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GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
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                    [geoname_id] => 4509177
                    [names] => Array
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                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [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
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            [country] => Array
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                    [iso_code] => US
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [postal] => Array
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            [registered_country] => Array
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                            [ru] => США
                            [zh-CN] => 美国
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                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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            [validAttributes:protected] => Array
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    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [iso_code] => US
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                        (
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            [validAttributes:protected] => Array
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        )

    [locales:protected] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
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        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
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                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [2] => isInEuropeanUnion
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        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.24
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
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                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
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                    [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
                        (
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                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

    [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
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                    [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
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)

 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
)

The increasing cost of groceries in Canada has become a significant concern, and web scraping has played a crucial role in revealing the underlying inflationary trends. By leveraging web scraping techniques, analysts have been able to collect and analyze data from various online sources to gain insights into the rising prices of essential food items.

Through web scraping, researchers have been able to monitor and track the prices of groceries across different regions in Canada. By scraping data from online grocery platforms, e-commerce websites, and official government sources, they have gathered comprehensive information on price fluctuations over time.

The findings of these web scraping efforts have indicated a notable inflationary trend in the grocery sector. Key food staples such as fruits, vegetables, dairy products, and meat have experienced consistent price increases, impacting household budgets and consumer purchasing power.

By scraping and analyzing large volumes of data, experts can identify patterns, trends, and regional variations in grocery prices. This information is invaluable for policymakers, economists, and consumers alike, providing them with a better understanding of the economic landscape and the impact of inflation on daily expenses.

Web scraping continues to be a valuable tool in shedding light on important economic indicators such as the rising cost of groceries. Its ability to collect real-time data from multiple sources enables researchers to uncover valuable insights and inform decision-making processes. As the cost of living remains a crucial concern for many Canadians, web scraping will continue to play a pivotal role in monitoring and understanding economic fluctuations.

Loblaws, one of Canada's major grocery retailers, has come under scrutiny due to significantly higher prices for chicken breast compared to its competitors. Recent observations have revealed that Loblaws is charging nearly $40 Canadian for a pack of chicken breast, sparking controversy and public outcry.

One may think that was the pricing mistake although the pricing was certainly correct:

In this blog post, we delve into the realm of grocery prices in Canada, utilizing the power of web scraping to uncover valuable insights regarding the extent of grocery and food inflation. By leveraging web scraping techniques, we gain access to real-time data from various sources, enabling us to analyze and understand the changing landscape of grocery prices in the country.

Unveiling Inflation Trends with Actowiz Solutions: A Web Scraping Solution

Actowiz Solutions provides a powerful web scraping tool that enables businesses to reveal inflation trends and gain deeper insights into consumer behaviors and market volatility. By utilizing our web scraping capabilities, we can extract data from various websites, particularly grocery store sites, to analyze product prices across Canada and identify patterns in the cost of groceries, thus shedding light on inflation rates.

Our free web scraping tool, Actowiz Solutions, can aggregate data from multiple sources, such as supermarkets. This data can be exported on a scheduled basis to formats like JSON or CSV files or accessed through our API for further analysis. Many companies leverage Actowiz Solutions for price monitoring, allowing them to uncover discoveries such as average cost inflations on different food products or regional discrepancies in price hikes.

With comprehensive data related to food pricing obtained through web scraping, shoppers are empowered to make more informed decisions. At the same time, policymakers can develop targeted measures to address inflationary issues at their core. For instance, in a previous piece, we explored the concept of the Pink Tax, highlighting how female products often come with a higher price tag than their male counterparts.

With Actowiz Solutions' web scraping capabilities, businesses can harness big data related to food pricing and gain valuable insights. By staying informed about inflation trends, businesses, and consumers can adapt their strategies and make informed decisions that positively impact their bottom line.

Average Food and Grocery Prices from 2015 to 2023: A Glance at Inflation Trends

Over the years, the average prices of particular food and grocery items in Canada have experienced fluctuations, providing insights into inflation trends. Let's take a closer look at the price ranges observed from 2015 to 2023:

Milk (4L): The average price of a 4-liter container of milk has increased from around $5.52 to over $6.63 during this period, highlighting the impact of inflation on dairy products.

Bananas: The price of bananas has remained relatively stable throughout this period, indicating a more consistent pricing trend for this popular fruit.

Steak (1kg): The average price of a 1-kilogram steak has witnessed an upward trend, rising from approximately $24.74 to over $27.49. This signifies inflationary pressures on meat products, particularly steak.

Eggs (Dozen): The average price of a dozen eggs has also experienced a moderate increase, going from around $3.33 to over $3.87. This reflects the impact of inflation on essential protein sources like eggs.

These figures are a snapshot of the average prices of select food and grocery items over the given timeframe. It's important to note that prices can vary across regions and individual stores and may be influenced by factors such as supply and demand dynamics, production costs, and economic conditions.

By monitoring and analyzing such data, businesses, and consumers can gain valuable insights into inflation trends and adjust their strategies, whether budgeting for household expenses or making pricing decisions in the retail industry.

Based on data from Trading Economics, the cost of food and non-alcoholic beverages in Canada saw a 9.7% increase in February 2023. This growth rate was slightly lower than the 10.4% increase observed in the previous month.

The rise in the cost of food and non-alcoholic beverages indicates the presence of inflationary pressures within this sector. Factors such as supply chain disruptions, changes in commodity prices, and shifts in consumer demand can contribute to these price increases.

Monitoring these inflation trends is crucial for individuals, businesses, and policymakers to make informed decisions and adapt their strategies accordingly. By staying abreast of these changes, stakeholders can navigate the evolving economic landscape and mitigate the potential impact on their budgets, pricing strategies, and overall financial well-being.

Driving Factors behind Grocery Inflation in Canada

Several factors are driving the inflation of grocery prices in Canada, resulting in increased consumer costs. These factors include:

Global supply chain disruptions: Disruptions in global supply chains, including transportation delays and shortages of raw materials, have impacted the availability and cost of grocery items. These disruptions can be attributed to various factors, such as trade disputes, natural disasters, and the ongoing effects of the COVID-19 pandemic.

Labor shortages: Labor shortages within the agricultural and food processing sectors have increased production costs. The scarcity of skilled and seasonal laborers has affected farming operations, resulting in reduced yields and higher labor expenses passed on to consumers.

Climate change and agricultural challenges: Climate change-related events, such as extreme weather conditions, droughts, and floods, have adversely affected agricultural production. Crop failures, reduced yields, and increased irrigation and pest control costs contribute to higher prices for agricultural products.

Impact of the COVID-19 pandemic: The pandemic has disrupted global food production and distribution systems, leading to increased costs at various supply chain stages. Restrictions on travel, social distancing measures, and labor force disruptions have affected food processing, transportation, and retail operations.

Consumers have expressed concerns about supermarkets potentially engaging in price-gouging practices, where prices are unjustifiably inflated. However, existing laws and regulations are in place to prevent such practices.

Web scraping, coupled with data analysis from sources like Statistics Canada, provides a means to track and monitor price fluctuations in the grocery sector. By comparing current prices to historical trends, stakeholders can gain insights into the drivers of grocery inflation and make informed decisions to mitigate the impact on consumers.

By understanding these factors and actively monitoring price changes, individuals and policymakers can take preventive measures to address issues related to grocery inflation and work towards more stable and affordable food prices for Canadians.

Addressing Grocery Inflation in Canada: Potential Solutions and the Role of Technology

The rising cost of groceries in Canada has become a pressing concern for households nationwide. To tackle this issue, it is crucial to explore potential solutions and harness the power of modern technology. In particular, integrating artificial intelligence (AI) and machine learning algorithms, along with web scraping and data harvesting techniques, offers promising avenues for mitigating the effects of grocery inflation.

By leveraging AI and machine learning, retailers and suppliers can optimize their supply chain management and streamline logistics processes. These advanced technologies can analyze vast amounts of data, including historical pricing trends, consumer preferences, and market demand, to make informed decisions and enhance efficiency. By identifying inefficiencies and reducing waste throughout the supply chain, these technologies reduce costs and ultimately lower consumer prices.

Web scraping and data harvesting play a vital role in monitoring the effectiveness of AI and machine learning algorithms. By extracting data from various sources, such as supermarket websites, digital flyers, and statistical platforms, valuable insights can be gained regarding pricing fluctuations and trends. Web scraping enables the collection and analysis of data over time, providing governments and corporations with a comprehensive view of the impact of different strategies on curbing inflation. This information empowers decision-makers to make informed policies and pricing decisions that benefit society.

The integration of technology offers potential solutions for addressing grocery inflation and opens up opportunities for innovation and collaboration within the industry. By fostering partnerships between retailers, suppliers, and technology providers, a collaborative ecosystem can be established to tackle the challenges posed by rising grocery prices. Through shared data and insights, stakeholders can work together to optimize processes, negotiate fair pricing, and ensure the availability of affordable and quality food products for consumers.

Conclusion

In conclusion, the issue of Canadian grocery inflation poses significant challenges for households across the country. However, with web scraping and other technological advancements, there is potential for gaining valuable insights, identifying root causes, and seeking viable solutions. By leveraging these technologies, we can enhance our understanding of the factors driving inflation and explore innovative food production and supply chain management methods to mitigate its impact on consumers.

Staying informed about price trends and adapting shopping habits can empower Canadian consumers to navigate the challenging financial landscape caused by grocery inflation. Digital flyer apps like Flipp are convenient for finding good bargains and making cost-effective purchasing decisions. By leveraging web scraping, data analytics, and statistics, we can continuously monitor the fluctuating costs of groceries in Canada and globally. This ongoing monitoring allows for proactive collaboration among stakeholders to address rising food costs before they become unaffordable for consumers.

Combating grocery inflation requires a collective effort from policymakers, retailers, suppliers, and consumers. By harnessing the power of technology, we can continue to track and analyze data, identify trends, and implement measures to alleviate the impact of rising prices. Through these combined efforts, we can strive to ensure the availability of affordable and high-quality food for all Canadians.

As the landscape evolves, it is essential to remain vigilant and adaptable. We can make informed decisions and work collaboratively towards long-term solutions by embracing web scraping and data-driven insights. Together, we can address the challenges posed by grocery inflation and create a more sustainable and affordable food ecosystem for the benefit of all.

For additional information and assistance, please don't hesitate to reach out to Actowiz Solutions. We are here to provide comprehensive support for your mobile app scraping, web scraping, or instant data scraper service needs. Our team of experts is well-equipped to guide you through the process, answer your questions, and offer tailored solutions that align with your specific requirements. Contact us today to explore how Actowiz Solutions can help you harness the power of web scraping and data extraction for your business.

GeoIp2\Model\City Object
(
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                                    [pt-BR] => Ohio
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                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
        (
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    [country:protected] => GeoIp2\Record\Country Object
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    [locales:protected] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [validAttributes:protected] => Array
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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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            [validAttributes:protected] => Array
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.24
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)

 country : United States

 city : Columbus

US

Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

Start Your Project

+1 ▼

Select Service Web Scraping Real-Time API Access Data Dashboards Datasets Review & Sentiment Analysis Price Monitoring Custom Solution

Select Industry E-Commerce Quick Commerce Food Delivery Travel & OTA Grocery & Retail Real Estate Others

Target Country Web Scraping Services Mobile App Scraping Web and App Scraping API Datasets Dashboard

A$лвR$C$CHF¥Kčkr€£HK$FtRp₪₹kr¥₩Mex$RMkrNZ$₱złleikrS$฿₺$R Budget Range $500 - $1,000 - Starter Budget (POC/Single Site) $1,000 - $2,500 - Basic Plan (Small Business Needs) $2,500 - $5,000 - Growth Phase (Multi-site/Data Volume Projects) $5,000 - $10,000 - Business-Scale (Automation/API Integrations) $10,000 - $25,000 - Enterprise Projects (Real-Time Systems, Global Data) $25,000 - $50,000 - Enterprise+ (Custom Dashboards, Ongoing Support) $50,000+ - Strategic Partnership (End-to-End Data Ops)

Additional Trust Elements

✨ "1000+ Projects Delivered Globally"

⭐ "Rated 4.9/5 on Google & G2"

🔒 "Your data is secure with us. NDA available."

💬 "Average Response Time: Under 12 hours"

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 Galido

Co-Founder / Head of Product at Upright Data Inc.

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.”

Iulen Ibanez

CEO / Datacy.es

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!”

Febbin Chacko

-Fin, Small Business Owner

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

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

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How to Scrape The Whisky Exchange UK Discount Data to Track 95% of Real-Time Whiskey Deals Efficiently?

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Oct 25, 2025

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Oct 24, 2025

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Read More

How Automated Data Extraction from Sainsbury’s for Stock Monitoring Improved Product Availability & Supply Chain Efficiency

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How Scraping Wayfair Data for Price Intelligence and Savings Analysis Helped Retailers Achieve 12–25% Cost Savings

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How to Scrape Popular Halloween Product Data Across USA & UK Markets to Optimize Sales Strategies

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Read More

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

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Top 5 Brands Offering Deepest Discounts on Clothes This Navratri

Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.

Top 10 Most Ordered Grocery Items During Navratri 2025

Discover the top 10 most ordered grocery items during Navratri 2025. Explore popular festive essentials for fasting, cooking, and celebrations.

Read More

Maximizing Margins - Scraping Online Liquor Stores for Competitor Price Intelligence to Monitor Competitor Pricing in the Online Liquor Market

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Real-Time Price Monitoring and Trend Analysis of Amazon and Walmart Using Web Scraping Techniques

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Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.

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Our team focuses on clear, transparent communication to ensure that every project is aligned with your goals and that you’re always informed of progress.

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Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations

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