Email Receipt Ride-Sharing Data | Granular Transactional Data for Food Delivery/ Ride-Sharing Sector | Emerging Markets (APAC, LATAM, Europe & USA)
# | 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 |
pickupAddress |
dropoffAddress |
pickupLat |
pickupLon |
dropoffLat |
dropoffLon |
distanceInMiles |
tripTimeInSeconds |
carType |
priceItems |
driverId |
restaurant |
productItems |
deliveryFee |
deliveryFeeUSD |
additionalAddress |
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 | |
pickupAddress
|
String | Neo Grand Hotel | |
dropoffAddress
|
String | Tontamrab Muslim 1 (Halal) | |
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 | |
additionalAddress
|
|||
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 Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA)?
This email receipt ride-sharing dataset covers major players in regions like APAC, South-East Asia, Latin America, and part of Europe and US.
What is Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA) used for?
This product has 2 key use cases. Measurable AI recommends using the data for Investing and Market Intelligence. Global businesses and organizations buy Consumer Transaction Data from Measurable AI to fuel their analytics and enrichment.
Who can use Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA)?
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.
Which countries does Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA) cover?
This product includes data covering 18 countries like USA, Japan, Germany, United Kingdom, and France. Measurable AI is headquartered in Hong Kong.
How much does Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA) cost?
Pricing information for Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA) 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 Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA)?
Businesses can buy Consumer Transaction Data from Measurable AI and get the data via S3 Bucket and REST API.
What is the data quality of Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA)?
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 Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA)?
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 Grepsr Food Menu, Prices, Deliveries, and Reviews from Food Delivery Sites Global Coverage with Custom and On-demand Datasets. 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.