Need and decision path in one pass.

Discovery Questioning Method

discovery questioning

Situation, Problem, Implication, Payoff. Rewards developed need over an early pitch.

Qualification Framework

qualification

For complex deals: metrics, economic buyer, decision criteria, decision process, pain, champion. Measures how mature the decision is.

Budget & Decision Check

budget-check

Budget, authority, need, timeline. Scores whether all four were properly covered.

Pain-First Method

pain-first

Pain, budget, authority. Rewards surfacing the real pain early and giving no unpaid consulting.

Teach & Lead

teach-lead

Teach, tailor, take control. Scores whether the rep brings a new perspective and leads the call.

Closing Mindset

closing-mindset

Commitment and consistent objection handling. Tailored to the German-speaking market.

Core-Need Method

core-need

Core need, economic impact, access to the decision maker, a justified timeline. Depth instead of symptoms.

The default is the Discovery Questioning Method with Qualification Framework. Switch frameworks per training session.

The difference

Recheckable, not guessed.

Many tools let a language model guess a number. Run it again and you get a different one. A score like that cannot serve as a team's yardstick.

Comparison of scoring approaches, as of 2026.
Criterion sip.coach Typical AI scoring
Stability Three runs, median, spread reported Varies (e.g. 78, then 84)
Calculation Fixed rule on the server Free estimate by the model
Traceability Line in the transcript per sub-score Blanket judgment, no evidence
Scoring frameworks Eight, selectable per training session Usually one fixed, hidden yardstick
Audit Recheckable, aligned with the EU AI Act Black box, hard to verify
Numbers from the transcript Talk ratio, question rate, filler words Usually not reported
Frequently asked questions

Scoring & methodology: clearly answered.

Every call is scored three times, not once. The median of the three runs counts, and the spread is reported. The overall score is computed by a fixed rule on the server, not by the whim of the language model. So every score can be rechecked, including by auditors and works councils.
Five dimensions are scored separately: needs analysis, objection handling, value selling, closing strength, conversation control. A fixed weighting turns them into an overall score from 0 to 100. On top come numbers from the transcript: talk ratio, question rate, filler words, hedging, and vocabulary.
Every sub-score names the line in the transcript where it came from. You see not just a number but the moment where an objection was missed or the closing question was avoided. Instead of "too little empathy," it says which sentence was missing.
Eight scoring frameworks: Discovery Questioning Method with Qualification Framework (the default), Discovery Questioning Method, Qualification Framework, Budget & Decision Check, Pain-First Method, Closing Mindset, Teach & Lead, and Core-Need Method. You pick the framework per training session, and the scoring sets its expectations accordingly.
Many tools let a language model guess a number. The same recording then gets 78 one time and 84 the next, and nobody can say why. sip.coach scores three times, takes the median, computes the overall score by a fixed rule, and backs every sub-score with the line in the transcript. That holds up to scrutiny and is aligned with the EU AI Act.

Your first call. Your first score.

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