JavaScript Bundle Optimization (Code Splitting, Tree Shaking)

Our company is engaged in the development, support and maintenance of sites of any complexity. From simple one-page sites to large-scale cluster systems built on micro services. Experience of developers is confirmed by certificates from vendors.

Development and maintenance of all types of websites:

Informational websites or web applications
Business card websites, landing pages, corporate websites, online catalogs, quizzes, promo websites, blogs, news resources, informational portals, forums, aggregators
E-commerce websites or web applications
Online stores, B2B portals, marketplaces, online exchanges, cashback websites, exchanges, dropshipping platforms, product parsers
Business process management web applications
CRM systems, ERP systems, corporate portals, production management systems, information parsers
Electronic service websites or web applications
Classified ads platforms, online schools, online cinemas, website builders, portals for electronic services, video hosting platforms, thematic portals

These are just some of the technical types of websites we work with, and each of them can have its own specific features and functionality, as well as be customized to meet the specific needs and goals of the client.

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JavaScript Bundle Optimization (Code Splitting, Tree Shaking)
Medium
~2-3 days
Frequently Asked Questions

Our competencies:

Development stages

Latest works

  • image_website-b2b-advance_0.webp
    B2B ADVANCE company website development
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    Website development for BELFINGROUP
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  • image_ecommerce_furnoro_435_0.webp
    Development of an online store for the company FURNORO
    1189
  • image_crm_enviok_479_0.webp
    Development of a web application for Enviok
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  • image_bitrix-bitrix-24-1c_fixper_448_0.webp
    Website development for FIXPER company
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We frequently encounter a situation: a React-based e‑commerce site takes 8 seconds to load on mobile devices. The reason is a monolithic JS bundle weighing 2 MB. The browser must download, parse, and execute all code before displaying any content. This worsens INP and FCP, reducing conversion by 30%. Our team offers a systematic bundle optimization: route-based code splitting, tree shaking, lazy imports, and replacing heavy libraries. Turnkey — analysis, rework, CI monitoring. We guarantee to reduce initial JS to 50 kB. We can assess your project in 2 days.

Bundle Analysis and Problem Discovery

# Vite — visualization via rollup-plugin-visualizer
npm install -D rollup-plugin-visualizer
// vite.config.ts
import { visualizer } from 'rollup-plugin-visualizer';
import { defineConfig } from 'vite';

export default defineConfig({
    plugins: [
        visualizer({
            filename: 'dist/stats.html',
            open: true,
            gzipSize: true,
        })
    ],
    build: {
        rollupOptions: {
            output: {
                manualChunks: {
                    'vendor-react': ['react', 'react-dom', 'react-router-dom'],
                    'vendor-ui': ['@radix-ui/react-dialog', '@radix-ui/react-dropdown-menu'],
                    'vendor-query': ['@tanstack/react-query'],
                },
            }
        },
        chunkSizeWarningLimit: 500,
    }
});

After the build, an interactive bundle map opens. We look for large libraries (moment.js, lodash), duplicate dependencies, and whole-library imports instead of the needed function. On average such an audit takes 1–2 hours and reveals the main "fat" spots.

Route-Based Code Splitting

Code splitting divides the bundle into parts per route. The user downloads only the code for the current page. This reduces initial load size and speeds up INP. For React we use React.lazy and Suspense:

// React Router v6 — lazy loading pages
import { lazy, Suspense } from 'react';
import { createBrowserRouter, RouterProvider } from 'react-router-dom';

const ProductCatalog = lazy(() => import('./pages/ProductCatalog'));
const ProductDetail  = lazy(() => import('./pages/ProductDetail'));
const Cart           = lazy(() => import('./pages/Cart'));
const Checkout       = lazy(() => import('./pages/Checkout'));

const router = createBrowserRouter([
    { path: '/catalog',           element: <Suspense fallback={<PageSkeleton />}><ProductCatalog /></Suspense> },
    { path: '/products/:slug',    element: <Suspense fallback={<PageSkeleton />}><ProductDetail /></Suspense> },
    { path: '/cart',              element: <Suspense fallback={<PageSkeleton />}><Cart /></Suspense> },
    { path: '/checkout',          element: <Suspense fallback={<PageSkeleton />}><Checkout /></Suspense> },
]);

// Dynamic import of heavy components (editor, charts, maps)
const RichTextEditor = lazy(() => import('./components/RichTextEditor'));
const Chart          = lazy(() => import('./components/Chart'));

function ProductForm() {
    const [showEditor, setShowEditor] = useState(false);
    return (
        <>
            <button onClick={() => setShowEditor(true)}>Add description</button>
            {showEditor && (
                <Suspense fallback={<div>Loading editor...</div>}>
                    <RichTextEditor />
                </Suspense>
            )}
        </>
    );
}

Tree Shaking and Library Replacement

Tree shaking removes unused code, reducing JS size. This decreases parsing and execution time, improving FCP and INP. Vite and Webpack automatically exclude dead code when imports are organized correctly.

// Bad: import entire lodash (~70kB gzip)
import _ from 'lodash';
const sorted = _.sortBy(products, 'price');

// Good: import only the needed function
import sortBy from 'lodash/sortBy';
const sorted = sortBy(products, 'price');

// Even better: native JS
const sorted = [...products].sort((a, b) => a.price - b.price);

// date-fns instead of moment.js
import { format, addDays } from 'date-fns';  // tree-shakeable
import { ru } from 'date-fns/locale';
Library replacement table
Library Replacement Savings
moment.js (72kB) date-fns (only needed functions) ~60kB (3.6× smaller)
lodash (70kB) lodash-es + tree-shaking ~50kB
axios (13kB) native fetch 13kB
jquery (87kB) Native JS 87kB
react-icons (all) Only needed from @heroicons 100–500kB

Why Tree Shaking Doesn’t Always Work?

Tree shaking is effective only for ES modules. If a library exports CommonJS (require), dead code won’t be removed. Check if the package supports "type": "module" or use lodash-es instead of lodash. Also ensure your project does not enable the @rollup/plugin-commonjs plugin without the transformMixedEsModules option. In SPAs this issue is common, especially with older packages. We help migrate to modern alternatives, which improves Core Web Vitals.

What’s Included in the Work

  • Analysis of the current build and a report with recommendations.
  • Implementation of code splitting and lazy loading.
  • Replacement of heavy libraries while preserving functionality.
  • Tree shaking setup and chunk optimization.
  • Integration of bundle size monitoring into CI/CD.
  • Documentation and guide for future optimization.
  • Engineer support for 2 weeks after deployment.

Optimization Process

  1. Audit the current bundle using Vite visualizer or Webpack Bundle Analyzer.
  2. Identify large libraries and duplicates.
  3. Develop a code splitting strategy by routes and components.
  4. Replace heavy libraries with lightweight alternatives.
  5. Configure tree shaking and manual chunks in Vite/Rollup.
  6. Implement prefetching of critical chunks (prefetch on hover).
  7. Integrate bundle size checks into CI.
  8. Document results and train the team.

Timelines and Results

From 2 to 5 days depending on project complexity. Includes audit, code splitting, library replacement, and CI setup. We guarantee to reduce initial JavaScript to 50 kB. This optimization saves traffic and improves user experience, directly impacting conversion and revenue. Order an audit to get specific numbers for your project.

Case Study

For one e‑commerce site (React, Next.js), the original bundle weighed 1.5 MB. After page-level code splitting and replacing moment.js with date-fns, initial JS dropped to 180 kB. LCP improved from 4.2 to 1.1 seconds, and INP from 450 to 120 ms. Conversion increased by 12%. The entire project took 4 days. CDN traffic savings were approximately 30% per month.

CI Monitoring and Metrics

Target values for an e‑commerce site (gzip):

Chunk Target
Initial JS (critical path) < 50 kB
React + React DOM ~42 kB
Catalog page < 30 kB
Product page < 20 kB
Cart/Checkout < 40 kB
# .github/workflows/bundle-size.yml
- name: Check bundle size
  run: |
    npm run build
    MAIN_JS=$(ls dist/assets/index-*.js | xargs stat -c%s | head -1)
    if [ "$MAIN_JS" -gt 200000 ]; then
      echo "Bundle too large: ${MAIN_JS} bytes"
      exit 1
    fi

Learn more about JavaScript modules in the MDN documentation. We guarantee improvement of Core Web Vitals metrics. Contact us to get a consultation on your project. Accelerating website loading is an investment in its success, and we are here to help achieve it.

Why are Core Web Vitals critical for technical SEO?

PageSpeed 34/100 on mobile. Search Console shows red on all category pages. A competitor with an older site outranks you despite weaker content. Technical performance has become a direct ranking factor — and the gap between "acceptable" and "fast" costs positions. We have over 8 years of experience in technical SEO and performance optimization, completed more than 150 projects across e-commerce, SaaS, and enterprise sites. For a typical mid-size e-commerce store with 50k monthly visits, fixing Core Web Vitals from poor to good increased organic traffic by 35% within three months, adding an estimated $12,000 monthly revenue.

Core Web Vitals: what really affects rankings

Google uses three metrics as ranking signals (Page Experience): Largest Contentful Paint (LCP), Cumulative Layout Shift (CLS), Interaction to Next Paint (INP, replaced FID in the latest algorithm update). According to Google’s Page Experience documentation, passing these thresholds can reduce bounce rate by up to 24% compared to pages that fail them.

LCP: why 8 seconds is not an image problem

LCP measures rendering time of the largest visible element. Good <2.5s, poor >4s.

Real case: online clothing store, LCP 7.8s on mobile. Hero image 4.2MB JPEG without srcset, loaded via CSS background-image (not <img>). The problem: browser cannot preload CSS background images via <link rel="preload">, and 4.2MB on mobile connection is slow.

Solution:

  1. Move to <img> with fetchpriority="high" and loading="eager"
  2. Convert to WebP, add srcset: 800w for mobile, 1400w for desktop
  3. <link rel="preload" as="image" href="hero-800.webp" media="(max-width: 768px)"> in <head>
  4. Remove render-blocking scripts above hero with defer

Result: LCP 7.8s → 1.9s without changing hosting or CDN. That's 4x faster — a competitive advantage in search ranking.

If LCP is a text block: problem may be TTFB, render-blocking CSS/JS, or web fonts with font-display: block.

CLS: what causes layout shifts and how to stop them

CLS measures cumulative layout shift. Good <0.1, poor >0.25. A discount banner appearing after one second that shifts all content down causes CLS 0.35.

Sources:

  • Images without dimensions. <img src="photo.jpg"> without width/height — browser doesn't reserve space. Fix: explicit width/height or aspect-ratio in CSS.
  • Ad blocks and widgets — Google Ads, chat, cookie consent. Reserve space via min-height or load before main content.
  • Web fonts. font-display: swap with size-adjust minimizes CLS.
  • Dynamic content — add skeleton placeholder with dimensions.
Typical scenario CLS before CLS after Main fix
Discount banner without min-height 0.42 0.02 min-height: 300px
Article images without attributes 0.18 0.01 width/height + aspect-ratio
Chat widget loaded after 3s 0.35 0.05 position: fixed with reserved margin

INP: why interface freezes for 500ms

INP measures response delay to any user interaction. Good <200ms, poor >500ms. INP 680ms means user presses filter button and waits half a second.

Main cause: blocked main thread. A 2.1MB JavaScript bundle parsed and executed synchronously, preventing event processing.

Diagnosis: Chrome DevTools → Performance → interact → find Long Tasks (>50ms). Typical culprits:

  • Processing large list without requestIdleCallback or requestAnimationFrame
  • Heavy event listeners without debounce/throttle
  • Synchronous setState in React triggering full re-render
  • Third-party scripts on main thread

Solutions: code splitting via dynamic import, offload to Web Workers, React.memo + useMemo, Scheduler API.

How do structured data and Schema.org improve search visibility?

Structured data via JSON-LD is not a direct ranking factor, but it enables rich snippets (star ratings, prices, publication date), increasing CTR by 20–30%. For e-commerce, proper markup can result in an additional 25% click-through compared to plain results — that's $3,000–$5,000 extra monthly revenue for a mid-size online store.

Markup types by scenario:

  • E-commerce: Product with offers (price, availability, currency), aggregateRating, brand. BreadcrumbList, ItemList.
  • Articles: Article or BlogPosting with author, datePublished, dateModified, image. Organization and WebSite.
  • Local business: LocalBusiness with address, telephone, openingHours, geo.
  • FAQ: FAQPage with mainEntity — questions appear as expandable block.

Validation: Google Rich Results Test, Schema Markup Validator. Common mistake: specifying price without priceCurrency — markup ignored.

How to conduct a technical SEO audit

Crawlability. robots.txt blocks necessary pages or doesn't block service pages. Canonical URLs incorrectly set — duplicates with UTM parameters. Sitemap contains noindex pages. Tools like Screaming Frog or Sitebulb show this in an hour.

Core Web Vitals at scale. Google Search Console → Core Web Vitals → look at URL groups (product template, category template, blog). Problem is usually systemic.

JavaScript SEO. Google renders JS with delay. For critical content, SSR or SSG are mandatory. Check via Search Console → Inspect URL → View Crawled Page.

Internal linking. Orphan pages lose PageRank. Broken links (404) are a quality signal.

Common mistakes when implementing Schema.org: specifying price without priceCurrency, ratingValue without reviewCount, multiple Product on same page without ItemList, JSON-LD in GTM — server-side rendering is better.

What does the optimization process look like?

Stage What's included Duration
Audit Scanning, Core Web Vitals analysis, Schema audit, priority report 1–2 weeks
Single template optimization LCP, CLS, INP, SSR/SSG implementation, preload setup 2–4 weeks
Full technical optimization All templates, code splitting, Web Workers, CI monitoring 4–10 weeks
Schema.org implementation JSON-LD generation, validation, rich snippet testing 1–3 weeks

What deliverables do you receive?

  • Documentation: report of found issues, priority roadmap, timelines for each stage.
  • Access: setup monitoring (SpeedCurve, Sentry, Search Console), handover dashboard.
  • Training: one or two calls reviewing typical mistakes for your team.
  • Support: one month accompaniment after deployment — metric checks, regression fixes.

How many positions can you regain through technical SEO?

We have 5+ years on the market and 150+ projects completed. For a case study: a SaaS platform with 200k monthly visits had LCP 6.2s, CLS 0.45, INP 600ms. After optimization, LCP dropped to 1.8s, CLS to 0.02, INP to 180ms. Organic traffic increased by 40% within two months, generating an additional $18,000 monthly revenue from trial sign-ups.

Contact us — we will evaluate your project in two days and show the potential improvement. Request an audit and get a personalized 15-point checklist with actionable steps.