“AI speech analytics” gets used loosely enough that it is worth answering plainly: it is software that turns every one of your phone calls into text, then scores that text against criteria you set, so a manager can see what happened on a call without having to have been on it.
That is a narrower claim than it sounds. A transcript on its own is not analytics, it is just the call written down. Analytics is the layer on top: reading that text for the things you actually care about — did the rep follow the script, did the customer raise an objection nobody answered, did the call end with a next step or just a hang-up.
The three layers underneath the term
Strip away the marketing and the term covers three distinct jobs, stacked on top of each other.
Speech becomes searchable text, word for word.
The text is checked against a checklist: script adherence, objections, tone, whatever you defined.
Individual scores roll up across a day, a rep, or a script version, so a pattern is visible and not just one call.
A tool that only does the first layer is a transcription service, not analytics. The second layer is what makes it useful to a manager. The third is what makes it useful to an owner, because a single flagged call is an anecdote and a hundred flagged calls scored the same way is a pattern.
The problem it exists to solve
Before this category existed, a manager reviewed calls by listening to them, and listening does not scale. In our own operations, running call floors before Locator existed, a manual review reached 3-5% of conversations — our own operating figure, not an industry study. That ceiling has nothing to do with how good the reviewer is; there simply are not enough hours to listen to everything by hand.
So the category exists to close that gap: not to replace judgement about what to do with a bad call, but to make sure every call is actually looked at before anyone decides what counts as bad.
What it actually checks, call by call
“Speech analytics” is not one fixed checklist — you set the criteria, because a dental clinic and a debt-collection desk are not listening for the same thing. Locator's own default groups the checks into six areas, and most deployments customise from there:
- Sales stages — greeting, needs discovery, presentation, pricing, upsell
- Customer handling — objection handling, active listening, interrupting, tone
- Standards compliance — script adherence, banned phrases, required disclosures
- Wrap-up — confirming agreements, the next step, a proper sign-off
- Speech and delivery — pace, hesitation, filler words, confidence
- Cross-call analytics — recurring requests, common objections, where deals are lost
Notice that the last group is not about any single call at all. Once every call is scored the same way, patterns across hundreds of them become visible — which objection actually kills the sale most often, which script line customers consistently misunderstand — in a way a handful of manually reviewed calls never could.
What it is not
Two things get assumed about this category that are worth correcting directly, because they set the wrong expectation before anyone buys.
It is not a live-monitoring tool. Analytics of this kind reviews a call after it ends; it does not sit on the line, whisper prompts to an agent mid-call, or intervene in a live conversation. A tool that does that is solving a different problem and is usually sold as one.
And it does not decide what happens to a person. A score is evidence that a call went a certain way, not a verdict on the agent who took it. Coaching, discipline, or anything that affects someone's job still needs a manager to look at the specific calls and make that call — the software's job ends at making sure nobody has to guess what happened.
A score is evidence a call went a certain way. It is not a verdict on the person who took it.
How Locator does it
Locator is Benerra's own speech-analytics layer, built to the shape described above: it listens to 100% of a client's calls, scores every one against a checklist the client sets, and rolls the results up into where a team is strong and where it is losing customers. It usually runs before anything else we build, because it shows what customers and operators actually say before we design a voice agent meant to talk to either of them.
The point of the category
Speech analytics does not make the judgement calls. It makes sure the judgement is being made about all of your calls, not a sample of them.
If the question that brought you here was practical rather than definitional — what it costs, what it needs from you, where it stops — the Locator page answers those directly, checklist included.