Findings from inside broken booking machines. Jim Finneyfrock.
Five thousand leads collected. Zero ever contacted.
The automation was liking every comment, so the dashboard looked healthy. It just never sent the message. Nothing errored. Nothing went red. Six months.
You are already paying for the leads. I find the silent failures that make them worth less than they should be.
A number is off. Everybody has a story about why. The story is plausible, and the story is almost never the cause. The real cause is small, boring, mechanical, and silent. That is why it survives.
Jared Laurence, owner of the business I worked inside for four years. 70 seconds, his words.
The other thing I do
AI DM setting. I built one and ran it inside one business for four years, and it booked over $1.2 million in appointments from Instagram DMs. It worked because it was operated, not installed: it followed the proven human setting method, knew when to hand a conversation to a person, and got watched like production software, because that is what it is.
It is still for sale, downstream of the audit. Most businesses that ask for a setter have something already broken upstream of it, and bolting a setter onto that just makes the broken part run faster. So I find the problem first. If the audit says a setter is the answer, I build it, priced and scoped separately. If it is not, I say so, and that costs you nothing.
The archive
Findings from one hundred and four audits. Client names withheld, numbers unrounded. Write-ups publish as they clear client review.
Fifty of ninety-one booked appointments never happened
Fifteen cancels, sixteen no shows, nineteen reschedules. Nobody had ever counted it.
A 63% click rate into nothing
The best link in the stack had no funnel behind it. The hardest thing a stranger will ever do is care enough to click.
Two characters a paid developer had already missed
Reporting dark for months. A prefix in an identifier that was not part of the identifier. Twenty minutes to fix.
Five thousand leads collected, zero ever contacted
The automation liked every comment and never sent a single message. Six months of it, behind a healthy dashboard.
A 2.64 ROAS that was accurate and pointing the wrong direction
Two back end closes carried the entire return. The thing the ads were optimizing for was losing money.
Sixteen of sixteen accounts, and the welcome sequence never ran
The team had suspected onboarding for months and had been right the whole time. There was no mechanism attached to it.
One missing DNS record, four weeks of dead email
Under an hour to fix. It had already been explained away as a slow February.
Seven write-ups published. The archive grows as findings clear client review. Details that could identify a client are not published.
The audit
Every finding above was cheap to fix and expensive to leave alone. The DNS record cost four weeks of email. The five thousand leads cost six months of pipeline. The point of the month is simple: same leads, same team, more of them turning into booked calls that happen.
One month, one time. I go through the machine that turns attention into booked calls and find what is actually broken. I fix what I can fix inside the window.
Optional, after. I stay on the machine so the next silent failure gets caught in days instead of quarters.
- Every finding in writing, in plain language. What is broken, for how long, and what it has cost you.
- A ranked fix list. Ordered by what each fix is worth.
- The fixable things, fixed. Done inside the month.
- A straight answer. If the machine is fine, I say so. No padded report.
That has not happened yet, and I will not pretend it is a real risk to me. It is here because it should cost me something to be wrong about whether you have a problem. I do not guarantee results, because I do not control whether you act on what I hand you.
I do the work myself, by hand. That caps how many of these can run at once. If I am full when you call, I will tell you, and I will tell you when a slot opens.
Who this is for
This is not a beginner offer. It fits if most of these are true.
- You already generate real lead volume. Attention is going into the machine. The problem is what happens after.
- You have an appointment process that used to work. Setters, closers, a calendar, a show-up flow. Something worth auditing.
- A number has been quietly getting worse. Appointments, show rate, or close rate, and the explanation keeps changing.
- Your team has theories. Nobody has isolated the failure. That is the exact gap the audit fills.
- You spend enough that a 10 to 20% leak matters. If a silent failure would cost you less than the audit, do not buy the audit.
If that is not you yet, take the free write-ups and come back when it is.
How the month goes
- You give me read access to the machine. The platform, the ad account, the analytics, the inbox. No admin, no passwords.
- I go through it by hand. Not a scan, not a checklist. The archive above exists because somebody opened sixteen accounts one at a time.
- You get the findings in writing. What is broken, for how long, what it cost, what fixing it is worth. Ranked.
- I fix what is fixable inside the month. Most of it is. Case 019 took twenty minutes once somebody actually looked. Where a fix needs more than read access, you grant it for that one change and take it back after.
The examiner
Four years inside one coaching business running this exact machine. I built the AI setter that booked its appointments, and it did over a million dollars. The audits started because owners kept asking why theirs did not work, and the answer was never the setter. It was always something upstream, silent, and boring.
Book a call
Thirty minutes. You talk, I ask questions, and I tell you whether I think there is something here. If I think there is nothing, I say that, and we are done in fifteen.