Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride | Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA
# | subject |
accountEmailId |
receivedDate |
dataType |
receiptId |
htmlKey |
uniqueId |
extractSpecTag |
primaryKey |
orderId |
orderType |
totalPrice |
totalPriceUSD |
totalCharged |
totalChargedUSD |
currency |
rawPaymentMethod |
paymentMethod |
langCode |
pickupTime |
pickupTimezoneOffset |
pickupTimeHasTimeZone |
dropoffTime |
dropoffTimezoneOffset |
dropoffTimeHasTimeZone |
pickupAddress |
dropoffAddress |
pickupLat |
pickupLon |
dropoffLat |
dropoffLon |
distanceInMiles |
tripTimeInSeconds |
carType |
priceItems |
driverId |
uberOfficeAddress |
||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | 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 |
3 | 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 | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx |
4 | 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 |
5 | 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 | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx |
6 | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx |
7 | 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 | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx |
8 | 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 |
9 | 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 | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx |
10 | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | 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 | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Email Address | ||
subject
|
String | Your Tuesday morning trip with Uber | |
accountEmailId
|
Integer | 1402294295 | |
receivedDate
|
Integer | 1675209638 | |
dataType
|
String | UberReceiptType | |
receiptId
|
String | 71e8506348666e5f2473df07cb30713ac1db7de2f565cc6bfb4e1d4ff... | |
htmlKey
|
String | 7869d2ed62375190d9a0e8cfd52745a1ea2ec85d0b359e02dd3624648... | |
uniqueId
|
String | g5Oowh4GUUjV9tgyO/+FdOxftAddrkJnY6dg+3CdWa4= | |
extractSpecTag
|
|||
primaryKey
|
String | 783c8678-52ef-44d7-8716-3b2bdea5a96e_purchase | |
orderId
|
String | 783c8678-52ef-44d7-8716-3b2bdea5a96e | |
orderType
|
String | Purchase | |
totalPrice
|
Float | 14.55 | |
totalPriceUSD
|
Float | 14.55 | |
totalCharged
|
Float | 13.88 | |
totalChargedUSD
|
Float | 13.88 | |
currency
|
String | USD | |
rawPaymentMethod
|
String | american express | |
paymentMethod
|
String | amex | |
langCode
|
String | en | |
String | US | Country Code Alpha-2 | |
pickupTime
|
Integer | 1675152300 | |
pickupTimezoneOffset
|
Integer | 0 | |
pickupTimeHasTimeZone
|
Boolean | f | |
dropoffTime
|
Integer | 1675152960 | |
dropoffTimezoneOffset
|
Integer | 0 | |
dropoffTimeHasTimeZone
|
Boolean | f | |
pickupAddress
|
String | 21 W End Ave, New York City, NY 10023, US | |
dropoffAddress
|
String | 1585 Broadway, New York City, NY 10036, US | |
pickupLat
|
Integer | 0 | |
pickupLon
|
Integer | 0 | |
dropoffLat
|
Integer | 0 | |
dropoffLon
|
Integer | 0 | |
distanceInMiles
|
Float | 1.32 | |
tripTimeInSeconds
|
Integer | 660 | |
carType
|
String | UberX | |
priceItems
|
String | [{"itemType":0,"price":10.62,"priceLabel":"$10.62","price... | |
driverId
|
|||
uberOfficeAddress
|
String | Uber Technologies 1515 3rd Street San Francisco, CA 94158 |
Description
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Pricing
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Frequently asked questions
What is Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA?
Ride hailing receipt data across multiple key players in South East Asia, Asia, Middle East, Latin America, United States, India and Japan.
What is Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA used for?
This product has 5 key use cases. Measurable AI recommends using the data for Business Intelligence (BI), Competitor Insights, Consumer Intelligence, Analytics, and Customer Insights. Global businesses and organizations buy Alternative Data from Measurable AI to fuel their analytics and enrichment.
Who can use Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Alternative 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 Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA cover?
This product includes data covering 18 countries like USA, Japan, Germany, India, and United Kingdom. Measurable AI is headquartered in Hong Kong.
How much does Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA cost?
Pricing information for Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, 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.
What is the data quality of Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, 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 Uber Ride Hailing/ Ride-Sharing Transactional Granular Email Receipt Ride Global coverage across Southeast Asia, Asia, Middle East, LATAM, USA?
This product has 3 related products. These alternatives include Email Receipt Ride-Sharing Data Granular Transactional Data for Food Delivery/ Ride-Sharing Sector Emerging Markets (APAC, LATAM, Europe & USA), Consumer Edge Restaurants Transaction Data USA Data 100M Credit & Debit Cards, 12K Merchants, 800 Parent Companies, 600 Tickers, and PredSearch Web Search Data, Keyword Data, Online Search Trends Data Amazon, Google, TikTok - 2 years history Global coverage +500k/w keywords. You can compare the best Alternative Data providers and products via Datarade’s data marketplace and get the right data for your use case.