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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
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            [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] => 216.73.216.174
                    [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
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            [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] => 216.73.216.174
                    [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-Scrape-Amazon-Prices-Daily-Powered-by-Actowiz-Solutio

Executive Summary

In the rapidly evolving world of online retail, accurate and timely pricing is a game-changer. A prominent U.S.-based electronics retailer struggled with daily pricing insights on Amazon. By partnering with Actowiz Solutions, the client implemented a robust daily scraping solution that enabled them to monitor over 10,000 SKUs in near real-time. This empowered their dynamic pricing strategy and improved Buy Box ownership by 17%.

Client Background

The client, a well-established electronics brand selling through Amazon, Walmart, and their own D2C platform, found themselves at a competitive disadvantage due to delayed price updates and lack of granular visibility into competitor listings. They handled over 10,000 products on Amazon alone, yet relied on weekly manual price checks.

Business Challenges

The-Client
  • Delayed Price Intelligence – Prices were only reviewed every 3–4 days manually.
  • Buy Box Losses – Competitors captured the Buy Box by reducing prices strategically.
  • Lack of Competitive Benchmarking – No tracking of other sellers or private label pricing.
  • Missed Sale Events – Limited visibility during flash sales, Prime Days, and seasonal promos.

Solution by Actowiz Solutions

The-Client

Actowiz Solutions designed an automated scraping pipeline tailored to the client’s product portfolio.

Key Features:
  • Scraping Frequency: Every 2 hours for top-selling SKUs; every 6 hours for tail SKUs.
  • Amazon Domains Covered: amazon.com, amazon.in, amazon.co.uk (multi-region capability)
  • Scraped Attributes:
    • Product Title
    • ASIN
    • Current Price
    • Original Price / Discount
    • Seller Details
    • Availability Status
    • Prime Eligibility
    • Ratings & Review Count
    • Buy Box Ownership

Sample Data Table (Daily Extracted Data)

ASIN Product Name Price Discount Seller Prime Buy Box Owner
B08N5WRWNW Echo Dot (4th Gen) $27.99 30% Amazon Yes Amazon
B07FZ8S74R Fire TV Stick 4K $34.99 13% BestBuy Store Yes BestBuy Store
B0BLJ6N63K Galaxy M14 Smartphone $179 5% XYZ Retailer No XYZ Retailer

Technologies & Methodologies Used

  • Scraper Engine: Python + Playwright + Headless Browsers
  • Anti-Detection Mechanisms: Proxy Rotation, User-Agent Spoofing, Captcha Solving (2Captcha API)
  • Data Delivery: JSON feed to AWS S3 bucket + scheduled Excel export
  • API Integration: Realtime API with SKU endpoint filters
  • Alert System: Slack & email alerts on price drops >10% or Buy Box change
  • Custom Dashboard View

    The-Client

    Actowiz also developed a real-time PowerBI dashboard integrating scraped data. Key metrics included:

    • SKU-level price trends (24hr, 7d, 30d)
    • Discount flagging and depth analysis
    • Buy Box tracker across sellers
    • Prime vs Non-Prime price parity insights

    Results Achieved

    Metric Before Actowiz After Actowiz
    Buy Box Ownership 62% 79% (+17%)
    Avg. Price Refresh Delay 72 hrs 2 hrs (-97%)
    Dynamic Pricing Responsiveness Manual, weekly Automated, hourly
    Sales During Promo Windows Untracked +25% YOY Growth

    Client Testimonial

    "Actowiz transformed our Amazon playbook. Their hourly pricing feeds made our promotions smarter and margins stronger. We no longer guess – we know."

    – VP, eCommerce Strategy, U.S. Electronics Brand

    Compliance Considerations

    • Respecting Amazon’s TOS through scraping via public listings
    • Implementing rate limits, randomized access, and ethical data usage
    • Option for Amazon API (SP-API) hybrid integration

    Next Steps

    Want to automate your Amazon pricing strategy? Contact Actowiz Solutions for a demo.

    Conclusion

    With Actowiz Solutions’ expertise, the client achieved a game-changing edge in Amazon pricing intelligence. Hourly updates, deep insights, and real-time decision-making drove growth, higher Buy Box wins, and improved profitability.

    For sellers serious about staying ahead, daily Amazon price scraping isn't optional—it's essential. Actowiz delivers it at scale, securely and smartly.

    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

    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

    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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