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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] => 216.73.216.110 [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] => 216.73.216.110 [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 )
Drive growth by scraping restaurants data from iFood platform to gain pricing, menu, and competitor insights for smarter decisions and expansion.
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At Actowiz Solutions, we help food and restaurant brands unlock powerful competitive intelligence through advanced Scraping Restaurants Data from iFood Platform strategies. In Brazil’s rapidly evolving food delivery ecosystem, access to structured and real-time insights can determine whether a brand leads or lags behind competitors. By leveraging specialized Restaurant Data Scraping solutions, we enabled our client to gain deep visibility into menus, pricing, ratings, and location-based demand trends from iFood.
Our data-driven framework transformed fragmented information into actionable business intelligence. Instead of relying on assumptions, the brand began making precise pricing adjustments, optimizing menu positioning, and identifying high-performing cuisines across cities. This case study highlights how Actowiz Solutions combined scalable scraping technology, analytics dashboards, and strategic consultation to deliver measurable growth and stronger competitive positioning in Brazil’s dynamic online food delivery market.
Our client is a fast-growing multi-location food brand operating in Brazil’s cloud kitchen and quick-service restaurant segment. Targeting urban millennials, working professionals, and digital-first consumers, the brand depends heavily on food delivery platforms for customer acquisition and repeat sales.
However, the client lacked structured access to Web scraping iFood restaurant data, limiting their ability to benchmark against competitors or track city-level pricing trends. They needed visibility into menu strategies, promotional offers, customer ratings, and cuisine performance across multiple regions.
Without centralized intelligence, expansion decisions were based on limited internal reports rather than real-time market signals. The brand partnered with Actowiz Solutions to implement a scalable data infrastructure capable of delivering automated insights, competitive benchmarking, and performance analytics—ultimately helping them compete more effectively within Brazil’s highly competitive food delivery ecosystem.
Challenge: The client struggled to Extract restaurant listings from iFood, making it difficult to track new entrants and category leaders.
Objective: Implement automated Food Delivery Data Scraping to gain complete competitor visibility across cities.
Challenge: Inconsistent pricing strategies reduced competitiveness in key zones.
Objective: Develop structured pricing intelligence dashboards.
Challenge: No clear tracking of high-demand vs. underperforming items.
Objective: Enable SKU-level performance monitoring.
Challenge: Limited data for city-wise demand forecasting.
Objective: Use location-based analytics to guide expansion planning.
We deployed automated systems to Scrape iFood restaurant menus and prices, capturing SKU-level pricing, combo offers, and discount trends across targeted cities. Our analytics model compared competitor clusters, cuisine categories, and delivery zones to uncover pricing elasticity and promotional effectiveness. This structured intelligence empowered the client to refine price positioning without sacrificing profit margins.
We built centralized dashboards integrating category performance, rating trends, and demand patterns. By analyzing menu sequencing and popular cuisines, the client optimized product placement and launched high-performing bundles. Real-time visibility into location-specific trends enabled smarter marketing campaigns and better inventory planning.
Frequent UI updates impacted data consistency and iFood restaurant-wise pricing Data insights extraction.
Solution: Implemented adaptive scraping logic with automated selector updates.
City-specific views limited comprehensive data capture.
Solution: Built geo-targeted scraping modules for accurate regional datasets.
Inconsistent naming conventions complicated comparisons.
Solution: Developed normalization algorithms to standardize menu and pricing formats for analytics accuracy.
Actowiz Solutions designed an end-to-end ecosystem integrating automated pipelines, validation layers, and visualization dashboards. Through advanced iFood City-Wise Restaurant Data Extraction, we captured hyperlocal insights, including cuisine popularity, rating patterns, and promotional trends. Combined with scalable Scraping Restaurants Data from iFood Platform, the system delivered structured, city-specific intelligence directly into BI dashboards.
This solution empowered the brand to monitor competitors daily, adjust pricing dynamically, and optimize menu layouts based on consumer demand. Additionally, predictive trend analysis helped forecast high-growth neighborhoods, enabling smarter outlet expansion strategies.
The scalable infrastructure ensured secure data handling, automated updates, and seamless integration with the client’s CRM and analytics tools—turning raw delivery data into measurable growth outcomes.
After implementing systems to Scrape Restaurants Data from iFood, the brand achieved a 29% increase in order volume within six months.
Dynamic pricing adjustments improved margin efficiency by 17%.
High-demand SKUs saw a 22% uplift in visibility and conversions.
City-level intelligence guided successful entry into two new high-demand regions.
Overall, structured intelligence significantly improved competitiveness, operational precision, and profitability.
"Actowiz Solutions transformed how we approach competitive strategy. Their expertise in Scraping Restaurants Data from iFood Platform gave us unmatched clarity into pricing, menus, and city-level demand trends. We now make faster, smarter decisions backed by real-time insights."
— Head of Strategy, Food Brand
We specialize in scalable Web Scraping iFood Data pipelines tailored for food delivery intelligence.
Our automation ensures consistent, accurate, and structured data delivery.
From extraction to visualization, we provide complete lifecycle management with secure infrastructure and dedicated support.
Actowiz Solutions combines technical excellence, domain expertise, and analytics-driven strategy to empower food brands with sustainable competitive advantage.
This case study highlights how Actowiz Solutions empowered a food brand with structured intelligence and scalable automation. Through our powerful Web scraping API, tailored Custom Datasets, and advanced instant data scraper, we transformed platform data into actionable growth strategies.
If you’re ready to unlock competitive insights from iFood and accelerate your brand’s expansion, partner with Actowiz Solutions today and turn data into measurable success.
It is the automated extraction of structured information such as menus, prices, ratings, and listings from the iFood platform for competitive intelligence.
Legality depends on platform policies and data usage methods. Ethical, compliant scraping aligned with regulations is recommended.
Brands can access pricing trends, menu comparisons, location-based demand, customer ratings, and promotional analytics.
Our solutions support daily, weekly, or real-time updates depending on business requirements.
We deliver scalable infrastructure, accurate datasets, customized dashboards, and ongoing technical support to help brands achieve measurable ROI in competitive food delivery markets.
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
Coffee / Beverage / D2C
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
Real Estate
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×
Organic Grocery / FMCG
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
Quick Commerce
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
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
Beverage / D2C
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
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
Real results from real businesses using Actowiz Solutions
In Stock₹524
Price Drop + 12 minin 6 hrs across Lel.6
Price Drop −12 thr
Improved inventoryvisibility & planning
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
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
With hourly price monitoring, we aligned promotions with competitors, drove 17%
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Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.
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.
Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations