UberEats E-Receipt Data | Food Delivery Transaction Data | Asia, Americas, EMEA | Granular & Aggregate Data available
# | mailSource |
subject |
accountEmailId |
receivedDate |
dataType |
orderType |
totalPrice |
totalPriceUSD |
totalCharged |
totalChargedUSD |
currency |
rawPaymentMethod |
paymentMethod |
langCode |
country |
orderTime |
orderTimezoneOffset |
orderTimeHasTimeZone |
pickupTime |
restaurant |
priceItems |
productItems |
driverId |
distanceInMiles |
tripTimeInSeconds |
carType |
paymentMethods |
||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx |
3 | 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 |
4 | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx |
5 | 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 |
6 | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | 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 |
7 | 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 | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx |
8 | 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 |
9 | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx |
10 | 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 | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Email Address | ||
mailSource
|
|||
subject
|
String | Your Sunday morning order with Uber Eats | |
accountEmailId
|
Integer | 2580802977 | |
receivedDate
|
Integer | 1676218133 | |
dataType
|
String | UberEatsReceiptType | |
orderType
|
String | Purchase | |
totalPrice
|
Float | 18.3 | |
totalPriceUSD
|
Float | 18.3 | |
totalCharged
|
Float | 18.3 | |
totalChargedUSD
|
Float | 18.3 | |
currency
|
String | USD | |
rawPaymentMethod
|
String | visa | |
paymentMethod
|
String | visa | |
langCode
|
String | en | |
String | US | Country Code Alpha-2 | |
country
|
String | United States | |
orderTime
|
Integer | 0 | |
orderTimezoneOffset
|
Integer | 0 | |
orderTimeHasTimeZone
|
Boolean | f | |
pickupTime
|
Integer | 1676160000 | |
String | Address | ||
restaurant
|
String | The Cleveland Bagel Co. ( Carnegie Ave ) | |
priceItems
|
String | [] | |
productItems
|
String | [] | |
driverId
|
|||
distanceInMiles
|
Integer | 0 | |
tripTimeInSeconds
|
Integer | 0 | |
carType
|
String | UberEats | |
String | Address | ||
paymentMethods
|
String | [{"paymentMethod":"visa","price":18.3,"priceLabel":"$18.3... |
Description
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Frequently asked questions
What is UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available?
UberEats E-Receipt data provides accurate consumer insights and understanding of industry trends based on restaurant & food delivery transaction data.
What is UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available 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 UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available?
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 UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available 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 UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available cover?
This product includes data covering 182 countries like USA, China, Japan, Germany, and India. Measurable AI is headquartered in Hong Kong.
How much does UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available cost?
Pricing information for UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available 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 UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available?
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 UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available?
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 UberEats E-Receipt Data Food Delivery Transaction Data Asia, Americas, EMEA Granular & Aggregate Data available?
This product has 3 related products. These alternatives include GrabFood, GrabExpress Restaurant & Food Delivery Transaction Data E-Receipt Data South East Asia Granular & Aggregate Data avail., Grepsr Food Menu, Prices, Deliveries, and Reviews from Food Delivery Sites Global Coverage with Custom and On-demand Datasets, and Consumer Edge Vision Retention Data CPG, Grocery, Food Delivery Psychographic US Transaction 100M+ Cards, 12K+ Merchants, Retail & Ecommerce. 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.