Most performance fixes don't last because they target symptoms. We fix the architecture underneath.
Enterprise Next.js with traffic at scale? Performance problems compound fast.These issues probably look familiar.
LCP, CLS, INP are red. Google ranks you lower, organic traffic drops, and marketing spend converts worse. These metrics directly impact rankings and revenue.
Pages take 4+ seconds to load. Users leave before they see your value. Every second slower costs you conversions. That's measurable revenue loss.
Tag managers, analytics, A/B tools, consent banners. A single unoptimized OneTrust banner adds 400KB of blocking JavaScript. Performance cost hidden in your marketing stack.
SSR, SSG, ISR setup is inconsistent. Cache layers work against each other. Pages that should be fast are slow, and you can't figure out why.
Slow pages become unstable releases. Unstable releases become outages during traffic spikes. Every deployment is a risk. Every peak traffic moment is a gamble.
From optimization cycles that never end to architectural fixes that last. Here's what changes when you fix the root causes.
We diagnose with field data, not just Lighthouse scores. Most issues trace back to rendering strategy, caching layers, and third-party scripts. We fix root causes, not symptoms.
We diagnose across the full stack. Find what's actually causing slowness. Fix the architecture underneath.
Stop guessing what's slow. Let's talk about fixing the root causes blocking speed, rankings, and conversions.
Field data first, not just Lighthouse scores. We measure what actual users experience, not only simulated conditions. Field data is almost always worse than lab scores. That gap is where rankings and conversions decay.
SSR, SSG, ISR, PPR matched to each page type. Most teams default to SSR everywhere and watch server costs spike. We configure the right strategy for each page and eliminate hydration overhead where it isn't needed.
LCP, CLS, and INP diagnosed and fixed at the source. INP is the hardest. It requires architectural change, not optimization. CookUnity saw 70% INP improvement after we rebuilt their signup flow.
CDN, ISR, and application-level caches aligned with proper invalidation. One misconfigured cache header is often the difference between a 3-second page and a 300ms page. We configure caching that shields the backend from traffic spikes.
Marketing scripts audited and optimized. We identify which tags block render, configure proper loading strategies, and eliminate the hidden performance tax. The marketing stack runs without hurting Core Web Vitals.
JavaScript bloat reduced, code splitting implemented, non-critical components lazy-loaded. The main thread stays unblocked. Users click and something happens instantly.
Challenge: Legacy React/Redux with spaghetti code throughout. Poor INP — the hardest Core Web Vital to fix. Signup funnel directly tied to revenue. Deployments once a month.
Solution: Migrated signup funnel to Next.js with server-side rendering.
Read the full case study →
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