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E-commerce Case study

Built for the day everyone shows up at once.

BluePeak's best days were their worst days. Every gear drop brought a wave of buyers, and took the store down with it. This is the story of rebuilding a storefront around its own busiest hour.

BluePeak Outdoors Outdoor gear retailer · Boulder

BluePeak Outdoors — project cover
Timeframe
9 weeks, audit to first drop
Role
Architecture, storefront build, load testing, launch support
Scope
  • Storefront rebuild
  • Drop-day infrastructure
  • Algolia spec-aware search
  • Stripe checkout
Stack
  • Next.js
  • Stripe
  • Algolia

The brief

Their best marketing kept crashing their own store.

BluePeak had built a genuine following around limited gear drops: new packs, new shells, gone in a weekend. The marketing worked almost too well. The old store, a monolith on a single overworked server, would slow to a crawl within minutes of a drop email and fall over at the peak. Support spent launch mornings apologising.

There was a quieter problem underneath. Serious buyers choose gear by the numbers (weights, denier, temperature ratings), and all of that lived in manufacturer PDFs. Shoppers left the site to research, and plenty never came back.

The build

Static where it can be, dynamic only where it must be.

The architecture followed one principle: a product page under drop-day load should cost the server nothing. Every page is statically generated and served from a CDN edge, so ten thousand simultaneous visitors read cached files, not a struggling database. Only the things that genuinely change (stock, cart, checkout) hit live services, each isolated so a spike in one can't drown the others.

The PDF problem became a data problem. We turned every spec sheet into structured data, and wired Algolia to understand it: shoppers can now filter jackets by warmth-to-weight, or search "sub-2lb 2-person tent" and get exactly that. The specs stopped being homework and became the shopping experience.

Before the first real drop we rehearsed with load tests at five times the worst historical traffic, then sat on the launch call with the BluePeak team, watching dashboards stay green while the biggest drop of the year sold through.

“First drop in two years where I watched sales instead of server graphs.”
Head of e-commerce, BluePeak Outdoors

The result

The drop that finally stayed up, and sold double.

The first launch on the new store did twice the sales of any previous drop, with zero downtime and checkout latency flat through the peak. The team's launch-morning ritual changed from watching error logs to watching the sales counter.

The spec-aware search turned out to be more than a defensive fix: filter-driven sessions convert at nearly twice the store average, because the people using them arrive at exactly the gear they meant to find.

What the work moved

sales on first drop, zero downtime
worst-case traffic, rehearsed before launch
~2×
conversion on spec-filtered sessions

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