Case Study
Mox Multisport Platform
I built and operate the digital platform layer for Mox Multisport: a production Next.js system that turns service expertise, product discovery, customer intent, lead capture, behavioral analytics, and sales follow-up into one operating platform.
The goal was not just to build a website. The goal was to platform the business on purpose: position the expertise, guide the customer journey, capture demand, and create more qualified bike sales opportunities.
Business Positioning Strategy
I engineered the platform around the way the business needed to be understood.
The platform was not built as a generic bike shop website. I structured Mox around the business model I saw inside the operation: premium service, expert fitting, complex repairs, custom builds, dealer authority, product education, inquiry-based sales, and follow-up workflows.
The positioning was intentional. The site teaches customers that Mox is not a mass-market inventory shop. It is a specialist service-commerce business where fit, trust, mechanical expertise, product guidance, allocation timing, and final setup matter before the sale happens.
That positioning shaped the platform architecture: service pages, fitting funnels, Dogma positioning, X-LAB allocation language, quote paths, lead intelligence, behavioral tracking, email workflows, and operational follow-up were all designed to support the same sales system.
Service-Commerce Pattern
Built for high-ticket service-commerce, not simple ecommerce.
Mox was the right production environment because the business is not easily solved by a basic Shopify storefront. The customer journey is closer to high-ticket service sales: search, research, trust-building, inquiry, consultation, fit confirmation, quote, deposit, fulfillment, and follow-up.
This same pattern applies beyond cycling. A plastic surgery practice, med spa, luxury salon, custom automotive shop, specialty clinic, or premium home service business also needs more than a static website or simple checkout. They need pages that qualify intent, forms that capture context, workflows that guide follow-up, and systems that connect customer interest to revenue.
The reusable platform is service-first, not cart-first. It is built for businesses where the sale happens through expertise, trust, consultation, and follow-up instead of a standard checkout flow.
Digital Authority Positioning
Platforming the business meant platforming the expert behind it.
Mox needed to be positioned around expertise, not just products. I helped turn the shop’s service knowledge, fitting experience, triathlon background, and high-end bike support into public-facing digital authority.
The service architecture, homepage positioning, fitting pages, Dogma content, and X-LAB launch flow all work together to make the business easier to understand: expert service, fit-first guidance, premium bike support, and high-consideration sales.
This is part of the platform value. Internal expertise becomes searchable content, customer trust, inquiry quality, sales context, and a clearer path from interest to follow-up.
Demand-Led Allocation Workflow
The system does what it was designed to do: create qualified bike sales opportunities.
The X-LAB workflow was built around demand capture, not passive product display. The page explains the allocation-based buying process, teaches the customer what information matters, and turns product interest into model, size, color, and next-step intent.
That gives the business a better ordering model. Instead of guessing what inventory might sell, the platform captures what customers are already asking for, then supports follow-up through availability checks, deposit links, work orders, and fulfillment.
Demand Captured
Model, size, color preference, source page, CTA, and buyer message are captured before inventory decisions are finalized.
Intent Qualified
Session path, scroll depth, time on page, device, referrer, and customer actions separate casual traffic from serious buying intent.
Order Path Enabled
The business can follow up with availability, deposits, allocation timing, work orders, and final setup instead of guessing what to stock.
Platform Systems Built
The platform is made of reusable business systems.
I built the platform as connected systems instead of isolated pages: acquisition, lead intelligence, service-commerce workflows, analytics, and production operations.
Customer Acquisition
- Product, fitting, service, and custom build lead funnels
- SEO-focused route architecture for local and product-specific search
- Conversion-oriented inquiry forms and CTAs
Lead Intelligence
- Customer Intent Report emails
- Session path, device, referrer, and engagement metadata
- Search queries, clicked results, customer actions, and form context
Service-Commerce Architecture
- Product model for bikes, fittings, services, dealer pages, and builds
- Quote request and inquiry workflows
- Service-first structure for high-consideration sales
Production Operations
- Reusable component architecture for pages, CTAs, modals, and forms
- Analytics tracking for traffic, attribution, engagement, and conversion
- GitHub, Vercel deployment, maintenance, and production iteration
Technical Stack
Built with production Next.js, TypeScript, analytics, and workflow tooling.
Frontend
Platform & Deployment
Analytics & Tracking
Lead & Email Systems
Architecture
Email Intelligence System
Customer Intent Tracking: what was the customer doing before they contacted us?
Traditional contact forms capture name, email, and message. The Email Intelligence System captures session path, search queries, clicked search results, customer actions, device context, engagement metrics, and referral source, then packages that data into a Customer Intent Report sent to the business owner.
Service-Commerce Pipeline
Search Intent → Product Discovery → Page View → Form Submission → Customer Intent Report → Sales Conversation with Full Context
Business Impact
The platform works because it does what it was designed to do.
It gives the business more than traffic and form submissions. It captures why a customer arrived, what they viewed, how engaged they were, which product or service they cared about, and what context the team needs to respond with the right next step.
The result is a platform that connects positioning, customer education, lead intelligence, demand capture, and operational follow-up into one sales-support system.
Business model fit
Designed for premium service businesses where the sale happens through inquiry, consultation, quote, deposit, fulfillment, and follow-up instead of standard cart checkout.
Development approach
Maintained through a production workflow built around TypeScript, reusable components, deployment discipline, analytics review, and incremental iteration.
AI-assisted workflow
AI-assisted planning, documentation, refactoring, code review, system modeling, and architecture reasoning, grounded in real production behavior.