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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] => 216.73.216.165
                    [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] => 216.73.216.165
                    [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
)
Weekly E-commerce Price Comparison in Amazon India - Trends & Insights-01

Introduction

In today's hyper-competitive quick commerce landscape, real-time grocery price monitoring has become essential for retailers, analysts, and pricing strategists. Platforms like Zepto, Blinkit, Swiggy Instamart, and BigBasket are transforming consumer expectations through instant delivery, competitive pricing, and inventory agility. However, these rapid shifts make it challenging for businesses to manually track and compare thousands of grocery SKUs across multiple platforms.

The Real-Time Zepto Data Scraping API by Actowiz Solutions bridges this gap by offering automated, real-time data collection and analysis. This API enables enterprises to gather comprehensive pricing, discount, and product information at scale — with 95% faster data extraction and 80% greater accuracy than manual or semi-automated methods. As the demand for price intelligence and digital retail analytics continues to rise, companies are increasingly turning to automated APIs to power real-time competitive insights and smarter pricing decisions.

Between 2020 and 2025, the quick commerce market is projected to grow at a CAGR of 28%, highlighting the urgent need for scalable, data-driven decision-making tools. The Real-Time Zepto Data Scraping API empowers businesses to stay agile, accurate, and competitive in this dynamic retail environment.

Why Real-Time Grocery Price Tracking Matters in Quick Commerce (2020–2025 Trends)

In the rapidly evolving quick commerce ecosystem, understanding and tracking grocery prices in real-time is no longer optional—it is critical for businesses aiming to stay competitive. Platforms like Zepto, Blinkit, Swiggy Instamart, and BigBasket have reshaped consumer expectations, offering near-instant delivery, a vast product selection, and highly dynamic pricing strategies. The rapid pace of price fluctuations and promotional campaigns in quick commerce makes manual tracking inefficient and prone to errors, which can lead to lost revenue, missed opportunities, and reduced market share.

The Real-Time Zepto Data Scraping API allows businesses to automate the collection of price data across thousands of SKUs in real-time. This ensures enterprises have up-to-date information on competitor pricing, seasonal promotions, and inventory levels. Between 2020 and 2025, online grocery shopping frequency increased by over 120%, and the average delivery time for quick commerce platforms decreased from 45 minutes in 2020 to under 15 minutes in 2025, demonstrating the speed and scale at which retailers need to operate.

Real-time price tracking is not only about monitoring competitors—it also enables smarter pricing strategies, targeted discount campaigns, and proactive inventory management. Businesses leveraging automated APIs can react instantly to market changes, maintaining profitability while optimizing customer satisfaction.

The following table illustrates trends in grocery pricing and quick commerce adoption over the past five years:

Year Avg. Grocery Price Changes/Month Quick Commerce Adoption (%) Avg. Delivery Time (min) Promotional Campaigns/Month
2020 15 32% 45 3
2021 28 45% 35 5
2022 40 58% 25 7
2023 52 71% 18 10
2024 60 83% 15 12
2025* 75 92% 12 15

By leveraging the Real-Time Zepto Data Scraping API, businesses can track not only pricing but also the frequency of promotions, ensuring optimal pricing adjustments. The data shows that as quick commerce adoption rises, so does the volatility in pricing and promotions, making automated monitoring a critical capability.

Furthermore, real-time tracking enables companies to identify patterns and forecast trends for future product launches or price adjustments. For example, between 2020 and 2025, the number of products with dynamic pricing grew by 65%, highlighting how critical real-time data is for decision-making. Businesses without real-time monitoring risk losing competitive advantage, while those using Real-Time Zepto Data Scraping API can maintain market leadership.

In conclusion, the combination of rapid market growth, increasing frequency of price adjustments, and rising consumer expectations makes real-time grocery price tracking essential. With the right API-driven tools, businesses can optimize pricing strategies, benchmark competitors effectively, and respond instantly to market shifts. The 2020–2025 trends clearly indicate that automated real-time pricing insights are no longer a luxury—they are a necessity.

How API-Based Zepto Data Extraction for Analytics Improves Decision-Making?

In today's competitive quick commerce sector, data-driven decisions are crucial for maximizing profitability and operational efficiency. The API-based Zepto data extraction for analytics empowers enterprises to gather structured product, pricing, and inventory data from Zepto and integrate it seamlessly into analytics tools. Unlike manual data collection, API-based extraction ensures data accuracy, minimizes human error, and allows businesses to scale analytics across thousands of SKUs and multiple competitors.

Between 2020 and 2025, companies adopting API-driven data analytics in grocery retail have seen adoption grow by 170%, while manual data processing times have decreased by over 70%. The insights generated help businesses identify pricing gaps, monitor competitor promotions, and optimize stock levels, enabling faster and more informed decisions.

Metric 2020 2021 2022 2023 2024 2025 (Projected)
Data-Driven Pricing Adoption (%) 18 25 33 41 46 49
Manual Data Processing Time (hrs/week) 22 19 15 12 8 6
Forecast Accuracy (%) 62 68 74 80 85 88
SKU Coverage (thousands) 8 12 17 22 28 35

The Real-Time Zepto Data Scraping API also ensures continuous updates, feeding fresh data into dashboards and predictive models. By automating collection, integration, and cleaning, businesses can achieve insights faster, reducing time-to-decision by up to 50%. API-based extraction enables better competitive benchmarking by providing consistent, reliable datasets for comparisons.

Moreover, these analytics help companies identify emerging trends in consumer preferences, promotional campaigns, and regional pricing variations. Retailers can leverage these insights to improve pricing strategies, plan inventory allocations, and enhance market responsiveness.

In conclusion, adopting API-based Zepto data extraction for analytics equips businesses with real-time insights, improves decision-making, and allows faster action in a fast-paced quick commerce ecosystem. By integrating Zepto data into their analytics pipelines, companies achieve higher efficiency, better forecasting, and improved competitiveness.

Unlock smarter decisions with API-based Zepto data extraction for analytics — boost accuracy, speed, and competitive insights today!
Contact Us Today!

What Benefits Come from Real-Time Zepto Pricing API Integration?

The Real-time Zepto pricing API integration allows companies to embed real-time pricing data directly into their internal systems such as ERP, CRM, and eCommerce platforms. This ensures pricing decisions are based on the most current market conditions. Traditional manual updates are slow and prone to error, leading to missed opportunities, lost sales, and decreased margins.

Adoption of real-time pricing API integrations has grown significantly from 2020 to 2025, with companies reporting up to 45% faster decision-making and a 33% improvement in pricing margin efficiency. With real-time access to Zepto data, businesses can quickly adjust product pricing to match market trends, competitive promotions, and inventory availability.

Integration KPI 2020 2021 2022 2023 2024 2025 (Projected)
Real-Time Pricing Sync Accuracy (%) 68 75 82 88 91 93
Manual Update Lag (hrs) 18 14 10 6 3 2
Pricing Margin Efficiency (%) 71 76 81 86 90 94
Products Monitored (thousands) 5 9 14 20 25 32

The API ensures that businesses always operate with the most accurate data available, eliminating errors and reducing operational bottlenecks. Real-time integration also improves forecasting, inventory management, and promotional planning by allowing predictive algorithms to run on current datasets rather than historical data.

Furthermore, seamless API integration enhances competitive benchmarking, enabling companies to monitor competitors' pricing strategies and respond instantly. This agility allows companies to maintain their market position and ensure their offerings remain attractive to customers.

Ultimately, Real-time Zepto pricing API integration drives efficiency, profitability, and competitiveness, giving businesses the tools to act instantly in a dynamic, fast-moving market.

How Zepto API for Real-Time Grocery Price Comparison Drives Market Advantage?

The Zepto API for real-time grocery price comparison provides businesses with a detailed, instant view of competitor prices across multiple quick commerce platforms. By using this API, companies can benchmark their pricing strategies against Zepto, Blinkit, Swiggy Instamart, and BigBasket, identifying gaps and opportunities for improvement.

From 2020 to 2025, the adoption of competitive pricing comparison APIs increased from 22% to 67%, reflecting the growing importance of real-time intelligence in the grocery market. Instant insights into competitor pricing help businesses implement dynamic promotions, adjust discounts, and optimize inventory turnover.

Year API Usage in Price Comparison (%) Avg. Competitive Accuracy (%) Price Update Frequency (per day)
2020 22 65 2
2021 31 72 3
2022 39 78 4
2023 49 85 6
2024 58 89 8
2025* 67 94 10

By leveraging Zepto API for real-time grocery price comparison, retailers gain actionable intelligence to maintain competitive pricing, attract more customers, and increase revenue. The API also facilitates dynamic price monitoring, ensuring businesses can adjust strategies immediately in response to market shifts.

Real-time comparison also enables better inventory planning by identifying high-demand products and adjusting stock levels accordingly. The API's integration into analytics and BI platforms ensures that data-driven insights are easily accessible and actionable, enhancing strategic decision-making.

How Does Web Scraping API for Zepto Price Insights Support Retail Intelligence?

The Web scraping API for Zepto price insights allows companies to collect comprehensive, structured pricing and product data for analysis. Unlike manual scraping, which is slow and prone to errors, this API ensures accurate and scalable data collection for thousands of SKUs across multiple regions.

Predictive pricing and inventory planning are key benefits. Between 2020 and 2025, predictive analytics adoption in quick commerce increased by 190%, demonstrating the critical role of automated data acquisition in operational decision-making.

Insight Metric 2020 2021 2022 2023 2024 2025 (Projected)
Predictive Pricing Adoption (%) 21 28 36 44 53 61
Forecast Accuracy (%) 70 74 79 84 88 92
Inventory Optimization Efficiency (%) 56 63 70 75 79 83
Products Monitored (thousands) 6 10 15 21 27 33

By integrating the Web scraping API for Zepto price insights into analytics workflows, retailers gain the ability to forecast pricing trends, optimize inventory, and respond proactively to competitor moves.

The API also enhances competitive benchmarking by providing a clear picture of market pricing dynamics, enabling faster and smarter decisions. Businesses that adopt such advanced scraping tools maintain a competitive advantage, reduce operational costs, and improve customer satisfaction.

Leverage the Web Scraping API for Zepto price insights to gain real-time retail intelligence and make data-driven pricing decisions today!
Contact Us Today!

Why Choose Zepto Competitor Price Monitoring API for Real-Time Market Intelligence?

The Zepto competitor price monitoring API delivers accurate, real-time information about competitor pricing, discounts, and product availability. By automating this process, companies reduce the risk of missed opportunities and enhance pricing strategy execution.

Between 2020 and 2025, the use of automated price monitoring solutions increased by 210%, highlighting its significance in maintaining competitiveness in quick commerce. Companies leveraging this API report faster response times to price changes and improved profit margins.

KPI 2020 2021 2022 2023 2024 2025 (Projected)
Automated Price Monitoring Users 420 600 850 1,050 1,200 1,300
Avg. Response Time to Price Change (hrs) 12 9 6 3 2 1.5
Profit Margin Stability (%) 68 73 78 84 87 90
Competitor SKUs Monitored (thousands) 5 8 13 19 24 30

The Zepto competitor price monitoring API ensures businesses can respond immediately to competitor actions, adjust promotions dynamically, and maintain pricing leadership across multiple platforms.

How Does Zepto API for Dynamic Price Monitoring Power the Future of Quick Commerce?

The Zepto API for dynamic price monitoring allows businesses to automatically adjust product prices based on demand, competitor pricing, and promotional trends. Dynamic pricing is essential for optimizing margins and staying competitive in fast-moving markets.

From 2020 to 2025, companies implementing dynamic pricing strategies have seen 35% higher conversion rates and 22% revenue growth.

Metric 2020 2021 2022 2023 2024 2025 (Projected)
Dynamic Pricing Adoption (%) 19 28 40 51 58 64
Revenue Growth via Dynamic Pricing (%) 9 12 15 18 20 22
Conversion Rate Increase (%) 12 18 24 29 32 35
SKUs Monitored for Dynamic Pricing (thousands) 4 8 14 21 27 33

The Zepto API for dynamic price monitoring enables companies to proactively adjust pricing strategies in real-time, optimize customer value, and maximize profitability. Integration with analytics platforms allows businesses to track performance metrics and refine algorithms for future success.

How Actowiz Solutions Can Help?

Actowiz Solutions is a trusted leader in Quick Commerce Data Scraping Services and Web Scraping Services. Our Zepto Grocery Data Scraping API and Web Scraping API deliver highly accurate, structured, and real-time data directly to your preferred analytics tools or internal databases. By leveraging advanced extraction frameworks, we help businesses Extract Real-Time Zepto Data for Pricing Monitoring, ensuring agility and market competitiveness.

Our data delivery ecosystem supports scalable integrations, automated updates, and secure API-based access, empowering teams with Competitive Benchmarking insights across multiple platforms. Whether you're a retailer, data analyst, or enterprise brand, Actowiz Solutions helps you unlock smarter decision-making and superior market positioning.

Conclusion

The grocery retail and quick commerce sectors are evolving faster than ever. Staying competitive requires access to real-time, high-quality pricing data — something traditional methods can’t provide. The Real-Time Zepto Data Scraping API by Actowiz Solutions empowers businesses to analyze live pricing data 95% faster and 80% more accurately, enabling informed decisions, improved margins, and stronger customer engagement.

With a suite of specialized APIs for Zepto and other quick commerce platforms, Actowiz Solutions ensures your business remains future-ready.

Contact Actowiz Solutions today to schedule a demo or discuss custom API solutions that bring precision, scalability, and speed to your pricing intelligence strategy!

You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper 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] => 216.73.216.165
                    [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] => 216.73.216.165
                    [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

2x Faster

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

★★★★★

“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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Real results from real businesses using Actowiz Solutions

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Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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Iulen Ibanez
CEO / Datacy.es
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Febbin Chacko
-Fin, Small Business Owner
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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

Actowiz Insights Hub

Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

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Case Studies
Infographics
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Nov 05, 2025

How Real-Time Zepto Data Scraping API (95% Faster & 80% More Accurate) Helps Compare Grocery Prices Across Quick Commerce Platforms?

Compare grocery prices 95% faster and 80% more accurately using the Real-Time Zepto Data Scraping API for instant insights across quick commerce platforms.

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D2C Beauty Brand: Price & Discount Tracking on Nykaa and Amazon | Case Study by Actowiz Solutions

See how Actowiz Solutions helped a D2C beauty brand monitor 15K SKUs across Nykaa, Amazon & Myntra, boosting festive ROI by 36% with price intelligence.

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Adidas Price Discounts Analysis 2025 - Global Black Friday Trends and Consumer Insights from Data Scraping

Explore the Adidas Price Discounts Analysis 2025, uncovering global Black Friday trends, price fluctuations, and consumer insights through advanced data scraping techniques.

Nov 05, 2025

How Real-Time Zepto Data Scraping API (95% Faster & 80% More Accurate) Helps Compare Grocery Prices Across Quick Commerce Platforms?

Compare grocery prices 95% faster and 80% more accurately using the Real-Time Zepto Data Scraping API for instant insights across quick commerce platforms.

Nov 04, 2025

Real-Time Price Scraping to Track Black Friday Deals on Amazon, Walmart & Target

Discover how Real-Time Price Scraping to Track Black Friday Deals on Amazon, Walmart & Target helps shoppers monitor discounts, compare prices, and maximize savings.

Nov 03, 2025

How Zepto Product Dataset for Q-Commerce Market Reveals Trends and 40% Increase in Product Listings Across India?

Discover how Zepto Product Dataset for Q-Commerce Market reveals trends and a 40% increase in product listings, highlighting India’s evolving quick commerce landscape.

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D2C Beauty Brand: Price & Discount Tracking on Nykaa and Amazon | Case Study by Actowiz Solutions

See how Actowiz Solutions helped a D2C beauty brand monitor 15K SKUs across Nykaa, Amazon & Myntra, boosting festive ROI by 36% with price intelligence.

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Tracking Product Availability & Price Drops on Black Friday 2025 Across E-Commerce Platforms

Monitor product availability and price drops on Black Friday 2025 with real-time insights, helping retailers optimize inventory, pricing, and maximize sales effectively.

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Scraping Zepto Grocery Data for Price Comparison to Power Real-Time Meal Planning Insights

Discover how Scraping Zepto Grocery Data for Price Comparison helped a meal planning app automate real-time pricing insights, optimize budgets, and enhance user experience.

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Adidas Price Discounts Analysis 2025 - Global Black Friday Trends and Consumer Insights from Data Scraping

Explore the Adidas Price Discounts Analysis 2025, uncovering global Black Friday trends, price fluctuations, and consumer insights through advanced data scraping techniques.

thumb

Real-Time API Scraping from Myntra, Ajio & Nykaa to Track Fashion Trends and Pricing

Discover how Real-Time API Scraping from Myntra, Ajio & Nykaa provides actionable insights to track fashion trends, pricing, and market intelligence effectively.

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Real-Time Electronics Price Tracking for Black Friday - Insights from 2025 Sales Trends and Consumer Behavior

Discover Real-Time Electronics Price Tracking for Black Friday 2025, revealing sales trends, discounts, and consumer behavior insights for smarter retail decisions.

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