Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
 
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] => 216.73.216.150
                    [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] => 216.73.216.150
                    [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
)

Start Your Project

+1 ▼
  • Home
  • Work
  • Pack-Size Variance & Price Wars: A 10-Platform Grocery Case Study

Pack-Size Variance & Price Wars Across 10 Major Grocery Platforms Powered by Actowiz Solutions

Discover how pack-size differences drive major price wars across 10 leading grocery platforms. A data-driven case study powered by Actowiz Solutions.

Download Case Studies

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] => 216.73.216.150
                    [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] => 216.73.216.150
                    [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
)
+1 ▼

Note: You’ll receive it via email shortly after submitting the form.

Navratri Mega Sale Price Tracking

Executive Summary

Grocery shoppers rarely notice how the same SKU appears in different pack sizes across platforms—yet this small variation creates major price differences, inconsistent margins, and misleading comparisons. Retailers often struggle to understand how competitors structure pack sizes, price-per-unit, and promotions.

Actowiz Solutions built a complete competitive intelligence framework that analyzed pack-size variance, price-per-unit gaps, discount patterns, and retail-level promotions across 10 leading grocery platforms, including:

  • Amazon Fresh
  • Walmart
  • Instacart
  • Target
  • Kroger
  • BigBasket
  • Zepto
  • Blinkit
  • JioMart
  • Flipkart Grocery

Using our advanced grocery data extraction, pack-size standardization, price intelligence, and SKU-level competitive mapping, the study highlights how grocery brands face platform-wise price wars and how retailers can optimize pricing using structured data.

Background and Business Need

Grocery e-commerce platforms use a mix of strategies to influence consumer buying:

  • Smaller packs to keep visible prices low
  • Larger packs with “value deal” positioning
  • Exclusive pack sizes on specific platforms
  • Different promotional cycles
  • Surge pricing during peak hours
  • Inventory-led dynamic discounts

For grocery retailers and CPG brands, this creates challenges:

  • The same product looks different due to pack-size variation.
  • Price-per-unit comparison becomes impossible manually.
  • Discounts differ by region, time, or store.
  • Platforms give preference to “exclusive” pack-size SKUs.
  • Price wars increase operational pressure.

A retailer approached Actowiz Solutions to understand:

  • How pack sizes differ across 10 leading platforms
  • How price-per-unit fluctuates
  • Which platforms run the steepest promotions
  • How brands engage in price wars
  • Which categories show the highest variability

Actowiz Solutions deployed advanced web data extraction, pack-size mapping, and pricing intelligence pipelines to reveal trends that were otherwise impossible to see manually.

Scope of Work

Navratri Mega Sale Price Tracking

Actowiz Solutions analyzed top 20 grocery categories, including:

  • Dairy
  • Snacks
  • Beverages
  • Edible Oils
  • Staples
  • Breakfast Items
  • Frozen Foods
  • FMCG Essentials
  • Baby Care
  • Household Products

Across 10 platforms, using structured, real-time data extraction:

Platform Region Covered
Amazon Fresh USA, India
Walmart USA
Instacart USA
Target USA
Kroger USA
BigBasket India
Zepto India
Blinkit India
JioMart India
Flipkart Grocery India

Data Extraction Framework (Actowiz Solutions)

To ensure consistency, Actowiz Solutions deployed:

SKU-Level Data Crawlers

Capturing:

  • Title
  • Brand
  • Pack size
  • UOM
  • Price
  • Discount applied
  • Price-per-unit
  • Availability
  • Delivery time
  • Store-level variations
  • Historical prices (where applicable)
Pack-Size Normalization Engine

Handles variations such as:

  • “200g”, “0.2kg”, “Pack of 2 (100g each)”
  • “1L”, “1000ml”, “Family Pack 900ml”
  • “Buy 2 Get 1 Free” packs
Price Optimization Pipeline

Calculates:

  • Unit price
  • Price rank by platform
  • Discount depth
  • Promo tags
  • Platform-specific price wars
Taxonomy Mapping

Aligning each SKU to a unified category structure—L1, L2, L3, L4.

Competitive Intelligence Dashboards

Visualizing:

  • Lowest and highest price
  • Surge periods
  • Discount spikes
  • Unit-price gaps
  • Pack-size inconsistencies

Sample Data Extracted (Illustrative)

Pack-Size Variance for a Popular SKU: “Amul Butter”
Platform Pack Size Price Unit Price Discount
BigBasket 100g ₹52 ₹0.52/g 5%
Zepto 100g ₹55 ₹0.55/g 0%
Blinkit 200g ₹105 ₹0.52/g 6%
JioMart 500g ₹230 ₹0.46/g 12%
Amazon 100g ₹54 ₹0.54/g 0%

Insight: Larger packs on JioMart offer the lowest per-unit price.

Example: Coca-Cola Variants
Platform Pack Size Price Price/Litre Notes
Walmart 2L $1.99 $0.99/L Value pack
Instacart 1L $1.49 $1.49/L No discount
Target 1.25L $1.39 $1.11/L Promotional pack
Amazon Fresh 750ml $1.19 $1.58/L High markup

Insight: Instacart shows higher per-unit pricing due to convenience markups.

Findings & Insights

A. Pack-Size Manipulation Drives Perceived Value

Platforms intentionally change pack sizes to influence:

  • Search ranking
  • Price perception
  • Basket value
  • Promotion visibility

Example: A ₹99 small pack vs. a ₹145 medium pack creates illusion of value.

B. Unit-Price Gaps Go Up to 45–60%

Across categories:

  • Dairy: 22% gap
  • Beverages: 35% gap
  • Snacks: 18% gap
  • Staples: 45%+ in some cases
  • Oils: 30% gap due to exclusive packing
C. Retailers Engage in “Platform-Specific Price Wars”

Example:

  • Walmart aggressively undercuts Target
  • Amazon Fresh competes through bundled SKUs
  • Zepto runs micro-discounts during peak hours
  • Blinkit gives delivery-fee–driven implied discounts
D. Exclusive Packs Lead to Hidden Competition

Platforms create:

  • Special 850ml packs
  • 900g vs. 1kg packs
  • “Family Value” repacks
  • Combo packs

These cannot be directly compared by shoppers — but Actowiz Solutions maps them.

E. Discount Cycles Differ by Platform
Platform Discount Pattern
Walmart Weekly drops
Amazon Fresh Algorithmic dynamic pricing
Target Holiday-driven spikes
BigBasket Vendor-funded promos
Blinkit Hourly changes
Zepto Evening surge promos
JioMart Everyday low pricing
F. Price Wars Are Category-Specific

Highest volatility:

  • Soft drinks
  • Chips & snacks
  • Breakfast cereals
  • Cooking oils
  • Dairy (especially cheese & butter)
  • Baby diapers
  • Household cleaners

Actowiz Solutions’ Approach & Technical Execution

Data Extraction Across 10 Platforms

Real-time crawlers running every 2–6 hours.

Pack-Size Standardization Engine

Converts “Pack of 3 × 200g” → “600g”.

Normalized Pricing Engine

Calculates price-per-unit, discount depth, promo effect.

Multi-Platform SKU Matching

NLP + fuzzy match + attribute logic.

Price War Detection Algorithms

Monitor:

  • Time-of-day shifts
  • Region-wise variations
  • Retailer-driven promotions
Dashboards for Stakeholders

Interactive visuals:

  • Unit-price comparison
  • Category-level heatmaps
  • Pack-size variance charts
  • Platform ranking tables

Category-Level Deep Dive (Examples)

Dairy – Butter, Cheese, Milk
  • Exclusive 450ml milk packs on Blinkit
  • 900ml ghee pack only on Amazon Fresh
  • Walmart 2lb cheese yielding lowest unit price

Impact: Price gap up to 29%.

Beverages – Soft Drinks & Juices
  • Smaller SKUs dominate q-commerce
  • Value packs dominate Walmart & Target

Impact: Unit price gap 32–38%.

Snacks – Chips & Namkeen
  • Platform-exclusive sizes (e.g., 78g, 95g, 110g)
  • “Combo packs” manipulate true unit pricing

Impact: Unit-price gap 20–25%.

Oils & Staples
  • 850ml, 900ml, 950ml pack variations
  • Vendor-funded discounts on JioMart

Impact: Up to 45% price gap.

Sample Comparison Table (Multi-Platform)

Fortune Sunflower Oil (Illustrative)
Platform Pack Size Price Price/Litre
BigBasket 1L ₹145 ₹145
Zepto 900ml ₹136 ₹151
Blinkit 1L ₹149 ₹149
JioMart 1L ₹139 ₹139
Amazon 5L ₹640 ₹128

Insight: Bulk pack on Amazon offers the best per-unit pricing.

Business Impact & Outcomes

Actowiz Solutions helped the retailer gain:

Clear Understanding of Price Wars

Across all 10 platforms.

Improved Pack-Size Strategy

Launching competitive pack sizes for each platform.

Better Discount & Promotion Planning

Optimized based on real-time market behavior.

Accurate Unit-Price Benchmarking

Fair comparison across different pack sizes.

Automated Monitoring

Weekly price monitoring with dashboards.

Higher Margin Retention

By avoiding unnecessary price cuts.

Why Actowiz Solutions Was the Ideal Partner

  • Expertise in grocery data extraction
  • Strong pack-size mapping algorithms
  • Advanced price intelligence capabilities
  • Real-time tracking across 10 platforms
  • Clean, standardized datasets
  • Proven accuracy and scale

Actowiz Solutions stands as a leader in ecommerce pricing intelligence, pack-size variance analysis, and multi-platform SKU comparison.

Conclusion

Pack-size variance and competitive price wars influence customer buying more than brands realize.

This case study highlights how Actowiz Solutions enables grocery retailers to understand pricing dynamics, competitive positioning, and unit-price gaps across 10 major platforms.

With accurate data extraction, attribute standardization, SKU mapping, and dynamic pricing intelligence, retailers can stay ahead without sacrificing margins.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize
Explore Solutions Get a Custom Demo

Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
Trusted by Global Leaders – Secured by International Standards

Industry:

Fintech / Digital Payments

Result

Accurate daily voucher &

cashback visibility across platforms

★★★★★

“Actowiz Solutions helped us automate daily voucher and cashback data collection across PhonePe, Paytm, Flipkart, and Hubble. The API-driven delivery significantly improved offer accuracy and operational efficiency.”

Product Manager, Fintech Platform (India)

✓ Daily voucher & cashback tracking via Push & Pull APIs

View Case Studies

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

View Case Studies

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

View Case Studies

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

View Case Studies

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

View Case Studies

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

View Case Studies

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

View Case Studies

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

View Case Studies

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
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 highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

Request Demo Access icon

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

All
Blog
Case Studies
Infographics
Report
thumb
Feb 09, 2026

How to Scrape Supermarket Pricing Data by Postcode to Reduce Regional Price Gaps and Increase Retail Margins by 20%

Scrape Supermarket Pricing Data by Postcode to track regional price trends, monitor competitors, and optimize hyperlocal pricing strategies.

thumb

Getir UK 15-Minute Price Scraping in London Q-Commerce

Actowiz Solutions enabled real-time Getir UK price scraping across London to track 15-minute price changes, promotions, and hyperlocal availability in q-commerce.

thumb

10 Ways Data Scraping Drives Business Growth & Market Intelligence

Discover 10 powerful ways data scraping boosts business growth, from competitive price intelligence and demand forecasting to inventory tracking and market monitoring.

thumb

Baby Products API-Driven Price Intelligence - Analyzing Inflation’s Impact on Baby Products

This report examines inflation’s impact on baby products using Baby Products API-Driven Price Intelligence to provide accurate pricing insights and trends.
thumb
Feb 09, 2026

How to Scrape Supermarket Pricing Data by Postcode to Reduce Regional Price Gaps and Increase Retail Margins by 20%

Scrape Supermarket Pricing Data by Postcode to track regional price trends, monitor competitors, and optimize hyperlocal pricing strategies.

thumb
Feb 09, 2026

Scrape Restaurant & Cafe Menus and Prices Data in UAE for Solving Demand Forecasting and Cost Control Challenges

Scrape Restaurant & Cafe Menus and Prices Data in UAE for Solving Demand Forecasting and Cost Control Challenges with real-time pricing and menu insights.

thumb
Feb 09, 2026

The Race for "Now": Noon Minutes vs. Talabat Mart for the UAE’s Quick-Commerce Crown

Deep dive into the UAEs quick-commerce battle. Compare Noon Minutes and Talabat Mart pricing, speed, and market data with Actowiz Solutions.

Read More
thumb

Getir UK 15-Minute Price Scraping in London Q-Commerce

Actowiz Solutions enabled real-time Getir UK price scraping across London to track 15-minute price changes, promotions, and hyperlocal availability in q-commerce.

thumb

Glovo Quick Commerce Price Monitoring in Barcelona

Actowiz Solutions tracks hyperlocal Glovo prices in Barcelona using high-frequency q-commerce scraping to monitor pricing, promos, and availability.

thumb

Optimizing Customer Loyalty with Grab Rewards Data Scraping - Points, Tiers, and Rewards Analysis

Grab Rewards Data Scraping helps analyze reward points, offers, redemption trends, and user incentives to optimize loyalty and engagement strategies.

Read More
thumb

10 Ways Data Scraping Drives Business Growth & Market Intelligence

Discover 10 powerful ways data scraping boosts business growth, from competitive price intelligence and demand forecasting to inventory tracking and market monitoring.

thumb

Grocery Price Movement Tracker – Walmart, Instacart & Target

Real-time grocery price changes across Walmart, Instacart and Target. Track top SKU drops, increases and hourly volatility with Actowiz Solutions.

thumb

Enhancing Deep Learning Models With Image Scraping

Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.

Read More
thumb

Baby Products API-Driven Price Intelligence - Analyzing Inflation’s Impact on Baby Products

This report examines inflation’s impact on baby products using Baby Products API-Driven Price Intelligence to provide accurate pricing insights and trends.
thumb

UAE E-Commerce & Quick Commerce SKU Data Analysis - Price, Stock & Demand Insights

UAE E-Commerce & Quick Commerce SKU Data Analysis delivers insights on pricing, availability, trends, and performance to optimize catalogs and growth.
thumb

City-Wise SKU Demand and Pricing Trends - E-Commerce & Q-Commerce multi-Platforms

City-Wise SKU Demand and Pricing Trends - E-Commerce & Q-Commerce multi-Platforms, insights to compare demand, pricing, and growth patterns across cities
Read More
phone
Quick Connect
phone
Quick Connect