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GeoIp2\Model\City Object
(
    [city:protected] => GeoIp2\Record\City Object
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            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 4744870
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                            [de] => Ashburn
                            [en] => Ashburn
                            [es] => Ashburn
                            [fr] => Ashburn
                            [ja] => アッシュバーン
                            [pt-BR] => Ashburn
                            [ru] => Ашберн
                            [zh-CN] => 阿什本
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        )

    [location:protected] => GeoIp2\Record\Location Object
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                    [1] => accuracyRadius
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                    [3] => longitude
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                    [latitude] => 39.0469
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                    [time_zone] => America/New_York
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    [postal:protected] => GeoIp2\Record\Postal Object
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            [validAttributes:protected] => Array
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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    [subdivisions:protected] => Array
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                            [iso_code] => VA
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                                    [fr] => Virginie
                                    [ja] => バージニア州
                                    [pt-BR] => Virgínia
                                    [ru] => Вирджиния
                                    [zh-CN] => 弗吉尼亚州
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6255149
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                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                )

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    [country:protected] => GeoIp2\Record\Country Object
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                    [1] => geonameId
                    [2] => isInEuropeanUnion
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                    [4] => names
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [iso_code] => US
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                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
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                            [ru] => США
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            [validAttributes:protected] => Array
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                    [0] => queriesRemaining
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
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                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [zh-CN] => 美国
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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    [traits:protected] => GeoIp2\Record\Traits Object
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                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
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                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [ip_address] => 18.97.14.87
                    [prefix_len] => 18
                    [network] => 18.97.0.0/18
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    [raw:protected] => Array
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            [city] => Array
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                    [geoname_id] => 4744870
                    [names] => Array
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                            [de] => Ashburn
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                            [es] => Ashburn
                            [fr] => Ashburn
                            [ja] => アッシュバーン
                            [pt-BR] => Ashburn
                            [ru] => Ашберн
                            [zh-CN] => 阿什本
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                    [geoname_id] => 6255149
                    [names] => Array
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                            [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
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [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
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                    [accuracy_radius] => 20
                    [latitude] => 39.0469
                    [longitude] => -77.4903
                    [metro_code] => 511
                    [time_zone] => America/New_York
                )

            [postal] => Array
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                    [code] => 20149
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            [registered_country] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
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                            [ru] => США
                            [zh-CN] => 美国
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                )

            [subdivisions] => Array
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                            [geoname_id] => 6254928
                            [iso_code] => VA
                            [names] => Array
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                                    [de] => Virginia
                                    [en] => Virginia
                                    [es] => Virginia
                                    [fr] => Virginie
                                    [ja] => バージニア州
                                    [pt-BR] => Virgínia
                                    [ru] => Вирджиния
                                    [zh-CN] => 弗吉尼亚州
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                        )

                )

            [traits] => Array
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)

 country : United States
 city : Ashburn
US
Array
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    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS14618
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

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  • Scrape Milkbasket Grocery Data - Milkbasket Grocery App Scraping

Case Study - Scraping Grocery Data from Milkbasket Mobile App

This case study presents Actowiz Solutions' successful project in scraping grocery data from the Milkbasket mobile app. Actowiz Solutions leveraged web scraping techniques to gather comprehensive data and provide actionable insights for their client.

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Scraping-Grocery-Data-from-Milkbasket-Mobile

Abstract

This case study presents Actowiz Solutions' successful project in scraping grocery data from the Milkbasket mobile app. The objective was to extract and analyze valuable product information, pricing, and availability from Milkbasket, a popular online grocery delivery platform—Actowiz Solutions leveraged web scraping techniques to gather comprehensive data and provide actionable insights for their client.

Introduction

Actowiz Solutions, a leading data analytics company, was approached by a client interested in gaining a competitive edge in the online grocery market. The client sought detailed information about product offerings, pricing, and stock availability on the Milkbasket mobile app. Actowiz Solutions proposed a solution that involved scraping data from the Milkbasket app and transforming it into a structured format for analysis.

Objectives

Objectives

The key objectives of the project were as follows:

  • Extract comprehensive grocery data from the Milkbasket mobile app.
  • Collect information on product details, pricing, and stock availability.
  • Organize and structure the scraped data for further analysis.
  • Provide actionable insights to the client for strategic decision-making.

Methodology

Actowiz Solutions employed a robust scraping framework to extract data from the Milkbasket mobile app. The scraping process involved the following steps:

a. Reverse engineering: Actowiz Solutions reverse-engineered the Milkbasket app to understand its structure, data sources, and authentication mechanisms.

b. Data extraction: Using automated scraping tools and techniques, Actowiz Solutions extracted data from various app sections, including product listings, pricing, and availability.

c. Data transformation: The extracted data was cleaned, standardized, and transformed into a structured format, ensuring consistency and compatibility for further analysis.

d. Quality assurance: Actowiz Solutions implemented rigorous quality checks to ensure the accuracy and integrity of the scraped data.

e. Analysis and insights: Actowiz Solutions analyzed the scraped data to derive valuable insights, such as popular products, pricing trends, and stock availability patterns.

Results and Benefits

Actowiz Solutions' data scraping project yielded several benefits for the client:

a. Comprehensive data: The scraped data provided a comprehensive overview of Milkbasket's product offerings, pricing, and stock availability.

b. Competitive intelligence: The client gained valuable insights into their competitors' product range, pricing strategies, and stock management practices.

c. Pricing optimization: By analyzing pricing trends, the client was able to optimize their pricing strategy and remain competitive in the market.

d. Stock management: The data on stock availability helped the client identify potential supply chain bottlenecks and optimize their inventory management processes.

e. Decision-making support: The actionable insights from the scraped data enabled the client to make informed decisions, resulting in improved business outcomes.

Conclusion

Actowiz Solutions successfully executed the project to scrape grocery data from the Milkbasket mobile app, providing the client with a competitive advantage in the online grocery market. By leveraging web scraping techniques, Actowiz Solutions enabled clients to gain valuable insights, optimize pricing strategies, and enhance their stock management practices. This case study exemplifies the power of data scraping in extracting actionable intelligence for informed decision-making.

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 & palniring

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 inights Top-slling SKUs

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Our Data Drives Impact - Real Client Stories

Blinkit | India (Relail Partner)

"Actow's helped us reduce out of ststack 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

"Actow's helped us reduce out of ststack incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

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