Although I was most heavily involved for only the last 4-5 years, I spent nearly a decade helping grow my family's automotive business. As COO of Gateway Auto, I watched us go from $3 million to $11 million in annual revenue, and a lot of that growth came from pushing the team to think differently about technology and digital marketing before most shops in our market were willing to try. We were a radically different company than when I was a little kid detailing cars when we first opened.
Now I understood this industry. I thought I knew what it needed.
So when Alex and I started building our first software company, we built for the problem we understood best.
We called it LeadFoot Analytics.
The idea was straightforward: shop owners are drowning in data and paperwork that they don't have time to interpret: What if we pulled everything revenue, repair times, technician performance into one dashboard and put an AI assistant on top that owners could actually talk to? Not charts and spreadsheets. Conversations. The AI would surface what mattered and turn it into real action items for themselves and their teams.
We believed in it. We called shops. We ran demos. Some owners got genuinely excited – one liked it so much they floated the idea of buying the software outright just to have the tool for themselves.
But here's what we kept running into: most shop owners didn't care. Not because the product wasn't good. Because they had a more urgent problem than the one we were solving.
The large majority of shops weren't worried about optimizing. They were worried about staying afloat. Their minds were focused on getting new customers in the door, getting their name out there, and growing, in general.
It's easy to look back and see things clearly. One of the biggest lessons (and honestly, one that applies well beyond automotive) is that only a small percentage of people in any industry actually want to optimize to the level that most software is trying to get them to. There are a lot of business owners who are genuinely fine with getting by. But they don't want like week to week getting by, maybe even not month-to-month. But a few months of rent in the bank, enough to have backup in a catastrophe so they can feel comfortable, not stressed – that's good enough. Not everybody has the drive to chase multi-million dollar growth year over year, and that's okay. But it means when you're selling optimization software, you've already cut your market down significantly before you've even started your pitch.
And there's another layer to it: in all sense of value, we were selling time. Time back in their day, time saved on reporting, time reclaimed from operational chaos. That's a hard sell to people who don't feel that pain or don't understand it well enough to even know they need to be doing some of it. You're asking someone to invest effort upfront in learning a new tool, getting their team on board, changing habits, in exchange for a payoff that's often several months or more down the road. For a shop owner who's already stretched thin, that's a tough ask.
Compare that to what we're now doing with Service Stories. We're not selling optimization. We're selling money. You plug this in, you get more traffic, more customers come through the door, you grow. That's an easy value proposition to understand, and whether you're a small shop just trying to grow enough to be comfortable or your an MSO trying to create the next national brand, it makes sense without a second thought.
When I started talking to people about it, I didn't have to convince them of anything. The conversation basically went: "So you take my repair order and turn it into a story that brings people to my website?" Yeah. "And if I do that a few times a week, my traffic grows and more people call me?" Exactly. "Okay, that makes sense."
Service Stories is a no-brainer. It's direct. It makes money. And honestly? It's fun to talk about, and even more fun to watch it work for people.
That was the biggest reason we pivoted. LeadFoot could have been a good business. It just wasn't the one we wanted to chase.
Service Stories was born after we fully gave up on LeadFoot and just went back to work. I knew we didn't know what we wanted to do but I also knew if we just focused on doing our job 40 hours a week something would come to us. So the first step: I went back to Gateway Auto and filled my week focused on growth marketing.
For the first time in almost ten years, I was there full-time, 40 hours a week, with something I hadn't had in a long time: space to think. I wasn't working part-time on multiple contracts. I was full time on Gateway Auto, especially focused on growth marketing. And my choice was to point that energy at something I'd been pushing our marketing team toward for years without ever fully cracking it: long-tail, natural language query SEO content at scale.
This wasn't a new obsession. I'd known about it since I was building chatbots in Silicon Valley. For five or six years, I'd been convinced that conversational, natural-language search was going to reshape how customers find businesses. The problem was always execution. To capture long-tail keywords at any real volume, you need content at volume – and content at volume either costs a fortune in writers or gets reduced to generic templates that say nothing worth reading.
In previous years I pushed it on our interns, they thought it was rocket science trying to figure it out. I pushed Alex to figure it out while I managed other parts of the business, he already had too much on his plate. Now it was my turn, full-time.
I started experimenting. Maybe I could map every year, make, and model we serviced and push the data through a content template. Programmatic SEO is very common but also under utilized in service businesses. It seemed reasonable until I actually tried to do it. The templates would need constant updating. Every piece would read exactly like every other piece with only slight variation. And more importantly, what was the actual story? What was I writing about? Beyond keywords stuffing and symantic page structure, would the content just turn into something more likely to get us penalized than rewarded? All these thoughts swarmed my head for several weeks as I tried to figure out a solution.
Then something clicked.
The stories were already there. They had been there for years, sitting in every closed repair order in our Tekmetric system – the same system LeadFoot had been built to integrate.
Each ticket wasn't just a record. It was a complete narrative:
Every single one was different, because every single job was different. A 2014 Silverado with a specific transmission issue is not the same story as a 2019 F-150 with the same symptom. The details matter. And we had thousands of them. Tens of thousands of them. We'd have content for a decade!
I grabbed a handful of tickets and dropped them into ChatGPT to test the idea. The output was rough. The understanding of various automotive acronyms were wrong, the technical details were close but not close enough to publish under our name. Each story probably needed an hour of editing by someone who actually knew what they were looking at.
But that wasn't what I focused on. What I saw was that the pattern worked. It needed work and there was a lot of training to do in any given AI implementation, but it was possible.
The data could become content. Each piece would be genuinely unique and expert. And if the AI could be trained on labor guides, real industry language, and actual shop knowledge – not Reddit threads and DIY YouTube videos – it could get the details right. Not approximately right. Accurately, authoritatively right, and at scale. Written as if an expert from your industry wrote it themselves, but accessible to anyone reading it.
At the same time, something else was reaching a tipping point I'd been watching for years. People weren't just Googling anymore. They were asking ChatGPT. Querying Perplexity and Claude. Google's own AI Overviews were rewriting what search results even looked like. I had seen this in testing at Google 8 years ago and I knew it was coming – heck, I helped build some of the first chatbots the industry had come to know. But the timing couldn't be better. The conversational search future I'd been pushing toward was finally arriving, and it was accelerating fast.
Everything was coming together at once:
Eight months. Zero revenue.
And somehow, the thing that came out of it was the foundation for everything we'd build next. The database we built to understand a shop's operations could now be pointed in a completely different direction: not inward at efficiency, but outward at visibility.
That's Service Stories, the platform you use to turn your daily work into AI answers.
Next: How we figured out the name, who we sold it to first, and what those early conversations actually looked like.
