Persona scenarios are AI customers modelled on the calls that actually go wrong. Your team practises the hard conversation as many times as it takes, before it lands on a paying customer.


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The angry callerHard
The property managerModerate
The quiet callerEasyA supervisor playing an angry caller is still a colleague. They soften, they prompt, and they run out of time after two goes.
A persona does not soften. It interrupts, it pushes on price, it changes its mind halfway through, and it is available at eleven at night when your new starter finally has a spare twenty minutes.
Straightforward, tricky and hostile. New starters begin low and earn their way up.
Every persona has a job, a budget, a temper and a history, so the conversation goes somewhere.
Objections on price, availability and trust, delivered the way customers actually deliver them.
The same scenario can be run again and again until the response is second nature.
Every persona conversation is scored against the same rubric your real calls are scored against, so practice and performance are measured in the same language.
Supervisors can see which personas a rep keeps losing and set the next round of practice against exactly those.
We sit on top of the system you already run. We do not replace it.
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