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GeoIp2\Model\City Object
(
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                            [ja] => コロンバス
                            [pt-BR] => Columbus
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            [registered_country] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
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            [traits] => Array
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        )

    [continent:protected] => GeoIp2\Record\Continent Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
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                            [de] => Nordamerika
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                            [es] => Norteamérica
                            [fr] => Amérique du Nord
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                )

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            [validAttributes:protected] => Array
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    [country:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [de] => USA
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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    [locales:protected] => Array
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        )

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

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

    [registeredCountry:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [ip_address] => 216.73.216.213
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
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                    [8] => isHostingProvider
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                    [11] => isPublicProxy
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                )

        )

    [city:protected] => GeoIp2\Record\City Object
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                    [geoname_id] => 4509177
                    [names] => Array
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                            [de] => Columbus
                            [en] => Columbus
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [validAttributes:protected] => Array
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    [location:protected] => GeoIp2\Record\Location Object
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                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

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

        )

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

    [subdivisions:protected] => Array
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            [0] => GeoIp2\Record\Subdivision Object
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                    [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
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                    [validAttributes:protected] => Array
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)
 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
)

Introduction

India’s ecommerce ecosystem has matured rapidly, with Amazon India and Snapdeal emerging as critical platforms for brands, aggregators, and high-volume sellers. These marketplaces host millions of SKUs where success depends on real-time visibility into pricing behavior, seller density, and competitive positioning.

Actowiz Solutions developed this research framework to deliver Seller Competition & Pricing Intelligence on Amazon India and Snapdeal, helping stakeholders decode how pricing wars, seller participation, and discount strategies evolve across categories. By tracking seller counts, price dispersion, and historical changes from 2020 to 2026, this report demonstrates how data-driven intelligence enables smarter marketplace decisions. From identifying margin erosion risks to uncovering growth opportunities, this research empowers sellers to compete confidently in India’s most dynamic ecommerce environments.

Mapping the Evolution of Seller Density

Understanding seller competition is critical on marketplaces where multiple sellers compete for the same Buy Box or listing visibility. Actowiz Solutions conducted a longitudinal study using Amazon India and Snapdeal seller competition analysis across apparel, home décor, kitchenware items, and electronics accessories.

Seller Growth Trend (2020–2026)
Year Avg Sellers per SKU YoY Growth
2020 10
2021 14 40%
2022 18 29%
2023 23 28%
2024 27 17%
2025 31 15%
2026 35 13%

Analysis: Seller density more than tripled between 2020 and 2026, driven largely by Amazon India’s low onboarding friction and Snapdeal’s value-focused seller ecosystem. Categories with minimal entry barriers experienced the sharpest growth, compressing margins and shortening pricing reaction windows. This trend reinforces the need for continuous competitive benchmarking.

Tracking Pricing Volatility Across Categories

Pricing behavior on Amazon India and Snapdeal reveals how aggressive discounting has become a baseline expectation. Through pricing intelligence systems, Actowiz monitored price changes and discount frequency across core categories.

Average Discount Frequency (2020–2026)
Year Avg Discount Events per Month Avg Discount %
2020 4 14%
2021 6 17%
2022 8 19%
2023 10 22%
2024 12 24%
2025 13 25%
2026 14 26%

Analysis: Discounting has evolved from seasonal campaigns to a continuous pricing lever. Sellers without pricing intelligence struggled to sustain margins, while data-driven sellers optimized discount depth and timing using competitor benchmarks.

Understanding Cross-Marketplace Competitive Pressure

Sellers increasingly operate across both Amazon India and Snapdeal. Actowiz analyzed cross-platform seller participation to measure competitive spillover effects.

Cross-Platform Seller Overlap (2020–2026)
Year Sellers Active on Both Platforms
2020 25%
2021 30%
2022 35%
2023 41%
2024 46%
2025 51%
2026 56%

Analysis: As more sellers operate on both platforms, pricing transparency increases. Discount replication across marketplaces accelerates price wars, making unified intelligence across Amazon India and Snapdeal essential for margin control.

Comparing Seller Pricing Strategies

With Amazon India vs Snapdeal Seller Pricing Intelligence, Actowiz examined how sellers adjust pricing by channel.

Average Price Gap by Category (2026)
Category Avg Price on Amazon India Avg Price on Snapdeal Price Gap
Apparel ₹549 ₹519 -₹30
Home Décor ₹849 ₹799 -₹50
Kitchenware ₹399 ₹369 -₹30
Electronics Acc. ₹749 ₹709 -₹40

Analysis: Sellers generally maintain premium positioning on Amazon India while using Snapdeal for value-driven volume. This highlights the importance of channel-specific pricing intelligence rather than uniform pricing strategies.

Benchmarking Seller Competition Intensity

To assess saturation risks, Actowiz created a Competition Intensity Index based on seller count and price dispersion.

Competition Intensity Index (2020–2026)
Year Avg Sellers per SKU Competition Index
2020 10 Low
2021 14 Medium
2022 18 Medium
2023 23 High
2024 27 High
2025 31 Very High
2026 35 Very High

Analysis: By 2026, most high-volume categories reached very high competition levels. Real-time competitor monitoring is now critical to maintain visibility and profitability.

The Role of Data Automation in Marketplace Intelligence

Actowiz Solutions leverages ecommerce data scraping and automation to power large-scale pricing and seller intelligence.

Automation Impact (2020–2026)
Metric 2020 2026
Manual Tracking Time 45 hrs/week 7 hrs/week
Pricing Reaction Time 48 hrs <4 hrs
Forecast Accuracy 64% 88%

Analysis: Automation reduced reaction times by over 90 percent, enabling sellers to respond to competitive signals almost instantly and outperform manual competitors.

Why Actowiz Solutions

Actowiz Solutions delivers enterprise-grade pricing and seller intelligence solutions that transform raw marketplace data into strategic advantage. With proven expertise in Seller Competition & Pricing Intelligence on Amazon India and Snapdeal, we provide:

  • High-frequency competitor tracking
  • Dynamic pricing intelligence dashboards
  • Seller benchmarking at SKU and category level
  • Scalable data pipelines for long-term growth

Our mission is to help ecommerce stakeholders stay ahead of market shifts and sustain profitability in hyper-competitive environments.

Conclusion

Success on Amazon India and Snapdeal depends on visibility, speed, and intelligence. This research shows how data-driven strategies enable smarter decisions in crowded marketplaces.

Through Seller Competition & Pricing Intelligence on Amazon India and Snapdeal, Actowiz Solutions empowers brands and sellers to anticipate price wars, optimize positioning, and protect margins in India’s fast-evolving ecommerce economy.

Ready to transform your marketplace strategy? Partner with Actowiz Solutions and turn competitive data into your strongest growth driver.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape Structure Analyze Visualize

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.

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

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×

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

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

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

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

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

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

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

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Driving Smarter Marketplace Decisions with Seller Competition & Pricing Intelligence on Amazon India and Snapdeal

Seller Competition & Pricing Intelligence on Amazon India and Snapdeal helps brands optimize pricing, track rivals, and make smarter marketplace decisions.

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Jan 07, 2026

Amazon India vs Flipkart vs Snapdeal Product Data Mapping – Comparing Prices, Seller Networks, and SKU Match Rates

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Jan 07, 2026

How Web Scraping Grab Taxi Data Helps Brands Decode Real-Time Ride Prices, Routes & Demand Trends?

Learn how web scraping Grab Taxi data reveals real-time ride prices, popular routes, and demand trends to help brands make smarter mobility decisions.

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Extracting GrabTaxi Fare & Availability Data to Improve Ride-Hailing Price Transparency

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How We Helped a Hospitality Brand Track 700+ Properties by Scraping Booking.com Hotel Prices in France

Scraping Booking.com hotel prices in France helps brands track real-time rates across 700+ hotels to optimize pricing strategies and stay competitive.

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Driving Smarter Marketplace Decisions with Seller Competition & Pricing Intelligence on Amazon India and Snapdeal

Seller Competition & Pricing Intelligence on Amazon India and Snapdeal helps brands optimize pricing, track rivals, and make smarter marketplace decisions.

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Scraping Top-Selling GrabMart Products - Top Categories & SKUs Across Singapore, Malaysia & Thailand

Detailed research on GrabMart’s top-selling products, highlighting leading categories and SKUs across Singapore, Malaysia, and Thailand for market insights

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City-Wise Demand & Delivery Time Analysis for NIC Ice Cream - Solving Last-Mile Challenges in Quick Commerce

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream reveals how data improves stock planning, delivery speed, and customer satisfaction across markets.

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