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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] => 216.73.216.24 [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] => 216.73.216.24 [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 fast-paced digital marketplace, data has become the most powerful asset for businesses. From shopping patterns on e-commerce giants to local grocery purchases, actionable insights come from analyzing E-commerce Product & Review Dataset across multiple domains. That’s where the E-Commerce & Grocery Data Hub comes in—a centralized solution to unify insights from Amazon, Lazada, Zepto, and even travel platforms.
As consumers become more demanding, businesses need to access Real-Time Product Dataset to understand behavior, track competitor strategies, and optimize pricing. For instance, an Amazon Product Review Dataset can reveal product sentiment trends, while a Zepto Grocery Store Dataset can highlight real-time shifts in grocery demand. Similarly, integrating a Lazada Product Review Dataset or analyzing Travel & Tourism Datasets helps companies align with evolving consumer lifestyles.
By using Unified Dataset Services, businesses can enhance decision-making with AI-Enhanced Dataset Services, offering Product & Review Intelligence and competitive benchmarking through datasets such as Competitor Product Comparison Dataset and Real-Time Pricing & Reviews Dataset. Together, this creates a powerful E-Commerce & Grocery Data Hub that drives smarter, faster, and more profitable business decisions.
E-commerce and grocery sectors are undergoing a rapid transformation. Between 2020 and 2025, global e-commerce sales are projected to rise from $4.2 trillion to $7.4 trillion (Statista), while online grocery sales in India alone are forecasted to touch $24 billion. This exponential growth requires businesses to rely on E-Commerce & Grocery Data Hub solutions for comprehensive visibility.
With fragmented data sources, businesses often struggle to unify insights across multiple verticals. A centralized hub that merges Web Scraping Dataset Lazada , Amazon Product and Review Dataset , Web Scraping Grocery Prices Dataset, and Travel & Tourism Datasets provides businesses with one comprehensive view of customer demand, product pricing, and market competition.
Amazon is the largest e-commerce platform globally, with millions of reviews posted daily. Analyzing the Amazon Product Review Dataset allows businesses to track customer sentiment, uncover hidden issues, and identify opportunities for product improvement.
For instance, a report by eMarketer shows that 92% of consumers check product reviews before purchasing. Businesses that use the Amazon Product and Review Dataset can map review trends between 2020–2025 and align their strategies accordingly.
When combined with AI-Driven E-Commerce Data Insights, businesses can automate review categorization, detect fake reviews, and drive actionable Product & Review Intelligence at scale.
Lazada is Southeast Asia’s leading marketplace, where competition is fierce. By analyzing a Lazada Product Review Dataset alongside a Web Scraping Dataset Lazada, companies gain insights into product quality, customer satisfaction, and price positioning.
Between 2020–2025, Lazada’s GMV (Gross Merchandise Value) has grown at 19% CAGR, making it critical for brands to benchmark themselves against competitors. Leveraging Real-Time Pricing & Reviews Dataset allows businesses to monitor promotions, competitor launches, and customer feedback in real time.
By building insights from Lazada reviews and pricing data, businesses enhance Competitor Product Comparison Dataset models, enabling sharper pricing strategies and marketing campaigns.
With India’s quick-commerce boom, Zepto Grocery Store Dataset provides unmatched intelligence into grocery buying patterns. Groceries are among the most price-sensitive products, and data from Zepto reveals consumer demand in real-time.
Studies show that 72% of Indian consumers switched grocery platforms at least once between 2020–2023 due to better pricing or deals. By leveraging a Web Scraping Grocery Prices Dataset , businesses can monitor price changes of essentials like rice, milk, and vegetables, which fluctuate by up to 15% during festive seasons.
Key Benefits of Grocery Data Hub:
When integrated into AI-Enhanced Dataset Services, grocery datasets fuel Dynamic Pricing Software and ensure better consumer targeting.
Beyond e-commerce and groceries, the Travel & Tourism Datasets integrated into the hub provide businesses with a wider understanding of consumer spending. Travel is often correlated with retail and grocery purchases. For instance, international travelers show higher spending patterns on both groceries and e-commerce.
Between 2020 and 2025, the global travel booking market is expected to grow from $517 billion to $780 billion. This growth, when analyzed alongside retail data, creates a holistic picture of consumer demand. For example, cross-referencing a Real-Time Product Dataset from e-commerce with Travel & Tourism Datasets highlights seasonal shopping spikes during holiday periods.
This multi-sector intelligence supports retailers, travel agencies, and even FMCG brands to plan better marketing campaigns and promotions.
The integration of AI is the final layer that turns raw data into actionable insights. By applying AI-Driven E-Commerce Data Insights, companies can unlock patterns in pricing, reviews, and consumer behavior across multiple datasets.
Key use cases:
McKinsey research shows that businesses leveraging AI in e-commerce data saw a 30% increase in sales efficiency and 25% improvement in pricing accuracy between 2020–2025. This proves that unified intelligence hubs are essential for sustaining competitive advantage.
At Actowiz Solutions, we specialize in building Unified Dataset Services tailored to e-commerce, grocery, and travel sectors. Our E-Commerce & Grocery Data Hub combines structured and unstructured data sources, delivering real-time, actionable insights.
We offer:
By combining Web Scraping Grocery Prices Dataset, Amazon Product and Review Dataset, and Travel & Tourism Datasets, we help businesses unlock 360° insights. Whether you need Product & Review Intelligence or Real-Time Pricing & Reviews Dataset, our solutions are scalable, accurate, and industry-leading.
The convergence of e-commerce, grocery, and travel datasets highlights a new era of data-driven intelligence. With the E-Commerce & Grocery Data Hub, businesses can unify insights from Amazon, Lazada, Zepto, and travel platforms to stay ahead in a competitive market.
By leveraging AI-Driven E-Commerce Data Insights, companies gain real-time access to product performance, pricing, and customer sentiment. Whether you’re tracking competitor SKUs with a Competitor Product Comparison Dataset or improving loyalty with Product & Review Intelligence, the hub ensures better decisions at scale.
Ready to harness the power of unified datasets? Partner with Actowiz Solutions today and unlock smarter insights for your business future! 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
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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.
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Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.
Discover the top 10 most ordered grocery items during Navratri 2025. Explore popular festive essentials for fasting, cooking, and celebrations.
Explore how Scraping Online Liquor Stores for Competitor Price Intelligence helps monitor competitor pricing, optimize margins, and gain actionable market insights.
This research report explores real-time price monitoring of Amazon and Walmart using web scraping techniques to analyze trends, pricing strategies, and market dynamics.
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