I started by aligning on scope: Flipkart = India’s leading e-commerce marketplace, spanning electronics, fashion, home, and daily essentials. We’re investigating a 10% drop in order conversion rate over six months, from 30% → 20%, across all devices, platforms, and regions.
Metric sanity: Conversion rate = (Orders placed ÷ Users visiting platform) × 100. No definition or reporting changes, no BI or data pipeline issues. The drop was gradual, pan-India, and affected all user types. So not a data issue or isolated demographic problem.
I ruled out quick externals: no negative PR, no strikes or regulatory shocks, and competitors like Amazon and Meesho were stable. Pricing and discount competitiveness remained unchanged. So this wasn’t a market or macro factor.
Then I walked the funnel to pinpoint where users were churning:
Feed → Listing Page: Stable
Listing → Product Page: Stable
Product Page → Cart: Stable
Cart → Payment: Drop detected
This meant discovery and intent were fine, but conversion was breaking at the cart stage. I explored three hypotheses:
Discount application failure (coupon not working at checkout)
Price mismatch (price changes when GST is added at cart)
Delayed purchase behavior (sale banners prompting users to wait for better deals)
On review, price mismatch emerged as the cause. After a recent GST implementation update, the product page displayed pre-tax prices, but the cart reflected post-tax prices, leading to a visible price jump right before payment. For users, this created a loss of trust and perception of hidden charges, causing abandonment.
RCA (succinct): Conversion ↓ because checkout completion ↓; checkout completion ↓ because users dropped at the cart stage due to visible price mismatch after GST inclusion.
Immediate actions (0–2 weeks):
Display full (tax-inclusive) prices upfront on all product pages and listings.
Add a “Price breakdown” tooltip showing item cost + tax clearly.
Run A/B tests to verify recovery in cart → payment conversion.
Follow-ups (2–8 weeks):
UI consistency audits to ensure parity across listing, PDP, and cart.
Add a persistent price lock message — “Final price includes all taxes” — for transparency.
Benchmark Amazon / Meesho pricing flows to validate clarity and UX parity.
Macro hedge:
Trust messaging campaign highlighting “No Hidden Charges – What You See Is What You Pay.”
Contextual nudges during checkout to explain tax inclusion and prevent perceived “surprise jumps.”
How I’d measure success:
North Star: Cart → Payment conversion rate ↑ back to baseline (20% → 30%).
Leading indicators: Drop-off on cart page ↓, average time spent on cart ↓, successful payment rate ↑.
Quality checks: Customer support tickets tagged “price mismatch” ↓, and refund rate steady.
One-liner summary I’d give in the room:
This wasn’t a demand or pricing competitiveness issue — it was a price transparency bug. Users saw a higher price at checkout because GST wasn’t shown earlier, breaking trust and killing conversion. Fix visibility, align pricing across all stages, and reinforce user confidence through upfront clarity.