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Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
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                    [geoname_id] => 4509177
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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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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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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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                                    [pt-BR] => Ohio
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                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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            [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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            [validAttributes:protected] => Array
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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
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                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [validAttributes:protected] => Array
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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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            [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
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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    [traits:protected] => GeoIp2\Record\Traits Object
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                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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                    [0] => autonomousSystemNumber
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                    [14] => isTorExitNode
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        )

    [city:protected] => GeoIp2\Record\City Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 4509177
                    [names] => Array
                        (
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                            [en] => Columbus
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
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                            [zh-CN] => 哥伦布
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    [location:protected] => GeoIp2\Record\Location Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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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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                    [1] => accuracyRadius
                    [2] => latitude
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                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
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            [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
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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
)
Navratri Mega Sale Price Tracking

Introduction

Global food delivery platforms struggle with inconsistent menus, naming conventions, and pricing formats across regions. Different languages, cuisines, and local listing standards create fragmented data that impacts search, recommendations, and user experience. In this case study, we explore how Actowiz Solutions helped a leading food delivery platform unify its global menu ecosystem by leveraging Extract Global Food Delivery Data for Menu Standardization. The objective was to build a clean, scalable, and structured menu dataset that worked seamlessly across countries while supporting localization. Actowiz designed a robust data extraction and normalization pipeline that consolidated menus from thousands of restaurants worldwide. This enabled consistent categorization, standardized item naming, and improved price visibility across markets. The result was a unified global menu foundation that enhanced discovery, analytics, and operational efficiency, allowing the platform to scale internationally with confidence and precision.

About the Client

Navratri Mega Sale Price Tracking

The client is a multinational food delivery and discovery platform operating across North America, Europe, Asia, and Latin America. Its ecosystem includes restaurants, cafés, bars, food trucks, and cloud kitchens catering to diverse cuisines and consumer preferences. Serving millions of users daily, the platform relies heavily on accurate and searchable menu data to power recommendations and ordering experiences. However, regional inconsistencies limited scalability. To address this, the client sought Restaurant Menu Standardization via Web scraping to unify menu structures, item descriptions, and pricing across countries. Their target market included urban consumers, international travelers, and enterprise restaurant partners looking for global visibility. By partnering with Actowiz Solutions, the client aimed to transform scattered menu listings into a structured global asset that supported growth, personalization, and advanced analytics.

Challenges & Objectives

Challenges
  • Data Fragmentation: Disparate menu formats across regions prevented building a unified Food Delivery Dataset for Menu Standardization, impacting search accuracy and recommendations.
  • Localization Complexity: Multiple languages, currencies, and portion sizes made normalization difficult.
Objectives
  • Global Consistency: Create a single standardized menu framework usable across countries and cuisines.
  • Scalable Intelligence: Enable analytics, pricing insights, and AI-driven recommendations from one clean dataset.

Our Strategic Approach

Cross-Border Menu Intelligence

Actowiz implemented Menu Data scraping for cross-country food analytics using adaptive crawlers capable of handling regional variations. The system captured item names, descriptions, prices, categories, and modifiers while preserving local context.

Data Normalization & Enrichment

Extracted data was translated, standardized, and enriched with cuisine tags and dietary attributes. This ensured consistency while retaining regional relevance for users and internal analytics.

Technical Roadblocks

  • Multi-Language Parsing: NLP-driven logic enabled Actowiz to Scrape Restaurant Menus across multi-Country while maintaining semantic accuracy.
  • Dynamic Platforms: Headless browsers handled JavaScript-heavy food delivery apps and websites.
  • Frequent Updates: Automated monitoring ensured continuous data freshness despite menu changes.

Our Solutions

Actowiz delivered comprehensive Food Delivery Datasets through a scalable architecture designed for global operations. The solution unified menu data from worldwide restaurants, cafés, bars, and food trucks into a single structured format. Advanced normalization aligned item names, categories, and pricing across regions, while multilingual support ensured accuracy. The platform enabled seamless integration with search, recommendation engines, and analytics dashboards. By automating data collection and updates, Actowiz eliminated manual intervention and improved consistency. This empowered the client to enhance user discovery, streamline operations, and roll out new markets faster with reliable menu intelligence.

Results & Key Metrics

  • Search Accuracy: Improved results driven by standardized menus and Menu Price Scraping.
  • Global Coverage: Unified menus across 30+ countries and thousands of food outlets.
  • Operational Efficiency: Reduced data preparation time by over 65%.
  • Customer Experience: Better recommendations, cuisine tagging, and price transparency.

Client Feedback

“Actowiz Solutions helped us successfully Extract Global Food Delivery Data for Menu Standardization at a scale we couldn’t achieve internally. Their data accuracy and global coverage transformed how we manage menus and recommendations across markets.”

— Director of Data Platforms, Global Food Delivery Company

Why Partner with Actowiz Solutions?

Actowiz Solutions is a trusted data partner for global food delivery platforms seeking reliable, large-scale menu intelligence. With proven expertise to Extract Global Food Delivery Data for Menu Standardization, Actowiz helps businesses eliminate inconsistencies across regions, languages, and formats. Our scalable, secure, and compliant data architectures are designed to handle millions of menu records while ensuring accuracy, freshness, and regulatory alignment. We deliver true global coverage supported by strong localization intelligence, enabling platforms to capture region-specific menus without losing standardization. Beyond technology, Actowiz offers dedicated technical support and continuous optimization to adapt to changing platforms, new markets, and evolving business needs. Our combination of domain expertise, automation, and customization ensures clients gain actionable insights, improved search relevance, and seamless scalability, making Actowiz Solutions a long-term partner for data-driven growth.

How Actowiz Built a Unified Global Menu Dataset?

Actowiz engineered a clean, multi-language menu dataset spanning more than 30 countries by designing a robust global data extraction and normalization framework. The system captured structured menu information from worldwide food establishments, including restaurants, cafés, bars, food trucks, and beverage outlets—essentially any place offering food or drinks. Advanced scraping logic, language-aware parsing, and intelligent data mapping ensured menus were standardized while preserving local context. Item names, categories, prices, and modifiers were unified into a single consistent structure. This large-scale dataset enabled enhanced search relevance, smarter recommendations, and accurate cuisine tagging across global markets. By consolidating fragmented menu listings into one trusted source of truth, Actowiz empowered food delivery platforms to improve user experience, analytics, and operational efficiency worldwide.

Conclusion

This case study highlights how Actowiz Solutions successfully addressed global menu inconsistency using a powerful Web scraping API, tailored Custom Datasets, and an instant data scraper. By transforming scattered, multi-country menu data into a unified and standardized dataset, Actowiz enabled the client to scale internationally with confidence. The solution improved search accuracy, recommendations, and operational insights across markets. Food delivery platforms looking to achieve global consistency, faster expansion, and data-driven decision-making can rely on Actowiz Solutions as a trusted and scalable data partner.

FAQs

1. What types of food outlets are covered in the dataset?

The solution includes restaurants, cafés, bars, food trucks, cloud kitchens, and beverage outlets worldwide.

2. How does Actowiz handle multiple languages?

Menus are translated and normalized using language-aware parsing and enrichment techniques.

3. Can the dataset support recommendations and search?

Yes, standardized menus significantly improve search relevance, cuisine tagging, and recommendations.

4. How often is menu data updated?

Data refresh frequency can be customized from daily to near real-time updates.

5. Is the solution scalable to new countries?

Absolutely. The architecture is designed to onboard new regions quickly with minimal effort.

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:

Fintech / Digital Payments

Result

Accurate daily voucher &

cashback visibility across platforms

★★★★★

“Actowiz Solutions helped us automate daily voucher and cashback data collection across PhonePe, Paytm, Flipkart, and Hubble. The API-driven delivery significantly improved offer accuracy and operational efficiency.”

Product Manager, Fintech Platform (India)

✓ Daily voucher & cashback tracking via Push & Pull APIs

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
1 min
★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & 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

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