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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] => 216.73.216.141 [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] => 216.73.216.141 [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 )
Discover how a regional F&B player scaled 3x across PH, SG, and MY by leveraging Scrape GrabFood Delivery Fee Data For Weekly Benchmarking to optimize pricing and boost revenue.
Note: You’ll receive it via email shortly after submitting the form.
In today’s competitive food delivery market, regional F&B players face increasing pressure to optimize pricing, manage delivery fees, and stay ahead of competitors. Actowiz Solutions partnered with a leading F&B brand to drive expansion across the Philippines, Singapore, and Malaysia. By implementing Scrape GrabFood Delivery Fee Data For Weekly Benchmarking, the client was able to gain precise insights into delivery fee trends, competitor pricing, and market dynamics. This data-driven approach enabled faster decision-making and allowed the client to adjust strategies for maximum growth. Leveraging weekly data scraping provided not only a clear view of the market landscape but also actionable intelligence to improve profitability and operational efficiency. The approach combined cutting-edge technology with meticulous market research, ensuring the client could scale confidently across multiple regions. Ultimately, consistent benchmarking became a cornerstone of their regional growth strategy, resulting in measurable performance improvements and business expansion.
The client is a rapidly growing F&B brand with an ambitious vision to become a leading regional player across Southeast Asia. With a strong presence in the Philippines, they sought to enter the Singaporean and Malaysian markets while maintaining competitive pricing and delivery efficiency. Operating in a highly fragmented delivery ecosystem, the client required accurate insights into GrabFood’s dynamic fee structures and market trends. Actowiz Solutions stepped in to provide a tailored solution through Scrape GrabFood Delivery Fee Data For Weekly Benchmarking, ensuring the client had up-to-date, actionable data. The client’s core focus was on optimizing delivery fees, understanding competitor pricing, and scaling operations seamlessly across multiple countries. By leveraging this data-driven approach, the client could align business strategies with market realities, enhance customer satisfaction, and drive profitability. Actowiz’s solution provided the necessary analytical foundation to support the client’s ambitious regional growth plans and deliver tangible results across all target markets.
Expanding into multiple countries presented the client with several challenges. First, GrabFood delivery fees vary significantly across regions, and understanding these fluctuations required a systematic, data-driven approach. Second, competitor pricing strategies were constantly evolving, making it difficult for the client to remain competitive without real-time insights. The client also faced difficulties in monitoring delivery fee trends without a structured process for collecting and analyzing large datasets. In addition, manual data collection proved to be time-consuming and prone to errors, which hindered timely decision-making. Ensuring accurate benchmarking across the Philippines, Singapore, and Malaysia was particularly challenging due to differences in local markets, restaurant fees, and delivery logistics. Maintaining profitability while expanding operations required precise insights into weekly fee trends, competitor behavior, and market conditions. Furthermore, the client needed a scalable solution that could continuously extract, analyze, and report critical metrics. These challenges highlighted the need for a robust technological solution that could automate data collection, provide actionable insights, and support strategic growth decisions in a fast-paced market.
Actowiz Solutions implemented a comprehensive approach to address these challenges using Scrape GrabFood Delivery Fee Data For Weekly Benchmarking. First, the team developed a process to gather granular data from GrabFood, enabling the client to understand delivery fee structures and variations in different cities. Leveraging Weekly GrabFood Pricing Benchmarking Insights, the client could track trends and adjust their pricing strategy dynamically. To ensure complete market visibility, Actowiz enabled the client to Extract GrabFood Delivery Fee Trends Weekly, providing a continuous stream of actionable insights. A centralized GrabFood Weekly Fee Benchmarking Dataset allowed the client to analyze historical and current data, identify patterns, and forecast changes. Furthermore, Actowiz helped Extract GrabFood Weekly Fee Analytics to uncover opportunities for margin improvement and competitive positioning. By implementing GrabFood Delivery Fee Data Extraction for Benchmarking, the client gained accurate and timely intelligence to optimize delivery fees. Web Scraping GrabFood Restaurant Fees Data in Philippines, Singapore & Malaysia allowed for consistent monitoring of multi-market trends, while Scraping Weekly GrabFood Pricing & Commission Trends Data gave visibility into competitor strategies. Additionally, the solution enabled the client to Scrape GrabFood delivery fees in PH, SG, and MY for benchmarking, offering precise insights for strategic decision-making. Complementary solutions, including Competitive Benchmarking, Scrape Singapore Food Delivery Data, Food Delivery Data Scraping API, Price Monitoring, and advanced Web Scraping Services, ensured the client had a full suite of tools to maintain a competitive edge and drive expansion.
“Partnering with Actowiz Solutions has been a game-changer for our regional expansion strategy. Their expertise in Scrape GrabFood Delivery Fee Data For Weekly Benchmarking gave us unparalleled insights into delivery fees and competitor pricing across PH, SG, and MY. The data-driven approach allowed us to optimize fees, improve profitability, and scale 3x faster than anticipated. Actowiz’s team is professional, responsive, and truly understands the nuances of the food delivery ecosystem. Thanks to their solutions, we now have a sustainable process to monitor and benchmark delivery fees weekly, enabling us to stay ahead in a highly competitive market.”
— Marketing Director, Regional F&B Brand
Actowiz Solutions empowered the client to achieve significant growth by leveraging Scrape GrabFood Delivery Fee Data For Weekly Benchmarking as the foundation of their expansion strategy. By continuously monitoring and analyzing delivery fee trends, the client gained critical insights that informed pricing, menu offerings, and market entry decisions. The combination of data-driven intelligence and advanced web scraping solutions enabled the client to navigate the complexities of multiple markets efficiently. With actionable insights derived from Weekly GrabFood Pricing Benchmarking Insights, Extract GrabFood Delivery Fee Trends Weekly, and other complementary services, the client optimized operations, increased revenue, and enhanced competitiveness. This case study demonstrates that consistent and precise benchmarking is not just a tool for analysis but a strategic driver of growth. Actowiz’s approach ensures businesses can scale confidently, adapt quickly to market changes, and maintain a strong foothold across Southeast Asia’s dynamic food delivery landscape.
Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.
Find Insights Use AI to connect data points and uncover market changes. Meanwhile.
Move Forward Predict demand, price shifts, and future opportunities across geographies.
Industry:
Coffee / Beverage / D2C
Result
2x Faster
Smarter product targeting
“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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