Status: Delivered. Described from our own delivery records. Client identity, brand and commercial terms are withheld. Figures, where given, cover the period stated and nothing beyond it.
Context
A staffing business whose sales representatives need to handle industry-specific objections in live conversations.
The established way of building that skill is role-play with a manager, which depends on the manager's availability, the manager's own skill, and both parties taking it seriously at nine in the morning.
The problem
- Role-play sessions were difficult to schedule and therefore happened rarely.
- Quality varied with whoever played the prospect.
- Generic training scenarios did not reproduce the objections specific to the industries the team sells into.
- New hires ramped slowly because their first real practice was often a real prospect.
- Managers had no visibility into who was practising and where they were weak.
What we built
A conversation simulator embedded in the team's existing collaboration platform
So practice happens where work already happens rather than in a separate system nobody opens.
An AI counterpart tuned to the industry
Producing the objections and hesitations representatives actually encounter.
Real-time coaching feedback and suggested phrasing
During the conversation.
Scoring, gap analysis and exportable transcripts
So a representative can see where the conversation went wrong and a manager can see engagement across the team.
How we delivered it
- 1
Collect real objections
From recorded and remembered conversations — the simulator is only as good as the material behind it.
- 2
Frame what “good” means
Per category, with the sales leadership, before building any scoring.
- 3
Prototype the conversation loop
And test it with experienced representatives, who are the harshest and most useful critics.
- 4
Add scoring and gap analysis
Once the conversation itself was credible.
- 5
Pilot with new hires
Whose ramp is the clearest test.
How it was phased
Indicative phasing for work of this shape. Actual duration varies with data quality, access and decision speed.
What the client keeps
- The simulator and its source
- The objection library
- Scoring definitions and rubric
- Exported transcript history