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GeoIp2\Model\City Object
(
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                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

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            [traits] => Array
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                            [ru] => Северная Америка
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                            [ru] => США
                            [zh-CN] => 美国
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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                    [20] => userCount
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                )

        )

    [city:protected] => GeoIp2\Record\City Object
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                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

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    [location:protected] => GeoIp2\Record\Location Object
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                    [latitude] => 39.9625
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                )

            [validAttributes:protected] => Array
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                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
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            [validAttributes:protected] => Array
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    [subdivisions:protected] => Array
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                                    [pt-BR] => Ohio
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                                )

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                    [validAttributes:protected] => Array
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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
)

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  • Tracking Promotions and Seasonal Discounts – Deliveroo, Just Eat

Tracking Promotions and Seasonal Discounts on Deliveroo & Just Eat in the UK

Discover how tracking promotions and seasonal discounts on Deliveroo and Just Eat in the UK helped businesses gain insights, optimize pricing, and boost sales performance.

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GeoIp2\Model\City Object
(
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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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                            [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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                            [zh-CN] => 美国
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                                    [fr] => Ohio
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                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.213
                    [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
                            [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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                )

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    [country:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [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
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            [validAttributes:protected] => Array
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        )

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

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

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

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

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
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                    [network] => 216.73.216.0/22
                )

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                    [15] => mobileCountryCode
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        )

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                    [names] => Array
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                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                )

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        (
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                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
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            [validAttributes:protected] => Array
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                    [8] => timeZone
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    [postal:protected] => GeoIp2\Record\Postal Object
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        )

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            [0] => GeoIp2\Record\Subdivision Object
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                            [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
)
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Navratri Mega Sale Price Tracking

Introduction

In the highly competitive UK food delivery market, tracking Promotions and Seasonal Discounts is essential for restaurants and delivery platforms to remain competitive. Restaurants face constant changes in offers, seasonal promotions, and competitor campaigns, making manual monitoring inefficient and error-prone. To address this, the client leveraged Scrape Deliveroo and Just Eat promotions Data in UK, enabling structured, real-time insights from multiple platforms. By automating data collection, the client could monitor promotions dynamically, analyze trends, and adjust marketing strategies quickly. Actowiz Solutions implemented advanced Food Delivery Promotions & Seasonal Discounts Data Scraping solutions that transformed raw data into actionable intelligence, allowing restaurants and food brands to respond proactively to consumer behavior. This approach ensured timely promotional updates, optimized pricing strategies, and improved engagement with customers. The automation of promotional data collection also reduced operational workload and minimized errors, allowing the client to maintain a competitive edge in a fast-evolving market where timely decisions are critical for revenue growth and market positioning.

The Client

The client is a leading UK-based food delivery aggregator, partnering with hundreds of restaurants across major cities. As their network and customer base expanded, understanding competitor promotions on platforms such as Deliveroo and Just Eat became a priority. To optimize offerings and improve customer engagement, the client implemented Web scraping Deliveroo & Just Eat offers, enabling them to capture restaurant-specific menu trends, pricing adjustments, and promotional activities in real time. By analyzing this structured data, the client could identify which promotions were effective and which required adjustment. With real-time insights, they could proactively tailor their campaigns, maintain competitiveness, and improve overall profitability. Partnering with Actowiz Solutions allowed the client to leverage data-driven strategies to monitor seasonal and regular offers efficiently, optimize restaurant promotions, and make informed decisions. This empowered the client to enhance menu competitiveness, improve marketing effectiveness, and respond faster to market trends.

Key Challenges

Key Challenges-01

Before automation, the client relied heavily on manual tracking of promotions across Deliveroo and Just Eat. This process was time-consuming, error-prone, and often resulted in delayed decision-making. Maintaining accurate records of Just Eat seasonal discount data extraction from multiple listings was particularly challenging due to frequent changes in offers and the diversity of promotions running concurrently. Manual collection made it difficult to analyze trends across competitors consistently, leaving the client reactive rather than proactive in their strategy. Additionally, unstructured data from multiple sources created further hurdles in aggregating insights for actionable decisions. The inability to monitor restaurant offers in real time hindered the client’s responsiveness, leading to missed revenue opportunities and potential market share loss. Without an automated system to Extract seasonal discount data from Deliveroo & Just Eat, the client faced the risk of being outpaced by competitors who could adjust pricing and offers dynamically. Efficiently capturing, standardizing, and analyzing promotions data was critical to maintaining relevance in a highly competitive food delivery market where timing and precision are essential.

Key Solutions

The-Client

Actowiz Solutions implemented a comprehensive data scraping strategy to address the client’s challenges. By Scraping Deliveroo Food Delivery Data, the client could monitor restaurant offers, menu pricing, and promotional campaigns in real time. The team also deployed solutions to Scrape Deliveroo restaurant & Menu Data, enabling accurate analysis of menu trends, price variations, and promotional effectiveness. Our Price Monitoring Services ensured that pricing fluctuations across platforms were tracked continuously, allowing restaurants to remain competitive. In addition, Coupon & Deals Data Scraping captured special offers, discount codes, and seasonal promotions to provide a complete view of the market. On the Just Eat platform, Actowiz Solutions implemented solutions to Extract Just Eat Food Delivery Data efficiently, along with a Just Eat Scraping API that automated collection of seasonal discount information, menu updates, and promotional campaigns. By combining these solutions, the client was able to implement a robust system for Tracking Promotions and Seasonal Discounts, making data-driven decisions that improved sales, engagement, and profitability.

Client Testimonial

"Actowiz Solutions has completely transformed how we track promotions and seasonal discounts across Deliveroo and Just Eat. Their data scraping solutions provide accurate, real-time insights that allow us to optimize our offers and stay ahead of competitors. The automation has saved our team countless hours, and the insights have directly contributed to increased engagement and revenue. Working with Actowiz has been a game-changer for our strategy."

— Head of Market Insights, Leading UK Food Delivery Aggregator

Conclusion

This case study demonstrates how Tracking Promotions and Seasonal Discounts through advanced data scraping can empower food delivery platforms and restaurants to stay competitive. By leveraging Actowiz Solutions’ expertise in Food Delivery Promotions & Seasonal Discounts Data Scraping, the client was able to automate data collection from Deliveroo and Just Eat, analyze promotions effectively, and implement dynamic strategies that improved market responsiveness. The combination of real-time monitoring, structured insights, and actionable analytics enabled the client to optimize menu pricing, enhance promotional campaigns, and maximize revenue. As the UK food delivery market continues to evolve, the ability to Track Promotions and Seasonal Discounts ensures that businesses can make informed decisions, reduce manual effort, and maintain a strong competitive position. Actowiz Solutions continues to support clients in harnessing data intelligence for measurable growth and operational efficiency.

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Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

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Move Forward Predict demand, price shifts, and future opportunities across geographies.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
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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

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Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
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1 min
★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
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1 min

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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

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Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

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