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XYNEXIA — Our Own Growth System

How XYNEXIA engineered its own website as a growth system: Next.js architecture, performance, accessibility, SEO structure, lead pipeline, attribution and analytics — with the lessons and gaps stated plainly.

Client
XYNEXIA (first-party)
Sector
AI Growth / digital services
Published

The challenge

A new company needs to be found, understood and trusted by businesses searching for growth help — with no existing audience, no client logos to show yet and a requirement that every enquiry be traceable to its source.

The objective

Build a site that loads fast on mobile, is accessible, is structured for search, captures enquiries safely and records where each one came from — and treat that as the proof of how we work.

Strategy

Treat the website as the first component of the growth system: one canonical page per search intent, server-rendered content, a lead pipeline with attribution, and automated checks so quality cannot quietly regress.

Architecture

  • Next.js App Router with statically generated pages; essential content exists in the rendered HTML, not behind client-side fetches.
  • Content as typed data (services, solutions, insights, case studies) so pages, sitemap and checks derive from one source.
  • One centralised metadata helper producing a unique title, description, canonical URL and Open Graph tags per page.
  • Structured data: Organization, WebSite, BreadcrumbList, Article and Service — Service only for offerings sold today.
  • A content security policy limiting scripts and connections to the site’s own origin.

Design

A dark, high-contrast visual system built around a single hero image of Earth at the horizon and a restrained cyan accent. Motion respects reduced-motion preferences, and the hero image is the only above-the-fold asset worth optimising for LCP.

Implementation

  • Lead form handled by a server action: origin check, honeypot, minimum fill time and per-IP rate limiting before validation.
  • Leads delivered by webhook and email, each carrying source, medium, campaign, click ID, referrer and landing page.
  • First-touch and last-touch attribution captured in the browser and sent with the enquiry.
  • Automated end-to-end tests on desktop and mobile: metadata, canonicals, JSON-LD shape, sitemap, robots, accessibility (WCAG 2.2 AA via axe), no-JavaScript rendering and the lead flow.

Technology

  • Next.js 16
  • React 19
  • Tailwind CSS 4
  • TypeScript
  • Playwright
  • axe-core
  • Vercel

Analytics and measurement

Interaction events are pushed to a data layer with personal-data keys stripped. No third-party analytics provider is installed yet; choosing one and extending the content security policy is an open item, not a finished feature.

Outcome

The site ships with unique metadata, absolute canonicals, a single H1 per page, a sitemap and robots file, structured data and automated accessibility checks — and a lead pipeline that stores the source of each enquiry.

Verified results

Largest Contentful Paint, desktop (median)
0.43 s
Source: Measured with Playwright against the production build; recorded in docs/xynexia-site-audit.md §11
Largest Contentful Paint, mobile throttled (median)
2.46 s
Source: Measured with Playwright against the production build; recorded in docs/xynexia-site-audit.md §11

What we learned

  • Decide the measurement design before launch: retrofitting attribution is harder than building it in.
  • A performance budget only works if it’s written down and re-tested after every change.
  • Future products should never share the markup of things you sell today; the first version of our structured data got this wrong and we corrected it.
  • Proof takes time. We have no client results to show for this site yet, so we show how it was built and what it measures.

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