GET STARTED

You'll receive the case study on your business email shortly after submitting the form.

Home Blog

What Are the Top Fasting Foods Identified by State-Wise Navratri Food Map Data Scraping?

How to Scrape Cloud Kitchen Data from Zomato & Swiggy-01

What Are the Top Fasting Foods Identified by State-Wise Navratri Food Map Data Scraping?

Introduction

As India prepares for Navratri 2025, the excitement is building not only in temples and homes but also in kitchens across states. Each region is gearing up with its own festive delicacies—whether it’s the energy-packed sabudana khichdi of Maharashtra, the crispy kuttu puris of Uttar Pradesh, or the refreshing singhara halwa of Bengal. Food Data Scrape has analyzed last year’s consumption patterns and upcoming seasonal indicators to bring a predictive outlook on regional Navratri food trends.

While celebrations vary widely—from Gujarat’s colorful garba nights to Bengal’s grand Durga Puja feasts—the fasting preferences during Navratri hold a unifying thread. Every state adapts its own culinary style, balancing tradition with modern innovations. This diversity makes State-Wise Navratri Food Map Data Scraping essential for businesses, allowing them to map demand shifts, ingredient popularity, and pricing changes across regions. By capturing such insights, restaurants and delivery platforms can prepare customized offerings that resonate with local tastes.

This blog provides a data-driven view of Navratri fasting food preferences, supported by scraping insights from menus, online delivery platforms, and regional vendors. Since Navratri is still a few weeks away, all the insights shared here are predictions based on last year’s scraping data and historical trends. By analyzing these trends early, businesses can gain a competitive edge, ensuring they are ready with the right meals, the right prices, and the right promotions as soon as the festival begins.

Regional Navratri Food Preferences

Regional Navratri Food Preferences

Different states celebrate the festival with distinct flavors. Scraping restaurant menus and online ordering data highlights fascinating state-level differences. For example, Uttar Pradesh shows high demand for kuttu atta puris and aloo sabzi, while Maharashtra leans toward sabudana khichdi and thalipeeth. Gujarat, meanwhile, balances fasting with festive snacks like farali chevdo.

These regional Navratri food trends datasets are crucial for restaurants, cloud kitchens, and FMCG companies preparing seasonal offerings. By mapping state-wise Navratri food preferences extraction, businesses can predict demand more accurately.

Why Food Data Scrape Tracks Navratri Trends

Food Data Scrape specializes in food delivery data scraping services, offering businesses competitive intelligence on meal pricing, menu availability, and regional choices. Navratri, being one of India’s biggest food-centric festivals, is an excellent case for studying seasonal demand shifts. By analyzing restaurant menu data scraping outputs, our team builds an intelligence layer that guides food-tech startups, restaurants, and packaged food brands.

For example:

  • Scraping Swiggy and Zomato during Navratri shows sharp increases in “fasting meal” listings.
  • Supermarket data reveals packaged sabudana and singhara flour sales spike in urban clusters.
  • Vendor insights confirm rising adoption of millet-based fasting snacks.

Sample Data Table: Predicted Navratri Fasting Food Preferences (State-Wise)

State Popular Fasting Dish Ingredient Trend Predicted Demand % Source (Scraped/Analyzed)
Uttar Pradesh Kuttu Poori & Aloo Sabzi Buckwheat Flour 35% increase Menu scraping + past sales
Maharashtra Sabudana Khichdi Sago Pearls, Peanuts 28% increase Restaurant menu analysis
Gujarat Farali Chevdo Potato & Peanuts Mix 22% increase Snack vendor data scrape
West Bengal Singhara Flour Halwa Water Chestnut Flour 18% increase Retailer scraping
Delhi NCR Samak Rice Khichdi Barnyard Millet 25% increase Delivery platform scrape

Note: Data is predictive, based on last year’s scraped insights and ongoing analysis.

Navratri Fasting Food Preferences Scraper

To understand how consumer demand shifts, Food Data Scrape deploys a Navratri fasting food preferences scraper. This automated system extracts menu-level data from delivery platforms, filters fasting categories, and maps them against state demand clusters.

For instance, in 2024, the scraper revealed that over 40% of listed Navratri meals in Delhi were based on samak rice variations. In contrast, Gujarat had more fried snack options, while Maharashtra leaned heavily toward sabudana recipes. This year, early indicators suggest an even higher diversity in millet-based fasting meals. Businesses that Scrape Popular Navratri Fasting Foods Data can identify such evolving preferences in advance, ensuring that they stock the right ingredients and design menus that appeal to regional consumer demands.

Regional Navratri Meal Data Scraper

Scraping data across India provides regional Navratri meal data, which is then categorized by states, ingredients, and preparation style. The findings are valuable not only for restaurants but also for packaged food companies aiming to introduce fasting-friendly SKUs.

For example:

  • Urban metros show rising demand for ready-to-eat fasting thalis.
  • Semi-urban areas continue preferring traditional homemade recipes, but order raw ingredients online.
  • Younger consumers lean toward fusion meals like sabudana pizza bites or paneer tikki with singhara flour.

Table: Predicted Ingredient Demand During Navratri 2025

Ingredient State with Highest Demand % Rise Expected Common Dish Example
Sabudana (Sago) Maharashtra +30% Sabudana Khichdi
Kuttu Atta Uttar Pradesh +35% Kuttu Poori
Singhara Flour West Bengal +20% Singhara Halwa
Samak Rice Delhi NCR +25% Samak Rice Khichdi
Peanuts Gujarat +18% Farali Chevdo

Predicted based on scraped retail and delivery data from 2024 trends.

The Value of Scraping Regional Navratri Food Trends

Navratri is not just about religious fasting; it is a massive seasonal food market. For delivery platforms, the challenge lies in curating fasting menus at scale. For FMCG companies, predicting which ingredients will trend is essential for stocking and supply chain planning.

By using scrape regional Navratri food trends tools, Food Data Scrape ensures that clients receive actionable intelligence—ranging from price points to packaging insights. This reduces wastage, improves targeting, and ultimately boosts sales.

Restaurant Data Intelligence Services for Navratri

During Navratri, restaurants experiment with limited-time offerings (LTOs). A thali priced at ₹199 in Delhi may perform very differently compared to the same thali in Mumbai. Through restaurant data intelligence services, Food Data Scrape provides analytics on:

  • Competitive menu pricing
  • Regional preference mapping
  • Seasonal trend forecasting

Restaurants can then adjust menu sizes, pricing, and portion design before Navratri begins.

How Food Delivery Intelligence Services Enhance Navratri Planning

Seasonal food demand fluctuates rapidly, and Navratri is one of the most important testing grounds for delivery platforms and restaurants. By applying food delivery intelligence services, businesses gain a deeper understanding of menu trends, pricing sensitivity, and customer choices.

For example, scraped data from last year showed that while Delhi customers ordered fasting thalis priced between ₹150–₹250, Mumbai buyers leaned toward premium combos worth ₹350 and above. This distinction is critical for setting the right menu strategies.

Food Data Scrape enables brands to anticipate these differences weeks in advance, giving them the flexibility to stock ingredients, design promotional campaigns, and collaborate with local vendors.

Restaurant Menu Data Scraping for Navratri Specials

Each Navratri season, restaurants introduce fasting-friendly menus. By running restaurant menu data scraping, we capture dish names, ingredients, prices, and even customer reviews. This structured dataset reveals which items gain traction and which ones fail to perform.

In 2024, scraped datasets highlighted three fast-selling categories:

  • Budget Thalis – Simple kuttu puri–aloo sabzi combos.
  • Protein-Rich Meals – Paneer tikki, peanut chaat, and yogurt-based snacks.
  • Fusion Fasting Items – Sabudana pizza bites and smoothie bowls.

With this year’s prediction, Food Data Scrape expects a sharp rise in millet-based options as awareness about healthier fasting choices grows.

Food Delivery Scraping API Services

While manual research can take weeks, Food Data Scrape offers food delivery scraping API services that automate the collection of real-time food delivery data. These APIs pull structured information directly from food delivery apps like Swiggy and Zomato.

During Navratri, this becomes especially valuable because menu listings change daily. Using the API, a restaurant chain can instantly monitor competitors’ fasting menu prices or check which dishes are trending in different states.

Businesses integrating these services get:

  • Real-time monitoring of fasting dishes and combos.
  • Instant alerts on competitor price changes.
  • State-level breakdowns for smarter stocking and marketing.

Regional Navratri Food Trends Dataset

After scraping and structuring, the data is packaged into a regional Navratri food trends dataset. This dataset becomes a reference guide for brands preparing their seasonal campaigns. It typically includes:

  • State-wise fasting food preferences
  • Popular ingredients and substitutes
  • Average price points for dishes
  • Predicted growth in demand clusters

For instance, the dataset for 2025 shows:

  • Uttar Pradesh & Bihar – Strong demand for buckwheat and potato-based meals.
  • Maharashtra & Madhya Pradesh – Sabudana remains dominant, but packaged khichdi kits are gaining traction.
  • Delhi NCR – Millet-based and premium thali combos are in higher demand.

Sample Table: Predicted Navratri Meal Pricing Trends (2025)

State/Region Avg. Thali Price (₹) Predicted Popular Dish Consumer Segment Focus
Delhi NCR 220 – 280 Samak Khichdi Combo Young Professionals
Maharashtra 280 – 350 Sabudana Khichdi Thali Families & Students
Uttar Pradesh 150 – 220 Kuttu Poori Set Traditional Households
Gujarat 180 – 250 Farali Chevdo Pack Snack-Lovers & Travelers
Karnataka 240 – 300 Millet Paneer Meals Health-Conscious Buyers

These numbers are predictive, based on last year’s scraped food delivery datasets and regional price mapping.

Food Price Dashboard for Navratri

One of the most practical tools built by Food Data Scrape is the food price dashboard. This interactive dashboard visualizes state-wise food prices, ingredient costs, and dish-level menu comparisons.

For Navratri, the dashboard can show:

  • How sabudana thali prices differ in Delhi vs. Mumbai.
  • Which packaged flour prices are spiking on e-commerce platforms.
  • The gap between retail ingredient prices and delivery menu pricing.

This empowers restaurants, cloud kitchens, and even food-tech investors to make smarter decisions during festive seasons.

Food Delivery Datasets for Seasonal Strategy

A robust food delivery dataset allows businesses to back predictions with facts. Food Data Scrape compiles data not only from delivery platforms but also from grocery marketplaces, supermarket listings, and online recipe portals.

For Navratri 2025, datasets include:

  • Meal availability across top 10 states.
  • Ingredient-level sales predictions (sabudana, kuttu, singhara).
  • Price ranges by consumer segment (budget, mid-range, premium).

Such granular information enables a state-wise Navratri food preferences extraction strategy, ensuring restaurants and FMCG brands can target their marketing campaigns effectively.

Restaurant Data Intelligence Services in Action

Let’s take a real-world example:A mid-sized restaurant chain in Pune wants to launch Navratri fasting thalis. Using restaurant data intelligence services, they can:

  • Scrape competitor menus in Maharashtra.
  • Identify which dishes are priced successfully.
  • Align ingredient sourcing with predicted high-demand items.
  • Test variations before scaling across branches.

This data-driven approach reduces risk, saves costs, and increases the likelihood of success during the competitive festive window.

Conclusion: Powering Navratri Insights with Food Data Scrape

Navratri is more than a cultural festival—it is a data-rich seasonal food economy. Each state brings its own flavors, but the opportunity for businesses lies in predicting these trends before they happen.

Food Data Scrape, with its specialized tools like the Navratri fasting food preferences scraper, food delivery scraping API services, food price dashboard, and regional datasets, equips businesses to act on these insights.

Whether you’re a delivery platform optimizing listings, a restaurant designing thalis, or an FMCG brand launching fasting-friendly products, leveraging food delivery intelligence services ensures you stay ahead of the curve.

By blending cultural tradition with modern scraping technology, Food Data Scrape helps businesses unlock growth opportunities this Navratri—backed by data, not guesswork.

If you are seeking for a reliable data scraping services, Food Data Scrape is at your service. We hold prominence in Food Data Aggregator and Mobile Restaurant App Scraping with impeccable data analysis for strategic decision-making.

GeoIp2\Model\City Object
(
    [continent] => GeoIp2\Record\Continent Object
        (
            [name] => North America
            [names] => Array
                (
                    [de] => Nordamerika
                    [en] => North America
                    [es] => Norteamérica
                    [fr] => Amérique du Nord
                    [ja] => 北アメリカ
                    [pt-BR] => América do Norte
                    [ru] => Северная Америка
                    [zh-CN] => 北美洲
                )

            [code] => NA
            [geonameId] => 6255149
        )

    [country] => GeoIp2\Record\Country Object
        (
            [name] => United States
            [names] => Array
                (
                    [de] => USA
                    [en] => United States
                    [es] => Estados Unidos
                    [fr] => États Unis
                    [ja] => アメリカ
                    [pt-BR] => EUA
                    [ru] => США
                    [zh-CN] => 美国
                )

            [confidence] => 
            [geonameId] => 6252001
            [isInEuropeanUnion] => 
            [isoCode] => US
        )

    [maxmind] => GeoIp2\Record\MaxMind Object
        (
            [queriesRemaining] => 
        )

    [registeredCountry] => GeoIp2\Record\Country Object
        (
            [name] => United States
            [names] => Array
                (
                    [de] => USA
                    [en] => United States
                    [es] => Estados Unidos
                    [fr] => États Unis
                    [ja] => アメリカ
                    [pt-BR] => EUA
                    [ru] => США
                    [zh-CN] => 美国
                )

            [confidence] => 
            [geonameId] => 6252001
            [isInEuropeanUnion] => 
            [isoCode] => US
        )

    [representedCountry] => GeoIp2\Record\RepresentedCountry Object
        (
            [name] => 
            [names] => Array
                (
                )

            [confidence] => 
            [geonameId] => 
            [isInEuropeanUnion] => 
            [isoCode] => 
            [type] => 
        )

    [traits] => GeoIp2\Record\Traits Object
        (
            [autonomousSystemNumber] => 
            [autonomousSystemOrganization] => 
            [connectionType] => 
            [domain] => 
            [ipAddress] => 216.73.216.33
            [isAnonymous] => 
            [isAnonymousVpn] => 
            [isAnycast] => 
            [isHostingProvider] => 
            [isLegitimateProxy] => 
            [isPublicProxy] => 
            [isResidentialProxy] => 
            [isTorExitNode] => 
            [isp] => 
            [mobileCountryCode] => 
            [mobileNetworkCode] => 
            [network] => 216.73.216.0/22
            [organization] => 
            [staticIpScore] => 
            [userCount] => 
            [userType] => 
        )

    [city] => GeoIp2\Record\City Object
        (
            [name] => Columbus
            [names] => Array
                (
                    [de] => Columbus
                    [en] => Columbus
                    [es] => Columbus
                    [fr] => Columbus
                    [ja] => コロンバス
                    [pt-BR] => Columbus
                    [ru] => Колумбус
                    [zh-CN] => 哥伦布
                )

            [confidence] => 
            [geonameId] => 4509177
        )

    [location] => GeoIp2\Record\Location Object
        (
            [averageIncome] => 
            [accuracyRadius] => 20
            [latitude] => 39.9625
            [longitude] => -83.0061
            [metroCode] => 535
            [populationDensity] => 
            [timeZone] => America/New_York
        )

    [mostSpecificSubdivision] => GeoIp2\Record\Subdivision Object
        (
            [name] => Ohio
            [names] => Array
                (
                    [de] => Ohio
                    [en] => Ohio
                    [es] => Ohio
                    [fr] => Ohio
                    [ja] => オハイオ州
                    [pt-BR] => Ohio
                    [ru] => Огайо
                    [zh-CN] => 俄亥俄州
                )

            [confidence] => 
            [geonameId] => 5165418
            [isoCode] => OH
        )

    [postal] => GeoIp2\Record\Postal Object
        (
            [code] => 43215
            [confidence] => 
        )

    [subdivisions] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [name] => Ohio
                    [names] => Array
                        (
                            [de] => Ohio
                            [en] => Ohio
                            [es] => Ohio
                            [fr] => Ohio
                            [ja] => オハイオ州
                            [pt-BR] => Ohio
                            [ru] => Огайо
                            [zh-CN] => 俄亥俄州
                        )

                    [confidence] => 
                    [geonameId] => 5165418
                    [isoCode] => OH
                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

Get in touch

We will Catch You as early as we recevie the massage

Trusted by Experts in the Food, Grocery, and Liquor Industry
assets/img/clients/deliveroo-logo.png
assets/img/top-food-items-inner/logos/Instacart_logo_and_wordmark.svg
assets/img/top-food-items-inner/logos/total_wine.svg
assets/img/clients/i-food-logo-02.png
assets/img/top-food-items-inner/logos/Zepto_Logo.svg
assets/img/top-food-items-inner/logos/saucey-seeklogo.svg
+1