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GeoIp2\Model\City Object
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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            [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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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
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                            [zh-CN] => 美国
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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                    [ip_address] => 216.73.216.3
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                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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    [city:protected] => GeoIp2\Record\City Object
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                            [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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                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
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            [validAttributes:protected] => Array
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                    [1] => accuracyRadius
                    [2] => latitude
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                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
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        )

    [postal:protected] => GeoIp2\Record\Postal Object
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                    [code] => 43215
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            [validAttributes:protected] => Array
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    [subdivisions:protected] => Array
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            [0] => GeoIp2\Record\Subdivision Object
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                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
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                                    [pt-BR] => Ohio
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)
 country : United States
 city : Columbus
US
Array
(
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    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

Introduction

The food delivery market in Malaysia has grown rapidly, with GrabFoods leading urban and semi-urban consumer behavior changes. This Malaysia GrabFoods Market Analysis examines city-level demand, pricing trends, and menu strategies from 2020–2026, helping restaurants, aggregators, and investors make data-driven decisions. Actowiz Solutions uses structured datasets, advanced scraping frameworks, and analytical models to convert raw GrabFood data into strategic intelligence. The insights support pricing optimization, expansion planning, and demand forecasting in Malaysia’s dynamic food delivery ecosystem.

Urban Price Signals and Competitive Dynamics

Year Avg Meal Price (MYR) Delivery Fee (MYR) Discount Rate (%) Price Index Growth (%)
2020 18.5 4.8 5 3.4
2022 21.9 5.1 6.7 9.2
2024 24.3 5.7 8.1 11.8
2026 27.0 6.2 9.5 14.2

GrabFood City-Level Price Monitoring in Malaysia shows rising meal and delivery costs, driven by inflation and urban demand. Discounts helped maintain competitiveness, especially in Kuala Lumpur and Penang. Price index growth illustrates strategic pricing variations across cities.

Key Takeaways:
  • Urban hubs maintain higher average meal prices
  • Discounts mitigate price sensitivity
  • Data-driven monitoring informs menu pricing and promotions

Consumption Patterns Across Malaysian Cities

Year Avg Weekly Orders Peak Hours Orders (%) Growth Rate (%) Tier-2 City Share (%)
2020 95,000 62 0 28
2022 138,000 68 45 31
2024 186,500 72 35 36
2026 238,000 75 28 41

City-Wise GrabFood Demand Data Insight reveals a surge in weekly orders, late-night peaks, and growing contributions from Tier-2 cities.

Key Takeaways:
  • Peak orders shifted later in the evening
  • Tier-2 cities gained significant share
  • Data supports staffing, promotions, and menu planning

Linking Demand with Pricing Intelligence

Year Price Elasticity Index Avg Order Value (MYR) Promo Conversion (%) Revenue Growth (%)
2020 0.68 22.3 15 7.4
2022 0.72 25.7 18 11.9
2024 0.76 28.1 21 15.3
2026 0.81 31.6 24 18.9

Malaysia GrabFood Demand & Pricing Analytics shows increasing consumer sensitivity and rising average order values.

Insights:
  • Elasticity rose 0.68→0.81 (2020–2026)
  • Combo deals increased AOV
  • Pricing calibration maximizes revenue without losing demand

Menu Intelligence and Competitive Benchmarking

Year Distinct Menu Items Premium Items (%) Avg Menu Price Variance (%) Combo Offer Share (%)
2020 12,500 14 5.8 8
2022 18,300 19 7.2 13
2024 24,700 25 9.1 17
2026 31,200 32 11.4 22

GrabFood Menu & Price Scraper in Malaysia highlights menu diversification, premium product focus, and rising combo share across cities.

Insights:
  • Premium offerings concentrated in urban hubs
  • Combo meals enhance customer retention
  • Price variance aligns with local purchasing power

Structured Menu Data for Strategic Decisions

Year Total Menu Records Validated Entries (%) Avg Update Frequency (days) Seasonal Offer Share (%)
2020 42,000 76 16 5
2022 68,000 83 12 9
2024 93,000 91 9 14
2026 117,000 96 6 18

GrabFoods Menu Data Scraping ensures structured datasets for trend analysis, forecasting, and cross-city benchmarking.

Insights:
  • Dataset size tripled in six years
  • Updates became more frequent (6-day average by 2026)
  • Seasonal offers now drive 18% of menu sales

Delivery Fee Trends and Cost Transparency

Year Avg Delivery Fee (MYR) Surge Fee Incidence (%) Subscription Usage (%) Customer Churn (%)
2020 4.8 8 12 4.4
2022 5.3 11 19 5.2
2024 5.9 16 27 6.1
2026 6.5 22 34 7.3

Weekly Delivery Fees Data From GrabFood demonstrates rising logistics costs, subscription adoption, and churn management.

Insights:
  • Surge fees up to 22% by 2026
  • Subscription models offset cost sensitivity
  • Data supports fee and loyalty optimization

Actowiz Solutions provides scalable Food Delivery Data Scraping to capture high-frequency, city-level insights across pricing, demand, menus, and delivery fees. Our expertise in structured datasets, real-time analytics, and trend forecasting enables actionable intelligence for restaurants, aggregators, and investors. With automated scraping, we reduce manual effort while improving accuracy and compliance, empowering clients to make strategic, data-driven decisions in Malaysia’s competitive food delivery ecosystem.

Conclusion

By leveraging Web Crawling service and advanced Web Data Mining, Actowiz Solutions transforms GrabFood data into actionable insights across cities, menus, pricing, and delivery operations. Restaurants and delivery platforms can optimize pricing, forecast demand, and make smarter growth decisions.

Partner with Actowiz Solutions today to unlock hyperlocal GrabFood intelligence and stay ahead in Malaysia’s rapidly evolving food delivery market!

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:

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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Real results from real businesses using Actowiz Solutions

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Co-Founder / Head of Product at Upright Data Inc.
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See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

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

Appzon AirPdos Pro

Price
Drop −12 thr

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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

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