Blog Folders

 

Introduction

Every July and August, two forces collide in Indian food delivery: the monsoon and the month of Sawan. Rain keeps customers indoors and pushes order volumes up sharply — while Shravan's fasting traditions flip demand toward vegetarian, satvik, and vrat-friendly menus across large parts of North and West India. For restaurants, cloud kitchens, FMCG brands, and the platforms themselves, this six-to-eight-week window is one of the most data-rich periods of the year.

At Actowiz Solutions, we extract real-time data from Zomato, Swiggy, and quick-commerce platforms — menus, prices, delivery times, surge fees, availability, ratings, and promotional banners — across hundreds of Indian cities. This report explains what the monsoon-Sawan window does to food delivery demand, how Zomato and Swiggy respond differently, and how brands can turn scraped platform data into revenue during the surge.

Why Does the Monsoon Reshape Food Delivery Demand?

Rain changes consumer behavior in three predictable ways, all visible in platform data.

Orders move indoors. Dine-out traffic falls during heavy rainfall while delivery orders climb — customers who would have stepped out order in instead. Platforms openly acknowledge this pattern with monsoon-specific campaigns, rain-themed collections ("Baarish Cravings"-style carousels), and comfort-food pushes.

Operations get harder just as demand peaks. Rider availability drops in heavy rain, delivery ETAs stretch, and both Zomato and Swiggy apply rain/surge fees during downpours. This creates the classic monsoon squeeze: peak demand meeting constrained supply — and it is precisely the moment when price, fee, and ETA data becomes most valuable to track.

Cuisine mix shifts. Chai-pakora, samosa, momos, soups, biryani, and hot comfort foods surge; salads and cold beverages dip. Restaurants that reposition menus and imagery for monsoon cravings capture disproportionate search visibility inside the apps.

The Sawan Effect: Fasting Flips the Menu

Layered on top of the rain is Shravan (Sawan) — in 2026 running from mid-July through August in most North Indian calendars. During Sawan, a large customer base shifts to vegetarian and vrat-compliant eating, especially on Mondays (Sawan Somwar). Platform data shows this in several ways:

Veg-only filter usage rises, and "pure veg" restaurants gain ranking visibility

Vrat/fasting menus appear: sabudana khichdi, kuttu items, fruit bowls, falahari thalis

Non-veg categories soften in North and West India, while South and East markets stay comparatively stable — making city-level data essential

Quick-commerce baskets change too: Blinkit, Zepto, and Instamart see fasting staples (sabudana, rock salt, makhana, fruits) spike

For a national restaurant chain or FMCG brand, the strategic question isn't whether Sawan shifts demand — it's by how much, in which pin codes, and at what price points. That is a scraping problem.

Zomato vs Swiggy: What Platform Data Reveals in the Surge Window

Both platforms respond to monsoon-Sawan dynamics, but not identically — and the differences matter for restaurant partners deciding where to spend ad budgets and how to price.

Below is representative sample data illustrating the structure of an Actowiz monsoon comparison deliverable (illustrative sample, not live figures):

Avg Delivery ETA: Zomato 42 min | Swiggy 39 min

Rain / Surge Fee: Zomato ?25 | Swiggy ?20

Temporarily Closed Restaurants: Zomato 9% | Swiggy 11%

Veg-Filter Results Share: Zomato 61% | Swiggy 58%

Monsoon-Themed Banner Campaigns: Zomato 4 | Swiggy 5

Avg Comfort-Food Discount: Zomato 22% | Swiggy 25%

Sample data — illustrative of Actowiz deliverable format. Actual client feeds are pin-code-level, timestamped, and refreshed hourly.

And a sample cuisine demand-shift snapshot (illustrative):

Chai, Pakora & Snacks: Pre-Sawan 100 → Sawan-Monsoon 168 → +68%

Biryani (Veg): Pre-Sawan 100 → Sawan-Monsoon 131 → +31%

Vrat / Falahari Items: Pre-Sawan 100 → Sawan-Monsoon 214 → +114%

Non-Veg Mains (North India): Pre-Sawan 100 → Sawan-Monsoon 74 → −26%

Ice Cream & Cold Beverages: Pre-Sawan 100 → Sawan-Monsoon 81 → −19%

Sample data — illustrative index for format demonstration.

This is the exact dataset shape that lets a cloud kitchen answer: which SKUs to push, where to raise prices, and which cities not to run non-veg promotions in until September.

Five Datasets Worth Scraping During the Monsoon-Sawan Window

Menu & price snapshots. Daily menu extraction across both platforms reveals competitor price moves, new vrat menus, and portion/pack changes — restaurant-level and item-level.

Surge fee & delivery ETA tracking. Rain fees and ETA inflation vary by platform, city, and hour. Tracking them quantifies the real cost customers see — and when demand gets rationed by fees.