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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] => 216.73.216.122 [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] => 216.73.216.122 [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 )
In today's rapid-fire retail environment, online businesses need instant access to market data to make informed, timely decisions. That's where a Quick commerce data API comes into play. With demand for swift delivery and frequent changes in price, inventory, and promotions, having a robust data pipeline is no longer optional — it's essential. Actowiz Solutions leverages such APIs to extract, aggregate, and deliver clean, structured datasets from leading quick-commerce platforms across India. This empowers brands, retailers, and sellers to stay agile, responsive, and ahead of the competition.
The growth of quick commerce in India between 2020 and 2025 has been nothing short of explosive. According to industry data, the gross merchandise value (GMV) of the quick-commerce sector rose from about $0.5 billion in FY22 to around $3.3 billion in FY24 — reflecting an annual growth rate far faster than traditional e-commerce.
By 2025, the market is estimated to reach roughly $5.38 billion, with further projections pointing toward continued growth in the coming years.
Driving this boom is a surge in consumer adoption: in recent industry reports from 2025, the top three platforms —Blinkit, Zepto, and Swiggy Instamart — collectively fulfill over 4 million orders per day.
This level of scale, volatility, and rapid change makes real-time data not just valuable — but mission-critical.
Using Instamart API data, businesses get direct visibility into product listings, pricing changes, stock availability, and delivery zones. This is especially valuable because Instamart leverages its parent company's logistics infrastructure, enabling quick expansion since its 2020 launch.
From 2022 to 2025, as quick commerce gained traction, Instamart reportedly expanded its network aggressively, adding hundreds of dark stores across Indian cities, boosting its capacity to fulfil orders swiftly.
Especially for brands or resellers wanting to list or compete on Instamart, this data ensures your product catalog remains aligned — and you can adjust your strategy dynamically.
Through Zepto API data, clients can monitor Zepto's evolving catalog, regional availability, promos, and user-level demand signals. Zepto — launched in 2021 — has rapidly scaled, especially in metro areas, capturing a significant portion of emerging quick-commerce demand.
By 2025, Zepto is estimated to hold approximately 30% market share in India's quick commerce sector, behind the market leader but growing steadily.
Zepto's strength lies in rapid expansion and aggressive catalogue additions. Using API-powered data extraction, businesses can:
For sellers and brands, Zepto-derived data offers a way to understand fast-moving trends and region-specific demand — crucial for timely inventory and marketing decisions.
With Blinkit API data, businesses gain insight into the patterns of India's largest quick-commerce network. Blinkit — originally Grofers — redefined itself for the fast-grocery segment, and after its acquisition by a major parent in 2022, has aggressively scaled its dark-store infrastructure.
As of 2025, Blinkit reportedly commands around 44% of the quick-commerce market share, making it the dominant player.
Data from Blinkit's API can help businesses:
Because Blinkit covers a wide geographic footprint and has deep penetration, data from its API often reflects broader market trends, making it especially valuable for forecasting or planning at scale.
In today's hyper-competitive retail environment, speed and responsiveness matter. That's why having access to a Real-time quick commerce API can be a game changer for online businesses.
Traditional data-collection methods like manual checks or periodic scraping are slow, error-prone, and often outdated by the time they're processed. By contrast, APIs deliver structured data — prices, stock status, catalog updates, regional availability — in real time. This allows you to:
Given the pace at which quick commerce moves — with the top three players now handling millions of orders daily and continuously expanding — real-time APIs are no longer a luxury but a competitive necessity.
While quick commerce began largely with grocery and daily essentials, by 2025 the ecosystem has broadened to include personal care, household goods, electronics accessories, and more. This evolution is captured effectively by Quick Commerce & Grocery Data Scraping services.
Between 2022 and 2025, quick commerce platforms have expanded SKUs rapidly, adapting to user demand and market shifts. For instance, as per several industry trackers, the quick commerce sector is expected to cross $5.38 billion in 2025, with continued growth projected.
By combining data from multiple APIs and scraping sources, you can obtain a holistic view of the market — not just for groceries, but for all fast-moving consumer goods across quick commerce platforms.
Leveraging a Quick commerce data API gives businesses a strategic edge in an environment defined by speed, volatility, and intense competition.
Consider these advantages:
In short: if you treat quick commerce data as a core asset rather than an afterthought, you can build competitive advantage.
At Actowiz Solutions, we understand that not every business has technical resources to build and maintain complex data pipelines. That's why we offer end-to-end solutions centered on Quick commerce data API integration.
With our services, you can:
Whether you are a brand launching new SKUs, a retailer monitoring price competition, or a researcher analyzing trends — Actowiz gives you the data backbone you need to move fast and make informed decisions.
In the dynamic world of quick commerce, agility is everything. By adopting Web Scraping, Mobile App Scraping, and integrating a reliable real-time dataset via a Quick commerce data API, businesses can transform raw data into actionable insights — fast. As quick commerce continues to reshape retail in India, those who leverage data effectively will lead. Want to stay ahead? Contact Actowiz Solutions today to unlock the power of real-time data for your business.
You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!
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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
Real Estate
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×
Organic Grocery / FMCG
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
Quick Commerce
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
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
Beverage / D2C
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
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
Real results from real businesses using Actowiz Solutions
In Stock₹524
Price Drop + 12 minin 6 hrs across Lel.6
Price Drop −12 thr
Improved inventoryvisibility & planning
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
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
With hourly price monitoring, we aligned promotions with competitors, drove 17%
Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place
Actowiz Solutions delivers real-time product scraping from Quick Commerce platforms, helping online businesses track prices, trends, and competitors instantly.
Brands can Scrape Top Selling Winter Apparel Categories on H&M, Zara, and Pantaloons to track trends, optimize inventory, and boost winter sale revenue.
Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.
Benchmark 2025 foodservice pricing, pack sizes, discounts, MOQ & availability scraped from Hyperpure, LOTS, Metro & Walmart for top brands. Powered by Actowiz Solutions.
A Quick Commerce Data API delivers real-time pricing, inventory, and product insights from Instamart, Zepto, and Blinkit, helping businesses stay competitive.
Scraping Germany Food Delivery App Data reveals a 78% consumer shift to online meals and hyperlocal delivery, helping brands optimize pricing, menus, and market reach.
Discover how automated scraping was used to extract McDonalds USA store locations data at scale, mapping 10,000+ outlets with precise geospatial and operational insights.
Discover how Nike.com price scraping with Python enabled real-time monitoring of flash sales and dynamic pricing, helping brands track discounts and trends efficiently.
Uncover how data-driven strategies optimize dark store locations, boosting quick commerce efficiency, reducing costs, and improving delivery speed.
Track how prices of sweets, snacks, and groceries surged across Amazon Fresh, BigBasket, and JioMart during Diwali & Navratri in India with Actowiz festive price insights.
Explore the Future of Web Scraping in the U.S. for Market Forecasts. Get insights on tools, ethics, regulations, and emerging industry trends.
Explore the top 10 real-world use cases of web scraping in 2025, enabling smarter business decisions, market insights, competitor analysis, and data-driven growth.
Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.
Our team focuses on clear, transparent communication to ensure that every project is aligned with your goals and that you’re always informed of progress.
Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations