Actowiz Metrics Real-time
logo
analytics dashboard for brands! Try Free Demo
Navratri Mega Sale Price Tracking

Executive Summary

The frozen foods category in India has exploded, driven by changing lifestyles, QSR-style snacking at home and the rise of modern retail and quick-commerce platforms. Brands like McCain, ITC Master Chef, Hyfun, and Yummiez lead the category with products like fries, nuggets, burger patties, momos and ready-to-cook snacks.

Retailers and distributors needed clear visibility into price differences, pack-size variance, availability, discount cycles, and platform-level competitiveness across major grocery and B2B platforms.

Actowiz Solutions created an end-to-end Frozen Snacks Benchmarking Dataset, covering over 120 SKUs across leading platforms: BigBasket, Blinkit, Zepto, JioMart, Swiggy Assure, Hyperpure, LOTS Wholesale, Metro Cash & Carry and Walmart Best Price.

Background

Navratri Mega Sale Price Tracking

Frozen foods are now a high-demand category for:

  • Home consumers
  • Restaurants
  • Cafes
  • Cloud kitchens
  • Caterers
  • Modern trade stores
  • Q-commerce platforms

The challenge is that every platform sells these brands at different:

  • Pack sizes
  • Prices
  • Discounts
  • MOQ levels
  • Wholesale slabs
  • Combo offerings
  • In-stock availability

This creates complexity for:

  • Procurement managers
  • Category heads
  • Brand managers
  • Distributors
  • Foodservice buyers

They needed accurate, real-time benchmarking data to understand category competitiveness.

Scope of Work

Brands Covered
  • McCain
  • ITC Master Chef
  • Hyfun
  • Yummiez
Platforms Monitored
Retail (B2C):
  • Blinkit
  • Zepto
  • BigBasket
  • JioMart
Foodservice (B2B):
  • Swiggy Assure
  • Hyperpure
  • LOTS Wholesale
  • Metro Cash & Carry
  • Walmart Best Price
Product Types Covered
  • French Fries (6mm, 9mm)
  • Potato Wedges
  • Hash Browns
  • Veggie Nuggets
  • Cheese Nuggets
  • Momos
  • Burger Patties
  • Pizza Pockets
  • Ready-to-Cook Snacks

Actowiz Solutions' Benchmarking Framework

To compare brands accurately, Actowiz Solutions deployed:

1. SKU-Level Extraction System

Capturing:

  • Pack size (200g, 400g, 1kg, 2.5kg)
  • Price
  • Price per kg
  • MRP vs selling price
  • Discounts
  • Availability
  • Category placement
  • B2B pricing slabs
  • MOQ levels
2. Pack-Size Normalization Engine

Example:

  • "2.5kg Pouch"
  • "Pack of 5 x 500g"
  • "Bulk 1kg Foodservice Pack"

All normalized to KG-based units.

3. Cross-Brand Attribute Standardization

Mapped attributes:

  • Product type
  • Cut-size
  • Base ingredients
  • Cooking method
  • SKU category
4. Platform-Wise Price Mapping

Retail vs Wholesale comparisons to see:

  • Who is cheapest
  • Who is premium
  • Who changes price fastest
5. Availability Monitoring

Captured "In-stock", "Out-of-stock", "Limited", "Unavailable in your area".

6. Discount & Promo Detection

Identified:

  • Promotional spikes
  • Combo offers
  • Coupon effects
  • Festival deals

Sample Data Extracted (Illustrative)

Table 1: Price Comparison — French Fries 1kg
Platform McCain ITC Master Chef Hyfun Yummiez
Blinkit ₹198 ₹185 ₹175 OOS
Zepto ₹205 ₹189 ₹178 ₹195
BigBasket ₹190 ₹180 ₹170 ₹188
JioMart ₹182 ₹176 ₹162 ₹185

Insight: Hyfun consistently offers the lowest price for 1kg fries.

Table 2: Pack-Size Variance – Veg Nuggets
Brand Pack Sizes Available Notes
McCain 200g, 400g, 1kg Strong retail presence
ITC 400g, 1kg, 2.5kg Focus on foodservice
Hyfun 1kg, 2.5kg Dominant in Horeca
Yummiez 400g, 1kg Retail + B2B mix
Table 3: B2B Foodservice Pricing – 2.5kg Fries
Platform McCain ITC Hyfun Yummiez
Hyperpure ₹465 ₹450 ₹430 ₹445
LOTS Wholesale ₹480 ₹455 ₹435 OOS
Metro ₹470 ₹460 ₹428 ₹450
Walmart Best Price ₹460 ₹455 ₹420 ₹445

Insight: Hyfun is the most aggressively priced in B2B.

Key Insights From the Benchmark

A. Hyfun Dominates Value Positioning

Across both retail and B2B:

  • Lowest price-per-kg
  • Wide B2B pack selection
  • Consistent availability

Hyfun clearly targets value-driven buyers.

B. ITC Positions as Premium Foodservice Brand

ITC Master Chef SKUs show:

  • Higher average selling price
  • Stronger presence in 2.5kg packs
  • Best performance in Horeca channels
C. McCain Owns the Retail Mindshare

McCain ranks highest in:

  • Studies brand recall
  • Shelf visibility on Zepto/Blinkit
  • Search ranking on BigBasket

McCain remains the most consumer-facing brand.

D. Yummiez Shows Category Variance

Yummiez performs strongly in:

  • Nuggets
  • Burger patties
  • Ready-to-cook varieties

But has uneven visibility in fries and wedges.

E. B2B Platforms Offer Up to 25–35% Lower Price Than Retail

For bulk buyers:

  • 2.5kg packs outperform 1kg retail pricing
  • Hyperpure and Walmart Best Price had best rates
F. Stock-Out Patterns

Major OOS cases found for:

  • Yummiez fries on Blinkit
  • ITC 2.5kg SKUs during peak times
  • McCain nuggets inside smaller dark stores

Deep-Dive: Category-Level Insights

French Fries
  • Most competitive category
  • Price difference of up to ₹40 per kg
  • Hyfun highest availability
Nuggets
  • ITC and McCain lead
  • Yummiez competes on price
  • Hyfun targets foodservice buyers
Burger Patties
  • McCain dominates retail
  • ITC strong in QSR usage
Momos
  • Yummiez performs best
  • Strong value-for-money positioning
Frozen Cheese Snacks
  • ITC and McCain lead premium segment
  • Hyfun focuses on bulk packs

Actowiz Solutions' Benchmark Workflow

1. Multi-Platform Data Extraction

Real-time extraction from both retail & B2B.

2. SKU Standardization

Mapped multi-pack variations into unified comparisons.

3. Price Normalization

Converted all prices to price per kg.

4. Availability Tracking

Time-based in-stock and out-of-stock detection.

5. Cross-Brand Comparison

Ranked brands on:

  • Price
  • Availability
  • Pack-size range
  • Value position
  • Category strength

6. Automated Insights Dashboard

Deliverables included:

  • Price heatmaps
  • Availability trends
  • Brand position matrix
  • Category-level competitiveness

Business Impact

Better Procurement Decisions

Retailers adjusted buying based on the most cost-efficient suppliers.

Improved Category Pricing

Retailers optimized margins after studying price-per-kg values.

Stronger Negotiation Power

Brands offered better trade deals once shown competitive data.

Clear Brand Positioning

Retailers understood:

  • Which brand is premium
  • Which is value
  • Which performs best on retail vs B2B

Correct Pack-Size Assortment

Platforms added missing sizes to improve conversions.

Reduced Stock-Out Loss

Availability insights improved replenishment planning.

Why Actowiz Solutions Was the Right Fit

  • Deep experience in foodservice data extraction
  • Expertise in pack-size mapping
  • Ability to compare B2C + B2B platforms together
  • Precise brand benchmarking
  • Real-time availability tracking
  • Custom dashboards for easy insights

Actowiz Solutions continues to help global brands with SKU benchmarking, price intelligence, and frozen snacks category insights.

Conclusion

Frozen snacks have become a high-growth category, but pricing, pack sizes, promotions and availability differ widely across platforms. With Actowiz Solutions’ benchmarking intelligence, retailers and brands finally have a clear picture of who leads in value, visibility and competitiveness.

This case study highlights how structured data, cross-platform monitoring and SKU-level intelligence can empower better decisions in the frozen food ecosystem.

Social Proof That Converts

Trusted by Global Leaders Across Q-Commerce, Travel, Retail, and FoodTech

Our web scraping expertise is relied on by 3,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.

3,000+ Enterprises Worldwide
50+ Countries Served
20+ Industries
Join 3,000+ companies growing with Actowiz →
Real Results from Real Clients

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

1 min
★★★★★
"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"
FC
Febbin Chacko
Small Business Owner
Fin
2 min
★★★★★
"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."
JI
Javier Ibanez
Head of Analytics
atacy.es
1:30
★★★★★
"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."
RK
Rajesh Kumar
CTO
QComm Brand
4.8/5 Average Rating
📹 50+ Video Testimonials
🔄 92% Client Retention
🌍 50+ Countries Served

Join 3,000+ Companies Growing with Actowiz

From Zomato to Expedia — see why global leaders trust us with their data.

Why Global Leaders Trust Actowiz

Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.

icons
7+
Years of Experience
Proven track record delivering enterprise-grade web scraping and data intelligence solutions.
icons
4,000+
Projects Delivered
Serving startups to Fortune 500 companies across 50+ countries worldwide.
icons
200+
In-House Experts
Dedicated engineers across scrapers, AI/ML models, APIs, and data quality assurance.
icons
9.2M
Automated Workflows
Running weekly across eCommerce, Quick Commerce, Travel, Real Estate, and Food industries.
icons
270+ TB
Data Transferred
Real-time and batch data scraping at massive scale, across industries globally.
icons
380M+
Pages Crawled Weekly
Scaled infrastructure for comprehensive global data coverage with 99% accuracy.

AI Solutions Engineered
for Your Needs

LLM-Powered Attribute Extraction: High-precision product matching using large language models for accurate data classification.
Advanced Computer Vision: Fine-grained object detection for precise product classification using text and image embeddings.
GPT-Based Analytics Layer: Natural language query-based reporting and visualization for business intelligence.
Human-in-the-Loop AI: Continuous feedback loop to improve AI model accuracy over time.
🎯 Product Matching 🏷️ Attribute Tagging 📝 Content Optimization 💬 Sentiment Analysis 📊 Prompt-Based Reporting

Connect the Dots Across
Your Retail Ecosystem

We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.

icons
Analytics Services
icons
Ad Tech
icons
Price Optimization
icons
Business Consulting
icons
System Integration
icons
Market Research
Become a Partner →

Popular Datasets — Ready to Download

Browse All Datasets →
icons
Amazon
eCommerce
Free 100 rows
icons
Zillow
Real Estate
Free 100 rows
icons
DoorDash
Food Delivery
Free 100 rows
icons
Walmart
Retail
Free 100 rows
icons
Booking.com
Travel
Free 100 rows
icons
Indeed
Jobs
Free 100 rows

Latest Insights & Resources

View All Resources →
thumb
Blog

How IHG Hotels & Resorts Data Scraping Helps Overcome Real-Time Availability and Rate Monitoring Issues

How IHG Hotels & Resorts data scraping enables real-time rate tracking, improves availability monitoring, and boosts revenue decisions.

thumb
Case Study

UK Grocery Chain Achieves 300% ROI on Promotional Campaigns

How a top-10 UK grocery retailer used Actowiz grocery price scraping to achieve 300% promotional ROI and reduce competitive response time from 5 days to same-day.

thumb
Report

Track UK Grocery Products Daily Using Automated Data Scraping to Monitor 50,000+ UK Grocery Products from Morrisons, Asda, Tesco, Sainsbury’s, Iceland, Co-op, Waitrose, Ocado

Track UK Grocery Products Daily Using Automated Data Scraping across Morrisons, Asda, Tesco, Sainsbury’s, Iceland, Co-op, Waitrose, and Ocado for insights.

Start Where It Makes Sense for You

Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.

icons
Enterprise
Book a Strategy Call
Custom solutions, dedicated support, volume pricing for large-scale needs.
icons
Growing Brand
Get Free Sample Data
Try before you buy — 500 rows of real data, delivered in 2 hours. No strings.
icons
Just Exploring
View Plans & Pricing
Transparent plans from $500/mo. Find the right fit for your budget and scale.
GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [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
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [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
                        )

                )

            [country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [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
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [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
                        )

                )

            [subdivisions] => Array
                (
                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [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
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [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
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 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
)

Request Free Sample Data

Our team will reach out within 2 hours with 500 rows of real data — no credit card required.

+1
Free 500-row sample · No credit card · Response within 2 hours