What your customers really ask, counted instead of guessed.
Every business has a list of questions it thinks customers ask. The calls, chats and emails hold the real one. We turn those conversations into tagged, counted findings, so the website, the scripts and the training fix what actually comes up.
What tagging looks like up close.
A sample chat for a made-up home services company. Each highlighted part gets a tag from a written list, so the same thing is counted the same way every time.
The questions, ranked by how often they come up.
Sample counts from a made-up month of 400 conversations. The red bars are questions your website could answer on its own.
We have done this for sent email.
For a client worried that its emails were landing in spam, we read the raw history of everything its CRM had sent. Delivery turned out to be fine. The review found three other problems instead:
- Sent twiceThe same email went to the same people more than once.
- Sent to the wrong peopleIntroductions meant for new prospects reached existing customers.
- A broken greetingEmails opened with a broken merge field instead of a name.
The fix was the copy and the targeting, not the sending setup. Calls and chats get the same treatment: read what really happened before deciding what to change.
For calls and chats, step by step.
Collect with consent
Chats and emails are already written. Calls need recording, with the notice your state requires. We point you to the rules in plain language; this is not legal advice.
Transcribe
Speech-to-text from a service you approve, or on a machine in your office if recordings must not leave it.
Agree the tag list
Fifteen to thirty tags written with your team, each with an example. A language model applies them; a person checks a sample every week.
Count and report
A monthly ranking, plus the conversations behind each number so anyone can read the real thing.
Fix the top three
A website answer, a script line, a training note. Next month's counts show whether it worked.
What it is not for
- Secretly scoring staffIf reviews feed coaching, your team knows how and why.
- Keeping recordings foreverYou set a retention period and it is enforced.
- Card numbers or health details in a reportThose are masked or left out.
About reviewing conversations.
How many conversations do we need for useful counts?
A few hundred a month gives clear rankings for the common questions. With fewer, we review them all by hand with AI help and report themes rather than percentages.
Can this check an AI assistant's conversations too?
Yes, and it should. The same tags show where an assistant answered wrongly or should have handed over to a person.
Which phone systems can you work with?
Most business phone systems can export recordings or send them on automatically. We check yours before quoting and say if it cannot.
More on what customers say
Where the findings get used.
Agent monitoring & debugging
Reviewing what an AI assistant said.
Knowledge base build-out
Turn the top questions into written answers.
Phone answering agents
Answer the common calls from approved facts.
Email & text campaigns
Fix the sends the review flags.
What makes an AI phone call feel natural
And why most don't.
What do you think customers ask most?
Write your guess down, then book a free call. We will tell you how to check it against the real conversations.