A fractional CMO case study: $0 to $30M in year one

Scaile exists because of this story. In January 2023 I took over marketing at a FinTech SaaS company that had no brand, no website and a $20M revenue goal. By the end of that year its total revenue had passed $30 million, from zero. This is how it happened, in order, and what a smaller company can borrow from it when it hires a fractional CMO instead of building a 17-person department.

I'm Guy Miotke. I have 20+ years in marketing, digital marketing and revenue operations, and I've managed over $100M in marketing budgets. I told this story from the stage at the Financial Marketing Summit, and I'm writing it down here with the client anonymized. I'm not naming the company in a public post. The numbers below are the ones I'm willing to put my name on.

The starting position: no brand, no website, a team of three

The company started as a client of my own marketing firm. Then I became its Head of Marketing, and also head of IT and marketing automation, in January 2023. The team I inherited was three people. Two of them quit.

The goal on the table was $20M in revenue for the year. We had no brand, no website and not much of an audience. Only a slice of people were raising their hand for what we sold. We had to talk to a lot of people quickly, and the only way to do that was to fill calendars. So we ran a direct-to-calendar model: the job of marketing was to get people to book a demo. Everything we measured came back to booked demos.

Step one: begin with the end in mind

The first thing I did was not a campaign. I set the destination and worked backwards from it, the way you solve a maze by starting at the exit. A $20M year and a calendar full of demos told us what had to be true at every stage before it. That is the part of the job a junior team can't do for itself, and it's where I start every fractional CMO engagement too.

Step two: a KPI stack where everything has to add up

With one goal, I built one chain of numbers: a minimum standard at every step of the funnel. Fall below one and we were fishing in the wrong water.

• 65% of opt-ins submit an application
• 40% of applications become marketing qualified leads (MQLs)
• 65% of MQLs book a demo
• 55% of held calls become sales qualified leads (SQLs)
• 125% calendar utilization

On top of those sat cost per booked call, revenue per held call and return on ad spend (ROAS). Everything had to stack up. If one rate was off, we knew which step to fix instead of arguing about the whole funnel.

The second rule was to align every KPI to one point, the MQL. Then we cut the same data by funnel, ad, hook, media and copy, and combined the green winners. I call it "change the row label, change your life," because it is one data set read from a different angle each time.

Step three: attention versus intention

Not every buyer is ready to book a demo. Following Eugene Schwartz's awareness stages, buyers run from unaware, to aware of the problem, to aware of solutions, to aware of the product, to most aware. Attention marketing speaks to the people who aren't looking yet. Intention marketing meets the people who are deciding. At the bottom of that ladder, with the most aware buyers, I was willing to throw the kitchen sink and spend where the buyer was already deciding.

The rest of the approach was personalized, omnichannel messaging, which I call an audience of one. Buyers need many touches before they buy, so what each touch costs decides whether a channel is profitable at all.

Step four: faster creative with data and AI

Speed became the next problem. It was taking 10, 11, even 14 days to get an ad out, and when ad fatigue is the issue, that's too slow. By cutting the data up the way described above, and using AI and better data, we got ad turnaround down to 24 to 48 hours. We found likely winners within three to five days. We cut our testing budget by 35% and put that money behind ads that were working.

The same part of my talk shows creative lead time down 60%, SEO articles up 40%, creative testing output up 200%, and the scale test down from 10 days to 5 to 7 days. AI here is an inward-facing tool. It makes decisions faster, and it still needs a human element.

The results

Here is what the record shows. Every number is from the company's own results, with the client anonymized.

The company did it without outside capital. It was funded from revenue. In 2024 revenue beat 2023 despite ad costs (CPMs) inflating about 300%, a flash crash and dozens of copycat competitors.

What a fractional CMO would do the same for a smaller company

A company at $2M to $50M doesn't need a department. It needs the decisions I made in the first weeks, made by someone who has made them before. Specifically:

• Set the destination first. One revenue goal, and the chain of numbers that has to be true to reach it.
• Pick one conversion point. For us it was the booked demo. Measure everything against it.
• Build the KPI stack before spending. If you can't say what each step should convert at, you can't tell a bad ad from a bad offer.
• Use AI on the inside first. Faster analysis and faster creative, with a human on anything that touches your brand.

That's the work in my Fractional CMO engagement: I own strategy, budget and team one to two days a week, with weekly check-ins and monthly reporting. If you want a faster start, the 30-day AI Growth Sprint produces the audit and the 90-day plan. For the day-to-day detail, see what a fractional CMO includes, or the plain-English explainer on what a fractional CMO is.

What I would do differently

I'd bring in big data sooner. I'd use contractors early for agility. I'd optimize for the deep-funnel KPI sooner instead of the one closest to the top. And I'd learn native ads earlier. It's what I'd tell a smaller company to do on day one.