Study.IQ — EdTech Platform

The Problem

The platform ran on legacy React.js with a Lighthouse Performance score of ~40 and a 9% payment drop-off rate. 30–40 routes needed porting to Next.js App Router with SSR, and the payment layer had no fallback handling for gateway failures.

Approach

1. 01Led the React.js → Next.js migration — porting 30–40 routes, adopting App Router, refactoring to server components, and rebuilding the data-fetching layer for SSR; lifted Lighthouse Performance from ~40 to 75+.
2. 02Integrated Razorpay as the primary payment gateway with Paytm and CCAvenue fallbacks — building webhook handling, retry logic, and failover on the backend — reducing payment drop-off from 9% to 4%.
3. 03Built Continue Purchase Logic and rebuilt PDP, PLP, and Checkout flows end-to-end — the engineering backbone of a conversion initiative that drove a 9x web conversion lift (1.16% → 11.3%).
4. 04Implemented frontend SEO architecture supporting 71% organic traffic growth; redesigned the Homepage and built the Test Series module.

Impact

“Engineering the checkout rebuild as a performance and reliability problem — not just a UI problem — is what unlocked the conversion numbers.”

9x web conversion lift (1.16% → 11.3%), Lighthouse Performance from ~40 to 75+, payment drop-off cut from 9% to 4%, and 71% organic traffic growth — all measured by the product team over the February–October 2025 engagement.