AI Sales Agent Oversight

An AI agent is talking to every lead you get.
Who is checking what it says?

We don't build your AI sales agent. We hold it to account. Metrix reads every conversation it has, charts what it is doing to your pipeline, audits where it goes wrong, and sends the fixes to whoever runs it.

Works with any supplier·Every conversation read·Audits sent weekly
Analytics dashboard: total leads, engagement rate, conversion rate, median first response, average interactions to conversion and converted revenue, with the sales funnel and leads over time
The challenge

You have an AI closing your sales, and no idea whether it is any good.

Your AI agent answers every enquiry from your website, email, WhatsApp and web chat. Quoting prices, following up, handing over to your team. Thousands of conversations a month. It replies in under a minute, day or night, and never forgets to follow up. What you cannot see is the quality.

01
Did it answer the question the customer actually asked?
02
Did it give a price when it was asked for one?
03
Did it apply the offer it mentioned two messages earlier?
04
Did it hand over the ones it should, and close the ones it could?

Your AI provider supplies headline numbers, but there is no real visibility into what is happening inside the conversations: what is working, where leads are being lost, or what the AI needs to improve. You are trusting the AI without truly measuring it.

See what your agent is really doing
The dashboard

The analytics layer your agent never had.

Every conversation your agent has ever had, analysed, measured and turned into clear insight. Filter by location, channel, lead source and date, with every figure explained in plain English, including how it was calculated.

Where in the conversation are we losing them?

•Total leads and engagement
•Conversion and revenue
•Median first response
•Interactions to a conversion
•Funnel, with the biggest drop named
•Conversion by location and by month
•Customer reply speed, in nine bands
•Enquiries and replies by hour
•Leads still live, with a quiet count
•Out-of-hours activity
Sales funnel: total leads, replied at least once, handed off or won, with the biggest drop named as 77% never reply
How fast customers reply, in nine bands from under five minutes to longer than a week
How fast customers come back, in nine bands. Most take days, not minutes.
Conversion by the message that got a reply: replied, won and conversion rate for one, two, three and four or more messages
Conversion by which message got the reply. The first one converts best.
When customers reply, by hour of day with the opening-hours band shaded, plus the busiest day and how out-of-hours enquiries convert
When customers are awake, and what happens to the ones who arrive out of hours.
The audit

Analyse. Feedback. Improve. Repeat.

Every week, Metrix audits your AI agent's conversations, identifies opportunities for improvement and turns them into actionable feedback. The result is an accountable, continuous improvement loop that would be impossible to achieve through manual review alone.

01
A balanced sample, every week

We review a mix of won, lost, unanswered and escalated conversations each week, so you see the full picture, not just the best cases.

02
Every conversation read in full

Duplicates and quoted email chains are removed, so each conversation is reviewed exactly as your customer experienced it.

03
Issues pinpointed to the exact message

Each issue is flagged where it happened, with its severity and the response the agent should have given.

04
Progress you can measure

A handled-well score tracked week on week, with every issue ranked by frequency, so you can see each fix take effect.

A finished audit week: nineteen conversations reviewed, handled-well rate, flags raised, the most common flag, severity split, and the shared queue of conversations still to read
A completed weekly audit: conversations reviewed, how many were handled well, and the most common issue.
A flagged agent message in the audit view: the issue tag Missed offer or promotion, severity Major, the customer's earlier message quoted as context, what was wrong, and what the agent should have said instead
The flag sits on the message itself, with the customer's own earlier words as the context that was missed.

Don't just identify the problem. Show the AI how to improve.

The reviewer provides the response the agent should have given, turning every finding into a clear, actionable training instruction.

Case study · What we found
A UK self-storage business, 5,000+ enquiries handled by an AI sales agent

The agent was handing over questions it could answer itself.

A price. A size. Whether a unit was available. It answered exactly those questions perfectly well elsewhere in the same week, so this was a habit, not a limitation. Every time it did it, a customer who was ready to book was handed a wait instead of an answer.

What kept happeningHow oftenWhat it costs you
Handed over a question it could have answered itself Most common in the data A live buyer waits on a branch callback instead of getting an answer and booking
Went quiet on a customer who was still asking Regularly, every month An engaged lead, the hardest kind to get, abandoned mid-conversation
Handed over, and the customer never heard back Regularly A qualified handover, the closest thing to a sale, dropped by the team
Chased again after the customer asked us to stop Rare, serious when it happened The lead is lost and so is the brand, and it is a compliance risk besides

Every one of these happens at the point the customer was still interested. The third is the only pattern about the team rather than the AI, and it is the most expensive of the lot, because those leads had already put their hand up.

Didn't answer the question

A customer asked where the site was. He had just committed to the twelve-month option, that question was the last thing standing between him and a booking. The reply handed him to a human without answering it.

Missed the offer

A customer volunteered a competitor's price of £90. The agent came back with three prices, all higher, and left the price-match guarantee to the last line. The 50% offer it had already mentioned twice was never applied.

Price withheld

Eleven days and ten messages before a price appeared, and only once the customer asked outright. The price had been on the enquiry from the start. In another, she had to say she was not interested to get a number out of it.

Ignored the customer

A customer answered what he was storing on the 23rd. The same three questions went back out on the 23rd, 24th, 26th and 30th. Four rounds asking for information already given, with no price offered in between.

No follow-up at all

One opener, then silence, on enquiries with a known start date a fortnight out. Other enquiries in the same week got four messages.

What it adds up to

Small moments. Repeated at scale. Significant impact.

None of these are complex problems. They are small behaviours that a good salesperson would recognise and correct immediately. But when AI is handling every enquiry, those same behaviours repeat across thousands of conversations, largely invisible in headline conversion figures.

Every conversation is an opportunity to learn. By identifying these patterns, feeding them back and continuously improving the agent, small improvements compound into significant commercial results.

£481k
in quoted sales that didn't convert
across 5,000+ enquiries handled by the AI agent
Three things they could not see before

What turned up in the first month.

01
#1 flag
The AI was missing clear signals to close the deal

Customers asked for a price, a size or availability, the moment they were ready to book, and the agent handed them to the team instead of answering. A wait instead of a sale.

02
13.6% vs 7.8%
Timing changed the result

Enquiries handled during opening hours converted at 13.6%. Those arriving out of hours converted at 7.8%, even though the AI replied just as fast. Same agent, very different outcome.

03
21.9% → 5.0%
More chasing is not more closing

Conversations closed in a single message converted at 21.9%. Nearly two thirds of enquiries needed four to six messages, and those converted at just 5.0%.

Automated reporting

Two reports, two jobs.

One tells the business how the agent is performing. The other tells whoever runs the agent exactly what to fix.

Report 1 · MonthlyPerformance reportFor the business · How is the agent performing?

Sent to the business every month. Leads, funnel, conversion by month and by location, response and reply timing, out-of-hours activity and why the losses were lost. Twenty-one sections, each one switchable, so it says what that customer wants it to say.

Monthly AI sales performance report, page one: total leads, engagement rate, conversion rate and converted revenue against target, then the sales funnel
Monthly report: leads by site ranked, and conversion rate by month against the concluded-leads denominator
Monthly report: how many messages went out before the first reply, and how fast customers reply in nine bands
Headline numbers and funnel, then location by location, then the message and reply timing.
Report 2 · WeeklyAudit reportFor whoever runs the agent · What needs fixing?

Sent every week to whoever runs the agent, your team or your AI provider. How many conversations were read, how many were handled well, every issue ranked by frequency with movement against last week, and each flagged conversation in four lines: what the customer asked, what the agent said, what was wrong, what it should have said. A spreadsheet comes attached with a blank column for them to record what they fixed.

Weekly review report, page one: conversations reviewed, handled-well rate, how many carried an issue and how many were critical
Weekly review report: flags by severity, and every issue checked for ranked most common first with movement against last week
Weekly review report: each flagged conversation set out in four lines, what they asked, what the agent said, our comment, and what it should have said
The score, then every issue ranked, then each flagged conversation in four lines.

The audit is not a report card. It is a work order, and the blank column shows what was fixed.

Works with the agent you already run

You bought the agent.
We'll tell you if it's selling.

We don't replace your AI sales agent and we don't need to change how it runs. We connect to the conversations it is already having, then build the analytics, the audit and the weekly feedback loop around it, whoever built it.

Want to see how it works? Give us 15 minutes.

We'll screenshare a live system, show you the dashboard, a real audit and the weekly feedback report, and discuss how we could point it at your agent.

Book a 15-minute demo
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