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GeoIp2\Model\City Object
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                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [ru] => Северная Америка
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    [country:protected] => GeoIp2\Record\Country Object
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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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            [validAttributes:protected] => Array
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                    [0] => queriesRemaining
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        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
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                    [iso_code] => US
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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    [traits:protected] => GeoIp2\Record\Traits Object
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                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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    [city:protected] => GeoIp2\Record\City Object
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                            [zh-CN] => 哥伦布
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    [location:protected] => GeoIp2\Record\Location Object
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            [validAttributes:protected] => Array
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            [validAttributes:protected] => Array
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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
)
Weekly E-commerce Price Comparison in Amazon India - Trends & Insights-01

Introduction

India's e-commerce market has grown exponentially over the past five years, with Amazon and Flipkart emerging as dominant players. For brands and retailers, understanding pricing dynamics across these platforms is crucial to staying competitive. Extract Amazon vs Flipkart Data for Price Comparison provides actionable insights into pricing trends, promotional strategies, and consumer behavior, enabling businesses to make informed decisions in real time.

With millions of SKUs across electronics, fashion, FMCG, and other categories, manual monitoring is inefficient. Leveraging automation and advanced data scraping tools ensures that businesses can Web Scraping for Price Insights in Amazon & Flipkart at scale. Real-time access to pricing information, discounts, and product availability empowers brands to benchmark their offerings, optimize promotions, and adjust pricing strategies dynamically.

By extracting structured data on product prices, sales trends, and category performance, businesses gain a comprehensive view of the competitive landscape. Price Tracking for Indian E-Commerce Platforms ensures timely intelligence, reduces revenue leakage, and helps brands respond effectively to market fluctuations. This blog explores how automated data extraction from Amazon and Flipkart can transform pricing strategy, optimize market positioning, and enhance decision-making across India's e-commerce ecosystem.

The Importance of Price Comparison in E-Commerce

Price comparison has become a critical factor for online shoppers in India. Between 2020 and 2025, studies show that more than 72% of Indian e-commerce customers compare prices across multiple platforms before purchasing, making it essential for brands to track competitors' pricing in real time. Extract Amazon vs Flipkart Data for Price Comparison provides businesses with actionable insights to stay competitive and respond to market trends effectively.

Amazon and Flipkart together cover millions of SKUs across electronics, fashion, FMCG, and home appliances. Monitoring such a vast product catalog manually is inefficient and prone to errors. Leveraging Web Scraping for Price Insights in Amazon & Flipkart, businesses can automatically extract detailed product information, pricing, and promotional data at scale. Real-time data enables brands to benchmark their pricing, track seasonal promotions, and optimize discounts to capture more sales.

For example, electronics discounts during festive seasons like Diwali typically range from 10% to 30%, while fashion and home appliances promotions see similar fluctuations. Using Price Tracking for Indian E-Commerce Platforms, companies can forecast these trends and align their marketing and inventory strategies accordingly.

Year Amazon Avg Discount (%) Flipkart Avg Discount (%) Key Categories
2020 12% 11% Electronics, Fashion
2021 14% 13% Electronics, Home Appliances
2022 16% 15% FMCG, Fashion
2023 18% 17% Electronics, FMCG
2024 20% 19% Fashion, Home Appliances
2025 22% 21% Electronics, FMCG, Fashion

By extracting structured data, retailers can identify which SKUs drive the most revenue, which products are underperforming, and where promotional opportunities exist. Scraping Product Price Data from Amazon allows detailed SKU-level tracking, while Real-Time Price Tracking for Flipkart ensures timely action.

Automation combined with analytical tools provides insights not just on pricing but also on product availability, stock levels, and discount frequency. Brands leveraging Extract Amazon vs Flipkart Data for Price Comparison can proactively adjust pricing strategies, run targeted campaigns, and improve profitability while enhancing customer satisfaction.

This data-driven approach ensures businesses remain competitive, react to real-time market changes, and maintain a strong foothold in India's growing e-commerce sector.

Automation and Scalability in Price Monitoring

Manual price monitoring across Amazon and Flipkart is time-consuming, error-prone, and impossible at scale given the millions of SKUs listed on these platforms. Automation solves this challenge. By Extract Amazon vs Flipkart Data for Price Comparison, companies can monitor pricing trends and promotions in real time, ensuring that decision-makers have timely, actionable insights.

Automated tools like Automated Price Scraping from Amazon & Flipkart allow businesses to track product prices, discounts, stock availability, and promotional campaigns across categories such as electronics, FMCG, and fashion. These tools refresh data at set intervals, ranging from hourly to real time, depending on the SKU and strategic importance.

Metric 2020 2021 2022 2023 2024 2025
SKUs Tracked 25,000 35,000 45,000 55,000 65,000 75,000
Data Refresh Frequency Weekly Weekly Daily Daily Hourly Hourly

Automation enables brands to Extract Real-Time Price Data from Amazon & Flipkart Sales and respond immediately to competitor price changes or promotions. For example, if Flipkart runs a flash sale on mobile phones, an automated system can alert Amazon sellers to adjust pricing or run counter-promotions.

In addition, Indian Market E-Commerce Data Scraping provides regional insights, helping businesses understand differences in demand and pricing across metro and tier-2 cities. SKU-level insights allow brands to identify best-selling products, high-margin items, and underperforming SKUs for better inventory planning.

Automated, scalable solutions reduce operational overhead, improve accuracy, and allow retailers to focus on strategy rather than manual data collection. Businesses that leverage these capabilities gain a competitive edge by making faster, smarter, and more informed pricing decisions across India's dynamic e-commerce landscape.

Boost efficiency and accuracy by leveraging automation and scalable price monitoring, enabling real-time insights and smarter, faster e-commerce decisions.
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SKU-Level Insights for Competitive Benchmarking

SKU-level insights are critical for understanding the performance of individual products across Amazon and Flipkart. By Scrape Amazon Product Data, businesses can monitor pricing, discounts, and sales trends at a granular level. Coupled with Web Scraping Flipkart Data, retailers can benchmark products across platforms to optimize competitive positioning.

From 2020 to 2025, SKU-level monitoring adoption in India increased by over 65%, emphasizing its importance for strategic decision-making. SKU-level data helps businesses identify top-performing products, forecast demand, and plan promotions effectively. For example, tracking pricing and discount trends on high-demand electronics during festive seasons allows companies to allocate inventory efficiently and maximize sales.

Category Amazon Avg Price ($) Flipkart Avg Price ($) Avg Discount (%)
Electronics 250 245 15
FMCG 20 19 10
Fashion 40 38 12
Home Appliances 150 145 18

Using Ecommerce & Marketplace Scraping, companies can track pricing patterns, identify high-demand SKUs, and detect regional variations in promotions and discounts. This data enables businesses to run targeted campaigns, optimize pricing strategies, and improve revenue performance.

Additionally, monitoring SKU-level data allows retailers to compare product performance against competitors, identify gaps in the market, and make strategic assortment decisions. Integrating SKU insights into dashboards and analytics tools ensures continuous, actionable intelligence for decision-makers, enabling brands to maintain an edge in India's competitive e-commerce environment.

Regional and Category-Level Insights

In India, pricing and consumer behavior vary widely across regions. Leveraging Web Scraping for Price Insights in Amazon & Flipkart enables businesses to uncover these differences and optimize their strategies at a regional level. For example, festive discounts on electronics may vary by state, with northern regions offering higher promotional percentages compared to southern or eastern regions. By extracting structured data, brands can identify which products are performing well in specific areas and tailor marketing campaigns accordingly.

Using Price Tracking for Indian E-Commerce Platforms, companies can monitor category-specific pricing trends across multiple states and cities. Between 2020 and 2025, the average discount on electronics ranged from 15% in tier-1 cities to 12% in tier-2 cities, while fashion discounts varied from 12% to 10% in the same regions. This variation highlights the importance of region-based strategies to maximize ROI.

Region Amazon Avg Discount (%) Flipkart Avg Discount (%) Popular Categories
North 18 16 Electronics, FMCG
South 14 13 Fashion, Electronics
West 17 15 FMCG, Fashion
East 15 14 Electronics, Home Appliances

By leveraging Extract Amazon Product Data, brands gain SKU-level insights across categories, allowing for more precise forecasting, inventory allocation, and promotion planning. For instance, tracking high-demand products like smartphones and kitchen appliances enables timely stock replenishment and competitive pricing.

Furthermore, Web Scraping Flipkart Data provides visibility into Flipkart-exclusive deals and regional promotions. Businesses can compare Amazon and Flipkart strategies, identify gaps in their own offerings, and align discounts to local market conditions.

Overall, regional and category-level insights derived from automated price tracking ensure brands remain competitive, respond dynamically to market shifts, and deliver tailored experiences that resonate with consumers across India's diverse e-commerce landscape.

Real-Time Insights and Trend Forecasting

Real-time intelligence has become essential for e-commerce success. Real-Time Price Tracking for Flipkart allows businesses to monitor live price changes, promotional campaigns, and competitor strategies continuously. Between 2020 and 2025, adoption of real-time monitoring increased by over 70% in India, as companies recognized the value of instantaneous market intelligence for maximizing revenue.

With Automated Price Scraping from Amazon & Flipkart, brands can track thousands of SKUs, identify trends in promotional activity, and forecast demand. For example, flash sales on electronics during Diwali showed a 20% uplift in revenue when companies leveraged real-time insights to adjust pricing and inventory.

Year Promotions Monitored Revenue Impact (%)
2020 1,500 12%
2021 1,800 14%
2022 2,200 17%
2023 2,700 20%
2024 3,300 21%
2025 4,000 22%

Real-time insights allow businesses to proactively respond to competitor campaigns. By leveraging Extract Real-Time Price Data from Amazon & Flipkart Sales, companies can implement dynamic pricing, optimize promotions, and reduce revenue leakage.

Using predictive analytics, businesses can also forecast upcoming trends based on historical price movements, consumer behavior, and competitor actions. By combining historical and real-time data, brands can anticipate high-demand periods, adjust inventory levels, and plan marketing campaigns more effectively.

Real-time intelligence also supports targeted decision-making at SKU, category, and regional levels. It helps identify the most profitable SKUs, the effectiveness of ongoing promotions, and opportunities for cross-platform price optimization. Extract Amazon vs Flipkart Data for Price Comparison ensures these insights are precise, actionable, and scalable, giving brands a clear advantage in India's competitive e-commerce market.

Gain a competitive edge with real-time insights and trend forecasting, enabling proactive pricing, optimized promotions, and data-driven e-commerce strategies.
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The Future of Price Comparison and Analytics

The future of Indian e-commerce depends on data-driven decision-making. Extract Amazon vs Flipkart Data for Price Comparison will become increasingly vital for brands aiming to remain competitive. Emerging technologies, including AI, machine learning, and enterprise-grade scraping, will enhance data quality, accuracy, and predictive capabilities.

Indian Market E-Commerce Data Scraping allows companies to continuously monitor competitor pricing, track new product launches, and capture promotional campaigns across platforms. This real-time, structured data supports actionable insights for pricing strategies, marketing campaigns, and inventory optimization.

Year SKUs Monitored Average Daily Price Updates
2020 25,000 1
2021 35,000 2
2022 45,000 3
2023 55,000 4
2024 65,000 5
2025 75,000 6

By integrating Ecommerce & Marketplace Scraping, retailers can capture deep insights across categories, regions, and consumer segments. For example, tracking both Amazon and Flipkart electronics and fashion categories reveals promotional patterns, pricing gaps, and top-selling SKUs.

Automation and predictive analytics enable dynamic pricing, targeted promotions, and optimized inventory management. Companies can respond in near real-time to market fluctuations, reducing revenue loss and improving customer satisfaction. By leveraging Web Scraping Services, brands gain continuous visibility into market trends, ensuring they remain agile in a fast-paced, competitive environment.

Ultimately, businesses that adopt advanced price comparison and data analytics strategies will outperform competitors in India's e-commerce market. Real-time monitoring, automated data extraction, and predictive insights allow brands to optimize pricing, promotions, and product assortment efficiently. Extract Amazon vs Flipkart Data for Price Comparison is no longer optional—it is essential for achieving sustained growth, profitability, and market leadership in the evolving Indian e-commerce landscape.

Why Choose Actowiz Solutions?

Actowiz Solutions provides end-to-end data extraction and analytics solutions tailored for India's e-commerce ecosystem. With Extract Amazon vs Flipkart Data for Price Comparison, businesses can gain actionable insights into pricing trends, promotions, and SKU-level performance across multiple product categories. Our tools combine automation, scalability, and real-time monitoring, ensuring that brands always have the latest market intelligence at their fingertips.

Through Scraping Product Price Data from Amazon and Web Scraping Flipkart Data, Actowiz Solutions enables brands to benchmark against competitors, forecast demand, and optimize pricing strategies effectively. Our enterprise-grade technology captures structured datasets, including product prices, discounts, ratings, and availability, allowing decision-makers to implement data-driven strategies with confidence.

By leveraging Real-Time Price Tracking for Flipkart and automated extraction capabilities, brands can identify seasonal trends, adjust promotions, and manage inventory efficiently. Actowiz Solutions delivers reliable, scalable, and precise insights that help businesses reduce revenue leakage, enhance market positioning, and maximize profitability in a highly competitive environment.

Conclusion

In India’s fast-growing e-commerce market, monitoring competitor pricing and promotional activity is critical for business success. Extract Amazon vs Flipkart Data for Price Comparison empowers brands to track real-time prices, analyze trends, and optimize strategies across multiple categories. By leveraging automated scraping tools, businesses can reduce manual effort, gain SKU-level insights, and respond quickly to competitor actions.

Actowiz Solutions provides a comprehensive platform for Automated Price Scraping from Amazon & Flipkart and Indian Market E-Commerce Data Scraping, ensuring businesses have structured, actionable intelligence for strategic decision-making. Companies can uncover emerging trends, benchmark against competitors, and improve profitability while maintaining an edge in a dynamic market.

By integrating data-driven insights into pricing, promotions, and inventory planning, retailers can enhance customer satisfaction, maximize sales, and maintain competitive relevance. Actowiz Solutions helps brands turn raw e-commerce data into a strategic advantage.

Stay ahead in India’s e-commerce landscape by leveraging Extract Amazon vs Flipkart Data for Price Comparison and real-time analytics to optimize pricing, promotions, and inventory management for sustainable growth.

You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!

GeoIp2\Model\City Object
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                        )

                )

            [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] => 216.73.216.165
                    [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
)

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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

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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.
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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
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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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Case Studies
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Oct 29, 2025

How to Extract Amazon vs Flipkart Data for Price Comparison Across India’s Leading E-Commerce Platforms?

Learn how to Extract Amazon vs Flipkart Data for Price Comparison to gain competitive pricing insights, optimize strategies, and track trends across India.

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Scraping Macy’s & Kohl’s for Retail Competitiveness to Benchmark Market Performance and Trends

Explore how Scraping Macy’s & Kohl’s for Retail Competitiveness provides actionable insights to benchmark pricing, promotions, and market trends effectively.

thumb

Regional Housing Supply & Demand Insights in the USA Using Automated Data Scraping Regional Housing Insights USA

Explore the latest US housing trends with Automated Data Scraping Regional Housing Insights USA, revealing supply, demand, and market opportunities in real time.

Oct 29, 2025

How to Extract Amazon vs Flipkart Data for Price Comparison Across India’s Leading E-Commerce Platforms?

Learn how to Extract Amazon vs Flipkart Data for Price Comparison to gain competitive pricing insights, optimize strategies, and track trends across India.

Oct 28, 2025

Scraping Consumer Preferences on Dan Murphy’s Australia - Unveiling 5-Year Trends Across 50,000+ Alcohol Listings (2020–2025)

Discover how Scraping Consumer Preferences on Dan Murphy’s Australia reveals 5-year trends (2020–2025) across 50,000+ vodka and whiskey listings for data-driven insights.

Oct 27, 2025

Scraping APIs for Grocery Store Price Matching - Comparing Walmart, Kroger, Aldi & Target Prices Across 10,000+ Products

Discover how Scraping APIs for Grocery Store Price Matching helps track and compare prices across Walmart, Kroger, Aldi, and Target for 10,000+ products efficiently.

thumb

Scraping Macy’s & Kohl’s for Retail Competitiveness to Benchmark Market Performance and Trends

Explore how Scraping Macy’s & Kohl’s for Retail Competitiveness provides actionable insights to benchmark pricing, promotions, and market trends effectively.

thumb

Using Amazon Review Scraping to Enhance Product Offerings and Optimize Seller Ratings

Discover how Amazon review scraping helps identify product gaps, improve offerings, and optimize seller ratings for better performance on the marketplace.

thumb

Leveraging Web Scraping to Track Stock Availability and Pricing Data on LCBO for Smarter Inventory Decisions

Discover how web scraping helps businesses track stock availability and pricing data on LCBO, enabling smarter inventory planning and real-time market insights.

thumb

Regional Housing Supply & Demand Insights in the USA Using Automated Data Scraping Regional Housing Insights USA

Explore the latest US housing trends with Automated Data Scraping Regional Housing Insights USA, revealing supply, demand, and market opportunities in real time.

thumb

UK Food Delivery Insights - Track Promotional Offers and Customer Ratings on Deliveroo & Uber Eats

Research UK food delivery trends by using data scraping to Track Promotional Offers and Customer Ratings on Deliveroo & Uber Eats effectively.

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Q-Commerce Insights 2025 - Track Product Availability Data for Q-commerce Platforms Across Blinkit, Zepto, and Swiggy Instamart

Explore 2025 Q-commerce trends by using Track Product Availability Data for Q-commerce Platforms across Blinkit, Zepto, and Swiggy Instamart for actionable insights.

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