How to screen sales candidates without wasting interview hours

A confident candidate with a polished résumé and a firm handshake can still freeze the moment a real prospect pushes back. The problem with the traditional sales interview is simple: it tests interviewing, not selling.

The interview measures the wrong thing

You ask "tell me about a time you handled an objection," and you get a rehearsed story. What you actually want to know is: when a buyer says "we're happy with our current provider," what comes out of this person's mouth in the next three seconds? You can't get that from a story. You get it from a call.

What a work-sample actually looks like

Decades of hiring research point to one thing: the best predictor of job performance is a work sample — watching someone do a realistic version of the job. For sales, that means a live call against a buyer who objects, stalls, and goes quiet.

The catch has always been cost. You can't ask every applicant to run a mock call with a senior rep — that's hours of expensive time, and every interviewer scores differently anyway.

Standardize it, then scale it

This is exactly what an AI assessment solves:

• Same test for everyone. Every candidate faces the same personas at the same difficulty, so you compare like with like.
• No interviewer bias. Scoring runs across seven fixed dimensions with weights you set for the role.
• 15 minutes, not an afternoon. Candidates complete the calls on their own time, before anyone on your team spends a minute.

You walk into the interview already knowing who can sell. The conversation shifts from "can they do the job?" to "do we want to work with them?" — which is what an interview should be for.

Hiring the wrong sales rep is one of the most expensive mistakes a team can make. An objective read before the first interview is the cheapest insurance you can buy.

Curious what the report looks like? See a sample report or see how it works.