This section covers what happens after practice: the properties of useful feedback, why a training score differs from real sales results, a scorecard for practice conversations, checking and correcting a simulation score, finding the team's recurring skill gap, and the division of work between AI feedback and the sales manager.
A practice score is a learning signal, not the basis for people decisions — that principle runs through every article. How evaluation is set up is on the Vexvon AI Training page.
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Sales skill gap analysis: three cuts by criterion, profile and recurring mistake, choosing one gap, a team plan and how much data you need.
Sales training scorecard: choosing criteria, observable descriptions, weights, a standard per profile, statuses and a sample results table.
AI sales coach and the manager: a division-of-work table, decisions never given to AI, a weekly 20-minute meeting and how to read reports.
What a sales training score measures and what it misses: four cases against real sales, real conversation quality, how to display it and people decisions.
AI sales coaching feedback: when feedback helps and when it harms, the four properties of useful feedback, and how to read the report.
Sales assessment fairness: five sources of error in simulation, a five-step correction procedure, fixing the system and the human final say.
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