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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] => 216.73.216.126 [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] => 216.73.216.126 [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 )
It has become increasingly easy for people to purchase things they want online. A similar has happened with sellers making stores to do online business at Flipkart, eBay, Walmart, Alibaba, etc. Although to get users' attention and convert them to customers, e-commerce sellers must utilize data analytics to optimize their offerings.
As of 2022, Amazon is the biggest e-commerce company in the U.S., with 38% of the total e-commerce retail sales. Many shoppers start their online searches on the Amazon website or app rather than using search engines like Yahoo or Google. This platform is an excellent data resource, allowing companies to make well-informed decisions and know customers well.
Amazon is the best place where you can get all the valuable and relevant data about sellers, reviews, products, news, special offers, ratings, etc. Gathering data from Amazon benefits everybody: buyers, sellers, and suppliers.
Rather than scraping hundreds of websites, gathering data from Amazon can assist solve the expensive procedure of scraping e-commerce data.
Let's see what type of data you can scrape:
There are some problems while scraping Amazon data to your own, despite the methods you select. The wickedest thing about self-scraping is you might not even expect the issues and might even meet unknown responses and network errors.
Here are a few examples of common problems you may face while scraping Amazon data to your own.
Amazon can easily control if the information is collected manually or using a boot scraper. It is detected by tracking a browser agent's behavior.
For instance, when a website finds scrapers or a user makes 400+ requests for similar pages at a particular time, some actions are taken against whoever is gathering the data. So, IP bans and captchas are utilized for blocking bots. If an IP address continues requesting pages without any Captcha details, this will get banned from Amazon, or an address will get blacklisted.
To conquer these obstacles, we at Actowiz Solutions use various methods and strive hard to make the behavior of crawlers more humanoid:
While collecting data on product descriptions from Amazon, you might have encountered many exceptions and response errors. The whole reason is that maximum scrapers are all set for a particular page structure, scraping HTML data from that and collecting relevant data. However, if a page's structure changes, a scraper could fail as it is not intended to deal with exceptions.
Amazon's site uses templates for updating product data, and pages have different layouts, HTML elements, and properties. It mainly emphasizes the main features and attributes of certain types of products. The product group or category recently added ASINs affect the templates utilized in the product installation procedure on Amazon.
So, to eliminate different inconsistencies, we at Actowiz Solutions write the codes in a way that can deal with the exceptions. By doing that, we ensure that our codes do not fail at the initial network or timeout errors.
One product could have diverse variations, helping customers to explore and select what they want. For instance, sweaters come in various sizes, and lipstick is available in multiple shades.
Product variations match the patterns we've drawn above and are presented on the website in various ways. And rather than getting rated on one type of a product, reviews and ratings are usually rolled up and reported by all accessible varieties.
We show total reviews when we gather customers' feedback data on Amazon. And to avoid the geolocation problem, we use the IP addresses of countries where we collect data on the Amazon platform.
It's tough to create a web scraper yourself, which will work for hours and gather hundreds of thousands of strings. The website's algorithms are mostly hard enough to extract as Amazon is different from other websites. The website is built to minimize the crawling practice.
Also, Amazon saves a significant amount of data. If you wish to gather content for the company's requirements, you must understand that extracting a considerable amount of material could be difficult, mainly if you do that yourself. It's a regular and time-consuming activity; therefore, creating an excellent, efficient web scraper will take time and effort!
The fast and dependable way is to leave Amazon data collection to professionals that can bypass the steeplechases of data scraping and systematically offer the data needed in the required format.
Amazon offers essential information collected in one place: reviews, ratings, products, news, exclusive offers, etc. Therefore, extracting data from Amazon would help you solve problems of the time-consuming procedure of scraping data from e-commerce websites. And there are vital benefits you could get if you include automatic web scraping methods in your work:
Price Comparison
Data scraping helps you regularly retrieve relevant competitors' pricing data from Amazon pages. If you don't track price changes in the marketplace, especially in peak seasons, you could get considerable losses in sales volumes online and competitive disadvantages. Price analysis could help you monitor pricing trends, analyze competitors, set promotions, and regulate the finest pricing strategy for staying in the market. A well-organized pricing strategy would raise profits and get more leads.
Recognize Targeted Group
Each dealer has a particular customer base that buys certain products—knowing the targeted group makes it easy to make reasonable options for selling products in demand. Researching customer sentiments and favorites on Amazon can assist you in clarifying the customer base, studying their purchasing habits, and planning various product sets for customers to increase sales.
Improve Product Profiles
Entrepreneurs must keep an eye on how the products sell in a marketplace. For Amazon sellers, the finest way of achieving higher sales is by putting products at the top of applicable searches. To make the product fit the description, you have to create and add a product profile. To study sentiments and make competitive analyses, you can get product data like pricing, ratings, ranks, reports, and reviews. Here, companies can better understand market trends and product positioning and properly create product profiles to applicable searches to get the goods on top and find more customers.
Demand Predictions
To regulate the most gainful niche, it is required to analyze market data comprehensively. This will help you analyze how the products fit in the current market, track interest in products on Amazon, and recognize which products have the highest demand. Extracting the platforms will offer you data that, after detailed study, can improve the supply chain and optimize the internal assortments, appropriately manage inventories and use superior production resources.
The primary winner is web scraping services if you need to select between various Amazon scraping procedures. Unlike the different methods, data scraping services can deal with all the problems given above. Hiring the best web scraping services will gather content and offer you quality data regularly. Web scraping services use professionals aware of different legal restrictions and won't have difficulties with blocking.
It will be more effective for the company if you put resources into the business and provide Amazon data collection to third-party firms with which you deal. They perform web scraping for you as per the set timeline.
Amazon is the world's biggest online retailer, where shoppers start their product search and are progressively confident in buying the items needed. E-commerce sellers must use data analytics to optimize products to convert an average consumer into a reliable customer.
That's where Amazon data scraping can offer a wealth of data in one place so that you can quickly speed up your Amazon data scraping procedure and use that to make critical business decisions. Also, avoid problems while scraping Amazon pages due to repeated queries or predictable behavior, and find assistance from scraping experts like Actowiz Solutions!
Contact us for all your mobile app scraping and web scraping services 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
Scraping Top Electronics Discount Insights to reveal 10 key trends from Amazon, Walmart & Best Buy. Discover real-time data on deals, prices & savings.
See how Actowiz Solutions helped a D2C beauty brand monitor 15K SKUs across Nykaa, Amazon & Myntra, boosting festive ROI by 36% with price intelligence.
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Discover the Top 10 Grocery Chains Locations in Florida 2025, highlighting store reach, market dominance, and strategic coverage across the state.
Scraping Noon Data for Track Prices, Ratings & Discounts with automated tools. Get real-time insights, 99% accuracy, and 3x faster price tracking.
Compare grocery prices 95% faster and 80% more accurately using the Real-Time Zepto Data Scraping API for instant insights across quick commerce platforms.
Monitor product availability and price drops on Black Friday 2025 with real-time insights, helping retailers optimize inventory, pricing, and maximize sales effectively.
Discover how Scraping Zepto Grocery Data for Price Comparison helped a meal planning app automate real-time pricing insights, optimize budgets, and enhance user experience.
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.
Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.
Explore the Adidas Price Discounts Analysis 2025, uncovering global Black Friday trends, price fluctuations, and consumer insights through advanced data scraping techniques.
Discover how Real-Time API Scraping from Myntra, Ajio & Nykaa provides actionable insights to track fashion trends, pricing, and market intelligence effectively.
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