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GeoIp2\Model\City Object
(
    [raw:protected] => Array
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            [city] => Array
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                    [geoname_id] => 4509177
                    [names] => Array
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                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [continent] => Array
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                    [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
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            [country] => Array
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                    [iso_code] => US
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [location] => Array
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                    [longitude] => -83.0061
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            [postal] => Array
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            [registered_country] => Array
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [subdivisions] => Array
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                            [iso_code] => OH
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                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [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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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [names] => Array
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                            [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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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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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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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
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                            [en] => United States
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                            [fr] => États Unis
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                            [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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                    [3] => isoCode
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        )

    [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
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            [validAttributes:protected] => Array
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                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
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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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                    [0] => en
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            [validAttributes:protected] => Array
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                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.58
                    [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
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                )

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

Introduction

Halloween has become one of the most significant seasonal events for the food delivery industry. Restaurants and delivery platforms leverage themed menus, limited-time desserts, and festive promotions to boost engagement and revenue. With consumers increasingly ordering through apps, monitoring trends on top platforms provides critical competitive intelligence. By Scraping Food Delivery Apps for Halloween Menu Trends, businesses can analyze menu launches, track popularity, forecast demand, and optimize operational decisions across key apps.

Between 2020 and 2025, Halloween-themed orders on top delivery apps grew by approximately 220%, with items like pumpkin spice desserts, ghost-shaped pastries, and themed beverages becoming highly popular. Real-time data extraction enables restaurants to respond rapidly to emerging trends, optimize pricing, and manage inventory effectively. Actowiz Solutions provides structured datasets, integrating menu data, consumer ratings, pricing, and order volumes, empowering businesses to make informed, strategic decisions during high-demand seasonal periods.

The following sections dive into detailed insights from the top 5 food delivery apps, analyzing Halloween menu trends, pricing, popularity, and delivery performance, with realistic fictional statistics from 2020–2025.

DoorDash – Menu Launches & SKU Analysis

DoorDash has grown into a dominant platform in the UAE for seasonal food offerings, particularly during Halloween. Between 2020 and 2025, Halloween-themed menu launches increased steadily as restaurants recognized the marketing potential of limited-time festive items. By Scrape Seasonal Halloween Menus from Food Delivery Apps, restaurants can monitor which SKUs are introduced, their pricing, and initial reception by consumers.

For instance, pumpkin spice desserts, ghost-shaped pastries, and monster-themed milkshakes emerged as high-demand items. The rise in menu launches indicates restaurants’ willingness to experiment with themed offerings to capture attention during the Halloween season.

Year	Halloween Menus Launched	Avg. Menu Item Price (AED)	Top-Selling SKU
2020	12	42.0	Pumpkin Pie
2021	16	44.0	Ghost Cupcakes
2022	18	45.0	Spider Donuts
2023	22	47.0	Monster Milkshake
2024	26	50.0	Vampire Brownies
2025	30	52.0	Pumpkin Spice Latte

DoorDash also saw an increase in the number of restaurants participating in Halloween menus, growing from 45 outlets in 2020 to 120 in 2025. Real-time monitoring allows restaurants to adjust offerings, price points, and promotions based on competitor activity and SKU performance.

Actowiz leverages Food Delivery Data Scraping Services to collect structured datasets on DoorDash’s menu launches, order trends, and SKU performance. By combining historical and real-time data, operators can forecast demand, manage inventory efficiently, and optimize menu planning. Data insights enable businesses to detect which seasonal SKUs are likely to become top sellers, identify underperforming items early, and create targeted promotions to increase customer engagement.

Moreover, analyzing DoorDash’s Halloween menus offers insights into regional preferences, flavor trends, and category performance, which can inform broader strategic decisions. By tracking SKU launches across multiple years, restaurants can determine which items retain popularity and plan future seasonal offerings more effectively.

Grubhub – Customer Reviews & Ratings

Consumer feedback plays a critical role in the success of seasonal menu items. By Tracking Halloween-Themed Food Trends via Web Scraping, restaurants can extract reviews, ratings, and comments from Grubhub to identify top-performing dishes and areas for improvement.

Between 2020 and 2025, Halloween-themed menu items on Grubhub showed a steady rise in average ratings, reflecting growing consumer appreciation for creative seasonal offerings. Desserts and beverages typically received the highest ratings, while main courses saw moderate engagement.

Year	Avg. Customer Rating	% 5-Star Reviews	Most Reviewed Item
2020	4.1	32%	Pumpkin Pie
2021	4.2	35%	Ghost Cupcakes
2022	4.3	37%	Spider Donuts
2023	4.4	40%	Monster Milkshake
2024	4.5	43%	Vampire Brownies
2025	4.6	46%	Pumpkin Spice Latte

By analyzing these trends, restaurants can refine recipes, introduce complementary items, and phase out low-rated dishes. Seasonal menus with consistently high ratings generate repeat orders, increase brand loyalty, and enhance promotional effectiveness.

Actowiz’s Food Delivery Data Intelligence service provides structured review datasets, combining ratings, sentiments, and review volume. By correlating ratings with sales data, operators can identify high-performing SKUs early, predict potential inventory shortages, and adjust marketing campaigns accordingly.

Furthermore, understanding customer preferences by demographic, location, or order timing allows restaurants to optimize menus for specific regions or delivery windows. This data-driven approach ensures seasonal menu success and maximizes revenue potential.

Deliveroo – Pricing & Promotions Analysis

Deliveroo serves as a key platform for seasonal promotions. By Extract Halloween Menu Data for Seasonal Food Analysis, restaurants can track pricing trends, discounts, and promotional campaigns to maximize revenue.

Year	Avg. Price (AED)	Avg. Discount (%)	Top Promo Item
2020	44.0	10	Pumpkin Pie
2021	46.0	12	Ghost Cupcakes
2022	48.0	11	Spider Donuts
2023	51.0	13	Monster Milkshake
2024	53.0	14	Vampire Brownies
2025	56.0	15	Pumpkin Spice Latte

Price adjustments over time indicate both increasing demand and ingredient costs. Restaurants can identify optimal pricing, plan promotions, and maintain competitiveness during peak seasonal periods.

Actowiz’s Web Scraping Halloween Food Trend Data provides historical and real-time insights on price fluctuations and promotion effectiveness. Analyzing promotional response helps operators decide which discounts maximize sales and minimize profit loss.

Additionally, tracking competitor pricing across Deliveroo enables dynamic pricing strategies, ensuring menus remain attractive without undercutting profitability. Seasonal analytics help restaurants design targeted campaigns, bundle offerings, and align pricing with demand forecasts.

Careem NOW – Delivery & Fulfillment Insights

Efficient delivery performance is crucial for customer satisfaction, particularly for seasonal offerings. By Real-TimeRestaurant Data for Seasonal Menu Tracking, Careem NOW insights allow restaurants to monitor fulfillment rates, delivery times, and regional performance.

Year	Avg. Delivery Time (hrs)	Fulfillment Rate (%)
2020	11.5	82
2021	10.0	85
2022	8.5	88
2023	6.5	91
2024	5.0	94
2025	3.8	96

Actowiz’s Scraping Halloween-Themed Menus from Food Delivery Apps collects real-time data to assess order fulfillment trends. Faster delivery correlates with higher repeat orders, better ratings, and increased promotional effectiveness.

Monitoring regional delivery variations ensures restaurants allocate resources efficiently, reducing delays and improving the customer experience. Insights on peak ordering hours and fulfillment bottlenecks allow proactive adjustments, minimizing late deliveries during high-demand periods like Halloween.

Uber Eats – Menu Category & Popularity Trends

Understanding category-wise popularity is critical for inventory and menu planning. By Scraping Food Delivery Apps for Halloween Menu Trends, restaurants can track which categories dominate orders, such as desserts, beverages, or snacks.

Year	Desserts (%)	Beverages (%)	Snacks (%)	Main Dishes (%)
2020	42	18	25	15
2021	44	19	23	14
2022	46	18	22	14
2023	48	17	22	13
2024	50	16	20	14
2025	52	15	18	15

Desserts consistently lead Halloween orders. Actowiz solutions provide Food Delivery Datasets to extract top-selling items, monitor category trends, and inform inventory decisions.

Restaurants can use these insights to adjust menu focus, manage ingredient procurement, and design seasonal promotions aligned with consumer demand.

Predictive Analytics for Upcoming Halloween Seasons

Predicting high-demand items helps restaurants prepare efficiently. Using Web Scraping API Services, Actowiz generates forecasts based on historical trends from all top 5 apps.

Year	Predicted Top Item	Forecast Accuracy (%)
2020	Pumpkin Pie	88
2021	Ghost Cupcakes	90
2022	Spider Donuts	91
2023	Monster Milkshake	92
2024	Vampire Brownies	93
2025	Pumpkin Spice Latte	94

Predictive models combine order history, ratings, pricing, and category performance to guide stocking, promotions, and marketing campaigns. Restaurants can reduce waste, maximize revenue, and capitalize on emerging trends with high confidence.

How Actowiz Solutions Can Help?

Actowiz Solutions enables restaurants and delivery platforms to gain deep insights by Scraping Food Delivery Apps for Halloween Menu Trends. By collecting structured datasets on menu launches, pricing, customer reviews, category popularity, and order volumes, businesses can optimize inventory, promotions, and menu design for peak seasonal periods.

With Food Delivery Data Scraping Services and Food Delivery Data Intelligence, Actowiz provides historical and real-time data to forecast demand, benchmark competitors, and improve operational efficiency. Predictive analytics allows restaurants to anticipate trends, stock top-performing items, and maximize revenue while reducing waste.

Actowiz solutions integrate multiple delivery platforms, ensuring a holistic view across DoorDash, Grubhub, Deliveroo, Careem NOW, and Uber Eats. This comprehensive approach empowers decision-makers to respond quickly to market shifts, design effective promotions, and maintain a competitive advantage in the seasonal food delivery market.

Conclusion

Halloween offers a unique opportunity to drive sales and customer engagement in food delivery. By Scraping Food Delivery Apps for Halloween Menu Trends, restaurants gain actionable insights into menu launches, pricing, ratings, and category popularity across the top 5 platforms.

Insights from Scrape Seasonal Halloween Menus from Food Delivery Apps and Tracking Halloween-Themed Food Trends via Web Scraping help businesses optimize inventory, tailor promotions, and forecast demand for high-performing seasonal items. Real-time data monitoring ensures operational efficiency and customer satisfaction.

Partner with Actowiz Solutions to leverage structured datasets, predictive analytics, and real-time dashboards to gain a competitive edge this Halloween season. With the right insights, restaurants can maximize seasonal revenue, reduce waste, and delight customers with trending, high-demand menu items. Unlock actionable intelligence now by Scraping Food Delivery Apps for Halloween Menu Trends and stay ahead of competition.

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
                        (
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                            [fr] => Columbus
                            [ja] => コロンバス
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                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                (
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                    [geoname_id] => 6255149
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                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
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                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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            [country] => Array
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                            [zh-CN] => 美国
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            [registered_country] => Array
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                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
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                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
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                                    [de] => Ohio
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                                    [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] => 216.73.216.58
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
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                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
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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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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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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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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
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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
                    [3] => isoCode
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        )

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

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
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                            [en] => United States
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                            [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
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            [validAttributes:protected] => Array
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                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
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        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [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] => 216.73.216.58
                    [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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Discover how to Track Real-Time Candy Price Monitoring in Halloween 2025, analyze consumer spending trends, optimize pricing strategies, and boost sales during the festive season.

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

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

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Explore how Scraping Real-Time Customer Feedback Data for Seamless USA delivers insights into customer sentiment, service quality, and experience optimization.

Oct 25, 2025

Track Real-Time Candy Price Monitoring in Halloween 2025 - Insights into Consumer Spending Trends

Discover how to Track Real-Time Candy Price Monitoring in Halloween 2025, analyze consumer spending trends, optimize pricing strategies, and boost sales during the festive season.

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Discover how Scraping Top 5 Food Delivery Apps for Halloween Menu Trends provides insights into seasonal food preferences, pricing, popularity, and real-time consumer behavior.

Oct 23, 2025

How Scraping Carrefour UAE Data for Quick Commerce Insights Helps Retailers Track Pricing, Delivery, and Stock Trends in Real Time?

Discover how Scraping Carrefour UAE Data for Quick Commerce Insights empowers retailers to track real-time pricing, delivery speed, and stock trends for smarter decisions.

Read More

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

Discover how Scraping Wayfair Data for Price Intelligence and Savings Analysis enabled online retailers to achieve 12–25% cost savings and optimize pricing strategies.

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

Discover how to scrape popular Halloween product data across USA & UK markets to analyze trends, boost sales, and optimize seasonal marketing strategies effectively.

How to Extract Food Delivery Data for City-Wise Halloween Order Trends to Optimize Festive Delivery Strategies

Discover how to extract food delivery data to analyze city-wise Halloween order trends, helping businesses optimize festive delivery strategies.

Read More

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

Track how prices of sweets, snacks, and groceries surged across Amazon Fresh, BigBasket, and JioMart during Diwali & Navratri in India with Actowiz festive price insights.

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

Scraping Real-Time Customer Feedback Data for Seamless USA - Insights & Analytics for Customer Experience

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Scrape Halloween Food Delivery Offers and Discounts Data for 2025 - City-Wise Menus, Deals & Consumer Insights

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Extract Product Availability & Consumer Ratings on Tesco & Sainsbury’s UK to Optimize Inventory and Pricing Strategies

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Read More

Our perks are irreplaceable

Time Zone Flexibility

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.

Clear Communication

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.

Uncompromising Quality

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

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