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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] => 216.73.216.160
                    [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] => 216.73.216.160
                    [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
)
How-to-Boost-Your-Healthcare-Research-with-Medical-Clinic-Data-Scraping-Services

Introduction

Access to accurate and up-to-date information about medical clinics is crucial in today's rapidly evolving healthcare landscape. Whether you're a patient seeking a new healthcare provider or a healthcare researcher looking to study trends and demographics, having access to comprehensive medical clinic data can be invaluable. This is where a Medical Clinic Data Scraping Service can be a game-changer.

The Importance of Medical Clinic Data

Medical clinic data is of paramount importance in today's healthcare landscape for a variety of reasons. It serves as the foundation for informed decision-making, research, and the efficient delivery of healthcare services. Here's why medical clinic data is crucial:

Patient Access and Choice

For patients, having access to accurate and comprehensive medical clinic data is vital. It allows individuals to make informed choices about their healthcare providers. Patients can search for clinics that specialize in their specific medical needs, are located conveniently, or align with their preferences, such as accepting their insurance.

Healthcare Planning

Healthcare organizations, policymakers, and government agencies rely on medical clinic data to plan and allocate healthcare resources effectively. Understanding the distribution of clinics, their specialties, and patient demographics helps in creating healthcare policies and strategies.

Quality Assessment

Medical clinic data plays a key role in assessing the quality of healthcare services. Researchers and regulatory bodies can use this data to evaluate the performance of clinics, identify areas for improvement, and ensure that healthcare providers meet certain standards of care.

Research and Analysis

Healthcare researchers and analysts utilize medical clinic data to study healthcare trends, patient outcomes, disease prevalence, and other critical factors. This research informs medical advancements, treatment guidelines, and healthcare policies.

Market Analysis

For healthcare businesses and entrepreneurs, medical clinic data is invaluable for market analysis. It helps in identifying opportunities for new clinics, assessing competition, and understanding the healthcare needs of specific regions.

Emergency Preparedness

In times of crises, such as pandemics or natural disasters, having access to medical clinic data is crucial for emergency preparedness. It allows for the rapid mobilization of resources and coordination of healthcare services.

Patient Referrals

Healthcare professionals often refer patients to specialists or other clinics for specialized care. Having accurate data on clinics, including their specialties and available services, is essential for making appropriate referrals.

Cost Efficiency

Healthcare providers and insurers can use clinic data to promote cost-efficient care. By understanding which clinics offer cost-effective services and have positive patient outcomes, healthcare systems can optimize resource allocation.

Transparency

Transparent and easily accessible clinic data promotes trust between patients and healthcare providers. Patients can review clinic details, including contact information, services offered, and patient reviews, which fosters transparency in the healthcare decision-making process.

Telehealth and Remote Care

In the era of telehealth and remote healthcare services, medical clinic data helps patients find clinics that offer virtual consultations and other remote care options, improving access to healthcare services.

Continuity of Care

Clinic data facilitates the continuity of care for patients. It ensures that patients can easily transition between different healthcare providers while maintaining a comprehensive medical history.

Data Fields of Scraping Medical Clinical Data

Data-Fields-of-Scraping-Medical-Clinical-Data

When scraping medical clinic data, it's essential to gather a comprehensive set of data fields to provide a complete and useful dataset. Here are some key data fields that should be considered when scraping medical clinic data:

  • Clinic Name: The name of the medical clinic or healthcare facility.
  • Address: The physical location of the clinic, including street address, city, state or province, and postal code.
  • Phone Number: Contact details for the clinic, including a primary phone number.
  • Email Address: An email contact, often used for appointment scheduling or inquiries.
  • Website URL: The clinic's official website, if available.
  • Specialty: The medical specialty or focus area of the clinic (e.g., primary care, cardiology, dermatology, pediatrics, etc.).
  • Services Offered: A list of medical services provided by the clinic, including specific treatments, procedures, and specialties.
  • Operating Hours: The clinic's regular business hours, including days of the week and opening and closing times.
  • Accepted Insurance: Information about the health insurance plans accepted by the clinic, if applicable.
  • Languages Spoken: Languages in which clinic staff can communicate with patients.
  • Clinic Description: A brief description or summary of the clinic's mission, values, or services.
  • Patient Reviews: If available, patient reviews and ratings of the clinic's services and staff.
  • Clinic Affiliations: Any affiliations or partnerships with hospitals, healthcare networks, or other organizations.
  • Appointment Booking: Details on how patients can schedule appointments, whether online, by phone, or through other means.
  • Accessibility Information: Information about clinic accessibility, including wheelchair access, parking, and public transportation options.
  • Provider Information: Names and credentials of healthcare providers, including doctors, nurses, and specialists, associated with the clinic.
  • Additional Contact Information: Other contact details, such as fax numbers or additional email addresses.
  • Patient Policies: Information on clinic policies, such as cancellation policies, payment methods, and whether new patients are accepted.
  • Emergency Contact: Contact information for after-hours or emergency care, if provided by the clinic.
  • Accreditations and Certifications: Any relevant certifications, accreditations, or awards received by the clinic.
  • License Information: License numbers or credentials for healthcare providers and the clinic as a whole.
  • Images: Images of the clinic's exterior, interior, waiting areas, and medical facilities, if available.
  • Location Coordinates: Geographic coordinates (latitude and longitude) for mapping and navigation purposes.
  • Real-time Availability: If applicable, information on real-time appointment availability and booking.
  • Social Media Links: Links to the clinic's social media profiles (e.g., Facebook, Twitter, LinkedIn) for additional information and updates.
  • Patient Demographics: Data on the demographic characteristics of patients served by the clinic, if available and relevant.
  • Telehealth Services: Indication of whether the clinic offers telehealth or virtual healthcare services.

How Medical Clinic Data Scraping Works

Medical Clinic Data Scraping is the process of automatically extracting information about medical clinics from various online sources, such as websites, directories, and databases. This data is collected, structured, and organized into a dataset that can be used for various purposes, including patient research, healthcare analysis, and business planning. Here's how the process of Medical Clinic Data Scraping typically works:

Defining the Scope

The first step is to define the scope of the data scraping project. This includes determining the specific data fields to be collected (e.g., clinic name, address, phone number, specialty) and the sources from which the data will be extracted (e.g., healthcare directories, clinic websites, public databases).

Web Crawling

Web crawling is the automated process of navigating the internet to visit web pages and extract data. A web crawler, also known as a bot or spider, is programmed to follow links, visit web pages, and collect information. In the case of Medical Clinic Data Scraping, the crawler is directed to visit websites and pages containing information about medical clinics.

Data Extraction

Once the web crawler accesses a clinic's webpage or source, it uses data extraction techniques to locate and extract relevant information. This typically involves parsing the HTML content of the webpage to identify specific data fields, such as clinic names, addresses, and phone numbers.

Structured Data

The extracted data is then structured into a standardized format. This may involve cleaning and formatting the data to ensure consistency and accuracy. For example, addresses may be standardized to a common format, and phone numbers may be formatted consistently.

Data Storage

The structured data is stored in a database or spreadsheet. Each clinic's information is typically organized as a record, with each data field represented as a column. This structured dataset makes it easy to search, filter, and analyze the information.

Data Validation and Quality Assurance

To ensure the accuracy and reliability of the data, quality assurance checks may be performed. This may involve verifying phone numbers, cross-referencing data with multiple sources, and checking for duplicates or errors.

Real-time Updates

Some Medical Clinic Data Scraping services offer real-time updates to keep the dataset current. This involves periodically re-crawling sources to capture any changes, additions, or deletions of clinic information.

Output

The final output of the scraping process is a dataset or database containing the collected information. This dataset can be used for various purposes, such as patient research, healthcare analytics, marketing, or directory listings.

User Interface

Depending on the service or application, users may interact with a user interface or dashboard to customize search criteria, initiate data scraping, and retrieve the desired dataset.

Compliance and Ethics

It's crucial for Medical Clinic Data Scraping to be conducted in compliance with legal and ethical standards. This includes respecting website terms of service, adhering to data privacy regulations, and ensuring that the data is used responsibly and securely.

Medical Clinic Data Scraping is a powerful tool for healthcare professionals, researchers, patients, and businesses in the healthcare industry. It streamlines the process of gathering clinic information, enhances decision-making, and supports various healthcare-related applications. However, it's important to approach data scraping with integrity, transparency, and compliance with relevant laws and regulations.

Benefits of Using a Medical Clinic Data Scraping Service

Using a Medical Clinic Data Scraping Service offers numerous benefits for various stakeholders in the healthcare industry, researchers, and patients. Here are some of the key advantages:

Time Efficiency

Manual data collection from numerous sources can be time-consuming and labor-intensive. Data scraping automates this process, saving significant time and effort.

Comprehensive Data

Data scraping services provide access to a vast amount of clinic information, including details about medical services, specialties, locations, and contact information, ensuring users have a comprehensive dataset.

Customization

Users can tailor their search criteria to find clinics that meet their specific needs, such as location, specialty, insurance acceptance, and more.

Market Analysis

Healthcare businesses can use scraped data for market analysis, helping them identify opportunities, assess competition, and make data-driven decisions.

Patient Access

Patients can easily find clinics that offer the services they need and make informed decisions about their healthcare providers. This improves patient access to care.

Research and Analysis

Healthcare researchers and analysts can use the scraped data to conduct studies, analyze healthcare trends, and inform healthcare policies and strategies.

Quality Assessment

The data can be used to assess the quality and performance of clinics, helping healthcare organizations and regulators ensure high standards of care.

Cost Efficiency

Healthcare providers and insurers can identify cost-effective clinics that provide quality care, helping optimize resource allocation.

Transparency

Patients can access clinic details, including reviews and ratings, fostering transparency and trust in the healthcare decision-making process.

Provider Referrals

Healthcare professionals can use the data to refer patients to appropriate specialists or clinics, enhancing patient care.

Telehealth Services

Patients can identify clinics that offer telehealth services, particularly valuable in times of remote healthcare delivery.

Emergency Preparedness

The data supports emergency preparedness efforts, enabling rapid resource mobilization and healthcare coordination during crises.

Continuity of Care

The data facilitates the seamless transition of patients between healthcare providers while maintaining comprehensive medical histories.

Real-time Updates

Some services offer real-time data updates, ensuring that the information remains current, especially in the dynamic healthcare environment.

Streamlined Decision-making

Users can make more informed decisions about healthcare providers, services, and locations, leading to improved healthcare outcomes.

Improved Marketing

Healthcare organizations can use the data for targeted marketing efforts, reaching out to potential patients based on their specific needs and preferences.

Accessibility

Patients with specific accessibility requirements can easily find clinics with features like wheelchair access and nearby public transportation.

Data Integrity

Data scraping services can ensure the accuracy and consistency of the dataset, reducing errors and inaccuracies.

Patient Demographics

Researchers and healthcare planners can use demographic data to tailor healthcare services to the needs of specific patient populations.

How Does Actowiz Solutions Help in Scraping Medical Clinic Data?

Actowiz Solutions offers a specialized service for scraping medical clinic data, helping users gather comprehensive and accurate information about healthcare providers. Here's how Actowiz Solutions can assist in scraping medical clinic data:

Customization of Data Collection

Actowiz Solutions works with clients to define the specific criteria and preferences for data collection. This customization ensures that the scraped data aligns with the client's needs, whether it's based on location, specialties, services, or other parameters.

Source Selection

Actowiz Solutions identifies and selects the most relevant and reputable online sources for medical clinic data extraction. This includes healthcare directories, clinic websites, public databases, and other authoritative sources.

Advanced Web Crawling

Actowiz Solutions employs sophisticated web crawling techniques to systematically navigate the internet and access web pages containing clinic information. Their web crawlers are designed to be efficient, respectful of website terms of service, and capable of handling large volumes of data.

Data Extraction

Actowiz Solutions utilizes advanced data extraction algorithms to extract specific information from web pages. This process involves parsing the HTML content of web pages to locate and capture relevant data fields, such as clinic names, addresses, phone numbers, specialties, and more.

Data Structuring

The scraped data is structured and organized into a standardized format. This includes cleaning and formatting the data to ensure consistency and accuracy. Data fields are typically organized in a database or spreadsheet, making it easy to access, search, and analyze.

Quality Assurance

Actowiz Solutions places a strong emphasis on data quality. They conduct quality assurance checks to verify the accuracy and reliability of the scraped data. This may involve cross-referencing data with multiple sources, validating contact information, and checking for duplicates or errors.

Real-time Updates

Depending on the client's requirements, Actowiz Solutions can provide real-time updates to ensure that the dataset remains current. This involves periodic re-crawling of data sources to capture any changes or additions in clinic information.

Data Delivery

The final output of the scraping process is delivered to the client in the desired format, such as a structured database or spreadsheet. This dataset can be used for various purposes, including patient research, healthcare analysis, marketing, and more.

Legal and Ethical Compliance

Actowiz Solutions conducts data scraping in compliance with legal and ethical standards. They ensure that data is collected responsibly, respects privacy regulations, and adheres to website terms of service.

User Support

Actowiz Solutions offers user support throughout the data scraping process, addressing any questions, concerns, or technical issues that may arise.

Conclusion

Actowiz Solutions provides a comprehensive and tailored approach to scraping medical clinic data, helping clients access valuable information efficiently and ethically. Their expertise in web scraping, data extraction, and data quality assurance ensures that clients receive high-quality and reliable datasets for their healthcare-related needs. For your medical clinic data scraping requirements, contact Actowiz Solutions now! You can also reach us for all your data collection, mobile app scraping, instant data scraper and web scraping service requirements.

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] => 216.73.216.160
                    [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] => 216.73.216.160
                    [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

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Smarter product targeting

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“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

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“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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Co-Founder / Head of Product at Upright Data Inc.
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-Fin, Small Business Owner
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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

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