We scraped identical restaurant menus on Swiggy & Zomato across 10 Indian cities. See who charges more, hidden fee gaps & surge patterns — full 2026 data.
TL;DR: Actowiz compared 25,000+ identical menu items from 1,200 restaurants listed on both Swiggy and Zomato across 10 Indian cities. Findings: the same dish is priced differently on the two apps for 38% of items, platform fees and delivery charges — not menu prices — create the biggest checkout gap, and surge patterns differ sharply by city and meal slot.
India's food delivery duopoly means most restaurants list on both apps — but the checkout price a customer sees is rarely identical. Menu markups, packaging charges, delivery fees, platform fees, and surge multipliers all stack differently. We scraped both platforms to quantify exactly where the gap comes from.
| Parameter | Coverage |
|---|---|
| Platforms | Swiggy, Zomato |
| Cities | Delhi NCR, Mumbai, Bengaluru, Hyderabad, Pune, Chennai, Kolkata, Ahmedabad, Jaipur, Lucknow |
| Restaurants matched on both apps | 1,200 |
| Identical menu items compared | 25,000+ |
| Capture windows | Lunch (12–2), evening (6–8), late night (10–12), across 45 days |
| Fields | Item price, packaging charge, delivery fee, platform fee, discounts, ETA, ratings |
Items were matched by restaurant + normalized item name + portion size; mismatches were excluded after validation.
For 38% of matched items, the listed menu price differed between apps — typically by ₹5–20. Patterns we observed:
Menu price tells half the story. On a standardized ₹400 order, the full checkout stack compared as:
| Cost component | Swiggy (avg) | Zomato (avg) |
|---|---|---|
| Delivery fee | ₹XX | ₹XX |
| Platform fee | ₹X | ₹X |
| Packaging | ₹XX | ₹XX |
| Effective checkout gap | — | ±₹XX (X%) |
Key insight: platform fees changed 12 times during our 45-day window — fee experimentation is continuous, and only ongoing monitoring catches it.
We match restaurant identity first, then normalize item names and portion sizes (e.g., "Paneer Butter Masala – Half") before comparison. Ambiguous matches are excluded, so reported gaps come from verified identical items.
Neither is uniformly cheaper. Menu prices are close; the checkout difference is driven by delivery and platform fees, which vary by city, time slot, and ongoing fee experiments. City-level data is the only reliable answer.
Yes — we deliver matched-menu datasets and ongoing monitoring for any city list, restaurant set, or competitor group, with alerts on price and fee changes.
Yes — Instamart, Blinkit (Zomato group), and grocery quick commerce are covered under our quick commerce datasets; see the linked tracker and case study.
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