Before you spend another dollar on SEO, find out what your competitors are actually doing.
I do local SEO for service businesses, and I do it differently: I measure every business competing with yours — not a sample, all of them — and build your rankings on what the data proves your market rewards. I'm a systems engineer, not an agency, and the machine described on this page is one I run in my own business every day.
Why most local SEO fails.
When someone in your area searches for what you do, Google shows a map with three businesses on it, and those three get most of the calls. Which three is not random: Google weighs your business profile, your reviews, your website, how consistently your information appears across the web, and how close you are to the searcher — for you, and for every competitor near you.
That last part is what the SEO industry quietly skips. A ranking is a comparison. Whether you appear third or thirtieth depends on what the businesses around you are doing — and the standard tools let a marketer track maybe ten of them. In a real market, remodeling contractors in a mid-sized metro, say, two hundred businesses compete for the same searches, and the ones taking your customers are not always the ones anyone would think to watch. SEO done against a sample of the field is guessing with charts.
So I don't sample. The major SEO platforms all buy their data from the same small group of upstream sources — search results, backlink indexes, business listings, page crawls — and those sources sell direct access. I query them directly and collect your entire market: every competitor, every keyword that matters, every signal, continuously, into a data warehouse built for exactly this. Nothing is left out, which means nothing moves unexplained — and SEO stops being a matter of opinion and becomes a matter of reading the data and doing the work in the right order.
Every competitor, every signal, all the time.
The foundation of the SEO is knowing the field completely. For every business competing with yours, continuously: search rankings — tracked from a grid of points across your service area, because your ranking changes block by block, and you might be first on the map two miles from your shop and invisible five miles away where the bigger jobs are. Plus reviews and their growth rate, citations, backlinks, advertising, and site performance. Dozens of signal types, collected on a rolling cycle, kept forever.
What this buys you is explanations instead of theories. When a competitor outranks you, the data shows why — the reviews, the pages, the links — and the reason is usually fixable. When something in your market moves, you get an alert, not a surprise three months later. Every recommendation I will ever make to you traces back to something in this data, and you can ask to see it.
Watch it working, down to the dollar.
Data you can't see might as well not exist, so the second layer is custom software: dashboards built around your business and the questions you actually ask. Your map rankings across your territory, neighborhood by neighborhood, over time. Which competitors gained ground this month and what they changed. Where the calls came from. Live, with alerts when a number that matters crosses a line you set — not a monthly PDF.
And one number most businesses have never seen once: cost per booked job. I connect your ad accounts, call tracking, forms, and job records, so a marketing dollar can be followed to a lead, and a lead to booked revenue — organic and paid alike. This is how you know the SEO is working in the only terms that count, and it changes every marketing decision you make afterward. These aren't configured templates from a platform; they're built for you, the way a large company's internal tools are built, sized for your business.
The ranking work, done every time.
Google's local rankings reward consistency: reviews arriving steadily, review responses posted, business information correct in every directory, and fast follow-through on the customers search sends you. Every one of those is work that businesses start with good intentions and stop doing by March. So the third layer does it structurally.
Review requests trigger the moment a job completes — the moment the customer is most inclined to say yes — because review count and velocity move rankings, and because the bigger the job, the more reviews a customer reads before calling. Citations stay correct and consistent everywhere Google checks: tedious work, which is why it's usually done badly, which is why doing it well moves rankings. And the calls the rankings produce get captured, not leaked: a missed call gets a text back in seconds, every estimate gets a follow-up sequence that runs until the customer books or declines.
All of it runs as monitored software with failure alerts — if a sequence breaks, I know before you do. And the same connective layer that does the SEO work ties your existing systems together through their APIs, so the CRM, the marketing tools, and the job records finally operate as one machine. Ranking you is what it's built for; fixing your stack is what it does on the way.
The content and operations engine.
Rankings ultimately rest on content and responsiveness — pages that answer what your customers search for, review responses that are specific instead of canned, records kept current. That's judgment work: it requires reading something and deciding. It could never be automated before. It can be now. An agent is software that does judgment work within limits you define, and it's the fourth layer of the machine.
What the agents produce here: service and location pages built around the searches your market actually makes. Project write-ups and before-and-after showcases drafted from your job photos, in your voice, reviewed before anything publishes. A considered, specific reply to every review. CRM records completed and kept current. Inbound email triaged with drafts prepared. A monthly report that explains what happened and why — what moved, what produced calls, what needs attention — instead of charts you're left to interpret. The machinery produces steadily; you control what represents you.
And because the honest problem with AI is that it can report success on work it didn't do — confidently — every agent runs under two controls. Verification: every task produces a record, checked against source data by ordinary deterministic software, not by another AI; a failed check stops the work and notifies me. Graduated authority: a new agent only reads and reports; then it drafts and you approve; only proven, reversible actions ever run unattended, and anything involving money or a commitment to a customer requires approval, always. I came up in industrial automation, where a machine that misreports its own state causes real damage. If a system can't show its work, I don't ship it.
What this looks like when you hire me.
Start with the Market Analysis.
Every engagement begins the same way, because it's the only honest way to begin: I measure your market before recommending anything.
A complete measurement of every business competing with yours — rankings mapped across your service area, reviews, citations, backlinks, advertising, and site quality, side by side with your own. Then the findings, in writing: which competitors beat you for which searches, the specific reasons why, the order to fix them in for fastest return, and how we'll verify each fix worked. It's an SEO plan built from evidence, and it's yours to keep — usable whether you hire me, do the work yourself, or hand it to someone else.
If the analysis doesn't surface specific, fixable reasons you're losing to particular competitors — named ones, with the evidence attached — you don't pay for it.
I can't do this work for two competing businesses in the same market: the engagement is built on competitive intelligence, and you can't honestly serve both sides of a fight. One business per trade, per market. If your competitor gets here first, I'll decline your inquiry and tell you why — which should also tell you something about what your competitor now has.
Background.
I've been self-employed since I was 17. Over 25 years I've worked across industrial process automation, machine design, data engineering, graphic and motion design, and now AI infrastructure.
The through-line is systems that have to actually work. Industrial automation is where I learned verification: a controller that misreports its own state causes real damage, so you design the checking in from the start. That habit turned out to be exactly what AI needs, since it fails the same way — confidently, and silently.
Today I run my own competitive-intelligence platform — thousands of business domains in a single market, scanned on a 72-hour cycle, feeding a warehouse I designed and operate alone. The SEO machine described on this site isn't something I read about. It's the tooling I built for my own business, offered to yours.
"If a system can't show its work, I don't ship it."
Fluent across the stack, loyal to none of it. The right solution is usually simpler than the one being sold.
Analysis that looks only at your own numbers can't explain them. I measure the whole field.
"It ran" and "it's verified" are different states. Only the second one counts.
The infrastructure gap between large companies and small ones keeps widening. Closing it, one business at a time, is the point.
Tell me what's broken.
One conversation, no pitch deck. Describe your situation — a market you want to win, rankings you can't explain, marketing you can't measure — and I'll tell you plainly whether I'm the right person for it. If your competitor already hired me, I'll tell you that too.