GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data | E-Receipt Data | South East Asia | Granular & Aggregate Data avail.
# | subject |
accountEmailId |
receivedDate |
dataType |
receiptId |
htmlKey |
uniqueId |
primaryKey |
orderId |
orderType |
totalPrice |
totalPriceUSD |
totalCharged |
totalChargedUSD |
currency |
rawPaymentMethod |
paymentMethod |
langCode |
country |
pickupTime |
pickupTimezoneOffset |
pickupTimeHasTimeZone |
dropoffTime |
dropoffTimezoneOffset |
dropoffTimeHasTimeZone |
pickupLat |
pickupLon |
dropoffLat |
dropoffLon |
distanceInMiles |
tripTimeInSeconds |
carType |
priceItems |
driverId |
restaurant |
productItems |
deliveryFee |
deliveryFeeUSD |
additionalStopFee |
additionalStopFeeUSD |
profile |
orderTime |
orderTimezoneOffset |
orderTimeHasTimeZone |
rewardPoints |
isPickupOrder |
serviceType |
dropoffLabel |
|||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx |
2 | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx |
3 | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx |
4 | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx |
5 | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx |
6 | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx |
7 | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx |
8 | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx |
9 | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx |
10 | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx |
... | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Email Address | ||
subject
|
String | Your Grab E-Receipt | |
accountEmailId
|
Integer | 2577125024 | |
receivedDate
|
Integer | 1682898707 | |
dataType
|
String | GrabReceiptType | |
receiptId
|
String | 79cf97f85fc1f539c611594f877b5ea7120caebe51d28c31807fdf609... | |
htmlKey
|
String | 31c6202fd61d34457ffa91e456b9239b6d46219747706d4e1a9829548... | |
uniqueId
|
String | GyCeID+aoegGguP6TYgK4N+kM6Oe4Ao4xotUMS+yKrQ= | |
primaryKey
|
String | a-4shm7jngwhhm_purchase | |
orderId
|
String | A-4SHM7JNGWHHM | |
orderType
|
|||
totalPrice
|
Integer | 80 | |
totalPriceUSD
|
Float | 2.344 | |
totalCharged
|
Integer | 80 | |
totalChargedUSD
|
Float | 2.344 | |
currency
|
String | THB | |
rawPaymentMethod
|
String | amex | |
paymentMethod
|
String | amex | |
langCode
|
String | th | |
String | TH | Country Code Alpha-2 | |
country
|
String | Thailand | |
pickupTime
|
Integer | 1682836800 | |
pickupTimezoneOffset
|
Integer | 0 | |
pickupTimeHasTimeZone
|
Boolean | f | |
dropoffTime
|
Integer | 1682836980 | |
dropoffTimezoneOffset
|
Integer | 0 | |
dropoffTimeHasTimeZone
|
Boolean | f | |
String | Address | ||
String | Address | ||
pickupLat
|
Integer | 0 | |
pickupLon
|
Integer | 0 | |
dropoffLat
|
Integer | 0 | |
dropoffLon
|
Integer | 0 | |
distanceInMiles
|
Float | 0.615 | |
tripTimeInSeconds
|
Integer | 180 | |
carType
|
String | JustGrab | |
priceItems
|
String | [{"itemType":0,"price":80,"priceLabel":"80","priceName":"... | |
driverId
|
|||
restaurant
|
|||
productItems
|
String | [] | |
deliveryFee
|
Integer | 0 | |
deliveryFeeUSD
|
Integer | 0 | |
String | Address | ||
additionalStopFee
|
Integer | 0 | |
additionalStopFeeUSD
|
Integer | 0 | |
profile
|
String | personal | |
orderTime
|
Integer | 0 | |
orderTimezoneOffset
|
Integer | 0 | |
orderTimeHasTimeZone
|
Boolean | f | |
rewardPoints
|
Integer | 0 | |
isPickupOrder
|
Boolean | f | |
serviceType
|
String | Mobility | |
dropoffLabel
|
Description
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Frequently asked questions
What is GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail.?
GrabFood and Grab Express Restaurant & Food Delivery Transaction datasets provide accurate consumer insights and understanding of industry trends based on restaurant & food delivery transaction data.
What is GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail. used for?
This product has 5 key use cases. Measurable AI recommends using the data for Investing, Consumer Intelligence, Market Intelligence, Alternative Investment, and Customer Insights. Global businesses and organizations buy Consumer Transaction Data from Measurable AI to fuel their analytics and enrichment.
Who can use GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail.?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Consumer Transaction Data. Get in touch with Measurable AI to see what their data can do for your business and find out which integrations they provide.
How far back does the data in GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail. go?
This product has 6 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, and yearly basis.
Which countries does GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail. cover?
This product includes data covering 8 countries like Japan, Indonesia, Thailand, Singapore, and Malaysia. Measurable AI is headquartered in Hong Kong.
How much does GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail. cost?
Pricing information for GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail. is available by getting in contact with Measurable AI. Connect with Measurable AI to get a quote and arrange custom pricing models based on your data requirements.
How can I get GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail.?
Businesses can buy Consumer Transaction Data from Measurable AI and get the data via S3 Bucket and REST API. Depending on your data requirements and subscription budget, Measurable AI can deliver this product in .json, .xml, and .csv format.
What is the data quality of GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail.?
You can compare and assess the data quality of Measurable AI using Datarade’s data marketplace. Measurable AI appears on selected Datarade top lists ranking the best data providers, including Who’s New on Datarade? July Edition.
What are similar products to GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail.?
This product has 3 related products. These alternatives include UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available, Consumer Edge Vision Retention Data CPG, Grocery, Food Delivery Psychographic US Transaction 100M+ Cards, 12K+ Merchants, Retail & Ecommerce, and Envestnet Yodlee’s De-Identified Restaurant and Food Delivery Transaction Data Row/Aggregate Level USA Consumer Data covering 3600+ corporations. You can compare the best Consumer Transaction Data providers and products via Datarade’s data marketplace and get the right data for your use case.