Three stages, priced up front.
Most agencies start with a discovery retainer and end with a slide deck. I start by finding the leaks and putting numbers on them. Building anything comes after that, and you can stop after any stage and keep everything.
Sales Friction Diagnostic
Three weeks inside your sales process, done the way I run my own.
- Quote-to-order time study: where deals stall and die
- Call log review: what customers ask that a tool could answer
- Search and AI visibility audit: where buyers can't find you
- Leak map with revenue estimates per leak
- Prioritized build roadmap with scopes and costs
Build & Launch
The items from the top of the list, built and shipped.
- Self-service tools: configurators, quoting, spec generators, calculators
- Built from your real product data, not a template
- Static reference content and structured data so Google and AI can read it
- Deployed, indexed, and verified in Search Console
Operate & Compound
Tools and pages keep paying if somebody tends them.
- New reference pages that compound search authority
- AI citation monitoring: who gets named when buyers ask
- Tool updates as your catalog and pricing change
- Quarterly friction review against the original leak map
The delivery loop
Whatever the stage, the work follows the same loop I use in my own company. It's built for manufacturers: start from the product data, ship working tools fast, and let every asset strengthen the others.
Discover
Two parallel tracks. External: what your buyers actually search for, what AI engines recommend in your category, and where competitors are visible while you're not. Internal: a process map and time study of your quote-to-order cycle, plus an inventory of the product data trapped in spreadsheets, PDFs, and tribal knowledge.
Your part is small: drop your catalogs, spec sheets, price lists, and installation guides in a shared folder. AI-assisted analysis structures them in days, not weeks.
Diagnose
Overlay the external demand signals on your internal process. Which customer needs map to which workflows? Where is valuable data (specs, compatibility rules, pricing logic) sitting in a format neither customers nor search engines can use? Every finding gets a revenue estimate and lands on the leak map. This is where build-versus-optimize decisions are made, before any money is spent on building.
Build
Working tools, not wireframes: product configurators, quoting tools, spec builders, selection wizards. AI where it earns its keep, not AI for the demo. Alongside every tool goes the static reference content and structured data that makes the data inside it visible to crawlers and AI systems. The tool serves your customer; the content layer makes sure they find you in the first place.
Launch
Deploy, index in Google Search Console, verify the structured data renders, and watch the rankings and AI citations. Then watch the users: which configurations get quoted most, where people drop off, what they ask next. That usage data feeds your sales process, not just the website.
Compound
Each new tool page strengthens the others through topical clustering. Each tool generates usage data that informs the next build. Your digital moat gets wider over time instead of just being maintained. That's what the Operate stage tends, and it's why this work behaves like an asset instead of an expense.
What you won't get
No 90-day onboarding
The diagnostic starts the week we sign. You'll have findings in your hands inside three weeks, not a kickoff deck.
No black box
Every deliverable (the leak map, the roadmap, the tools, the content) is yours. Documented, handed over, and executable with or without me.
No army of juniors
You work with me. I'm the one who runs the diagnostic, writes the roadmap, and builds the tools, the same way I do for my own company.