🔥 Black  Friday  Countdown  :  50%  OFF  Unlock  Advanced  Data  intelligence  with  Actowiz.  Hurry  -  Bumper Offer  Ends  28 Nov  💥
🔥 Black  Friday  Countdown  :  50%  OFF  Unlock  Advanced  Data  intelligence  with  Actowiz.  Hurry  -  Bumper Offer  Ends  28 Nov  💥
🔥 Black  Friday  Countdown  :  50%  OFF  Unlock  Advanced  Data  intelligence  with  Actowiz.  Hurry  -  Bumper Offer  Ends  28 Nov  💥
strip strip strip
strip strip strip
× 
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] => 216.73.216.184
                    [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] => 216.73.216.184
                    [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
)

Start Your Project

+1 ▼

Google Maps Business Data Scraping: Buy Google Maps Business Datasets

Explore Google Maps Business users worldwide when you Buy Google Maps Business Datasets from Actowiz Solutions. Track User Sentiment and Engagement with Google Maps Business Data Scraping. Explore unique filtering abilities to find trends, or track sentiment, at your convenience.

Google Maps Dataset

Collect improved data fields scraped from Google Maps Business accounts with Google Maps Business Datasets in the USA, UK, and UAE. These data points include name, address, category, location, opening hours, reviews, ratings, phone, and more.

Frame.svg
IdPlace_NameCategoryAddressCityLatitudeLongitudeRatingReview_CountOpening_HoursWebsitePhonePrice_LevelPopular_TimesAttributesGoogleMaps_URL
1Central ParkParkNew York, NY 10022New York40.785091–73.9682854.8120 000+Always openhttps://www.centralparknyc.org/+1 212‑310‑6600–Peak: Sat/Sun afternoonsFree entry, Dog friendly, Bike pathshttps://www.google.com/maps/place/Central+Park/@40.785091,-73.968285,15z
2Times SquareLandmarkManhattan, NY 10036New York40.758896–73.9851304.6450 000+Always open–––Peak: Evenings, weekends24/7, Tourist spothttps://www.google.com/maps/place/Times+Square/@40.758896,-73.985130,15z
Download

Competitive Business Intelligence with Google Maps dataset

Learn your competitors using the Google Maps database, and find potential customers, to improve CRM for better marketing. Utilize Google Maps datasets to understand competitors with ratings and review data and locate them.

Competitive-Business-Intelligence-with-Google-Maps-dataset

Location Based Marketing with Google Maps datasets

Target the relevant audience using location-based data like a warehouse, store,real estate assets of your competitors, etc.

Location-Based-Marketing-with-Google-Maps-datasets

Optimize Marketing Strategy with Google Maps data

Utilize datasets from Google Maps to create sales outreach and marketing strategies. Discover businesses worldwide with ratings, reviews, and other details to find competitors and potential customers.

Optimize-Marketing-Strategy-with-Google-Maps-data

Features of Datasets

Get structured and easy-to-use datasets for each use case.

Structure Maintenance

We maintain data sets depending on structural changes in the website.

Customized Output Fields

You can define customized Output Fields depending on your business needs.

24/7 Assistance

We offer all-time support to our clients whenever they ask us.

Subscription

Depending on predefined scheduled subscription to data feeds of updated records.

Multiple Options for Delivery

Google Cloud PubSun, Microsoft Azure, Amazon S3, and SFTP.

Multiple Output File Formats

Get datasets in various formats like Excel, CSV, ndJSON, or JSON.

Dedicated Account Manager

We assign a dedicated account manager to manage your data scraping.

Data Scaling

Assign servers to manage thousands of data requests.

Data with Quality Assurance

Don't worry about the data quality; focus on better decision-making with accurate and reliable data.

You focus on significant business activities; we will handle your data needs.

Hassle-free Discovery

Click all the data points appearing on the websites that you find challenging to uncover if you try to collect them yourself.

Complete and Correct

Get precise, complete, and fresh datasets covering millions of web pages with billions of data fields.

Enriched Data

Boost the usability and value of your data sets by adding several data resources to generate a valuable and accurate dataset.

Leaders in Compliance

Actowiz Solutions is fully committed to complying with data protection rules and regulations, including CCPA and GDPR.

Prefer to scrape the data yourself?

Try our Web Scraper IDE, built on our patented proxy and unblocking technology.

Different Formats

We will deliver datasets in formats like CSV, Excel, ndJSON, or JSON to your preferred storage system.

We use Google Drives, Cloud Storage, AWS, SFTP, and other platforms to deliver the data.

Flexible Pricing

Pricing will depend on your requirements for data quantity and difficulty level. So share your requirements with our team, and we will quote after analyzing your requirements.

  • Free samples for already available datasets
  • Price begins from 0.001 USD per record
  • Dedicated account manager and support system
Monitor-SKUs,-sales-volume,

15,000+
Customers
Worldwide

Monitor-SKUs,-sales-volume,

Category Leader
#1 in Web Data
Monitor-SKUs,-sales-volume,

Analyze-entire-product

Used by: Business Leaders, Decision Makers, Analysts, Academics, Software Engineers, IT Professionals

Operational-dashboard

Fortune 500 Companies, Academic Institutions, Small-Medium Businesses, NGOs

FAQ
Yes, you will get daily, weekly, monthly, and custom updates on your datasets.

Yes, you can buy a subset, including the data points needed. By buying a subset, the cost is substantially reduced.

Select any one format: JSON, CSV, ndJSON, or XLSX.

If you don’t wish to buy a dataset, you can start extracting data utilizing our web data scraper.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize
Explore Solutions Get a Custom Demo

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.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
Trusted by Global Leaders – Secured by International Standards

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

Request Demo Access icon

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

All
Blog
Case Studies
Infographics
Report
Nov 27, 2025

How to Scrape News Articles With Python and AI Using a Powerful News Scraper?

Learn how to scrape news articles efficiently with Python and AI using a powerful News Scraper, automating content collection for analysis, insights, and research.

thumb

How Nike.com Price Scraping With Python Helped Monitor Flash Sales and Dynamic Pricing Trends

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.

thumb

Enhancing Deep Learning Models With Image Scraping

Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.

thumb

Data Scraping Trends for United States - Insights and Forecasts for 2025–2030

Explore the latest Data Scraping Trends for United States from 2025–2030, uncovering emerging technologies, market opportunities, and business insights.
Nov 27, 2025

How to Scrape News Articles With Python and AI Using a Powerful News Scraper?

Learn how to scrape news articles efficiently with Python and AI using a powerful News Scraper, automating content collection for analysis, insights, and research.

Nov 26, 2025

Real-Time Insights - Extract Menu & Pricing Data from Food Delivery App Platforms Like DoorDash & Uber Eats

Gain real-time insights by extracting menu and pricing data from food delivery apps like DoorDash and Uber Eats to track competitors, optimize offerings, and boost sales.

Nov 25, 2025

How Brands Use the Amazon & Walmart Dataset for Comparative Insights and Better E-Commerce Strategy?

Discover how brands leverage the Amazon & Walmart dataset for comparative insights, smarter pricing, competitor tracking, and optimized e-commerce strategies in real time.

Read More
thumb

How Nike.com Price Scraping With Python Helped Monitor Flash Sales and Dynamic Pricing Trends

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.

thumb

Scaling Fashion Product Data Extraction from H&M, Zara, SHEIN & Myntra to Power Real-Time Trend and Pricing Analytics

Scalable fashion product data extraction from H&M, Zara, SHEIN & Myntra, enabling real-time trend insights, pricing analytics, and competitive benchmarking.

thumb

Enhancing Homebuyer Decision-Making with HouseSigma Property Dataset Integration – How One Platform Increased Lead Conversions by 42%

Enhance property search experiences using the HouseSigma Property Dataset. Learn how one platform improved buyer confidence, and boosted lead conversions by 42%

Read More
thumb

Enhancing Deep Learning Models With Image Scraping

Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.

thumb

Dark Store Location Optimization - Data-Driven Strategy Explained

Uncover how data-driven strategies optimize dark store locations, boosting quick commerce efficiency, reducing costs, and improving delivery speed.

thumb

Festive Price Surge Tracker: Amazon Fresh vs BigBasket vs JioMart in India

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.

Read More
thumb

Data Scraping Trends for United States - Insights and Forecasts for 2025–2030

Explore the latest Data Scraping Trends for United States from 2025–2030, uncovering emerging technologies, market opportunities, and business insights.
thumb

USA Adidas Store Insights 2025 – Analyzing Retail Footprint Using Adidas Stores Location Dataset

Explore the USA Adidas retail footprint in 2025 with our Research Report using the Adidas Stores Location Dataset to analyze store locations and trends.
thumb

US Zara Store Count Dataset 2025 – Web Scraping Analysis of Zara Store Distribution Across the U.S.

Explore the US Zara Store Count Dataset 2025 with web scraping insights, analyzing Zara store distribution, expansion trends, and retail market strategies.
Read More
phone
Quick Connect
phone
Quick Connect