Granular SKU-Level Transaction Data | Global Ecommerce Transactional Data for Emerging Markets
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Verified Data Provider| # | subject |
accountEmailId |
receivedDate |
dataType |
receiptId |
htmlKey |
uniqueId |
orderId |
orderType |
totalPrice |
totalPriceUSD |
totalCharged |
totalChargedUSD |
currency |
rawPaymentMethod |
paymentMethod |
countryCode |
country |
pickupTime |
pickupTimezoneOffset |
pickupTimeHasTimeZone |
dropoffTime |
dropoffTimezoneOffset |
dropoffTimeHasTimeZone |
pickupLat |
pickupLon |
dropoffLat |
dropoffLon |
distanceInMiles |
tripTimeInSeconds |
priceItems |
driverId |
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 |
| 2 | 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 | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx |
| 3 | 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 |
| 4 | 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 | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx |
| 5 | 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 | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx |
| 6 | 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 |
| 7 | 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 |
| 8 | 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 |
| 9 | xxxxxx | 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 |
| 10 | 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 | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx |
Data Dictionary
| Attribute | Type | Example | Mapping |
|---|---|---|---|
| String | Email Address | ||
|
subject
|
String | _____ __ ____ __ ___ ________ | |
|
accountEmailId
|
Integer | 1205313389 | |
|
receivedDate
|
Integer | 1654015438 | |
|
dataType
|
String | BoltReceiptType | |
|
receiptId
|
String | 9e1fd73c1613573065f9eb222cb00faee9b8f6b4698934a3514e3cc34... | |
|
htmlKey
|
String | d4f986a21c7641548cf5f261ca9463da33a011b0b2f17b5b42e8fa177... | |
|
uniqueId
|
String | jYHc81/qIl+KiHszbjvB0Q4fWCDaYHPHWf/Gy289atE= | |
|
orderId
|
String | 7edea435-9ea2-421e-9dd6-537e50f435db | |
|
orderType
|
String | Purchase | |
|
totalPrice
|
Integer | 47 | |
|
totalPriceUSD
|
Float | 12.491 | |
|
totalCharged
|
Integer | 47 | |
|
totalChargedUSD
|
Float | 12.491 | |
|
currency
|
String | SAR | |
|
rawPaymentMethod
|
String | ____ | |
|
paymentMethod
|
String | ____ | |
|
countryCode
|
String | SA | |
|
country
|
String | Saudi Arabia | |
|
pickupTime
|
Integer | 1654024980 | |
|
pickupTimezoneOffset
|
Integer | 0 | |
|
pickupTimeHasTimeZone
|
Boolean | f | |
|
dropoffTime
|
Integer | 1654026120 | |
|
dropoffTimezoneOffset
|
Integer | 0 | |
|
dropoffTimeHasTimeZone
|
Boolean | f | |
|
pickupLat
|
Float | 24.675 | |
|
pickupLon
|
Float | 46.67 | |
|
dropoffLat
|
Float | 24.736 | |
|
dropoffLon
|
Float | 46.817 | |
|
distanceInMiles
|
Float | 11.185 | |
|
tripTimeInSeconds
|
Integer | 1133 | |
|
priceItems
|
String | [{"itemType":0,"price":46.42,"priceLabel":"46.42 SAR","pr... | |
|
driverId
|
String | 13e2493a84eb2e9823847332e874e172 |
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Frequently asked questions
What is Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets?
High-definition SKU-level transaction data on a per transactional level for the e-commerce industry across emerging markets.
What is Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets used for?
This product has 5 key use cases. Measurable AI recommends using the data for Hedge Funds, Market Research, Business Intelligence (BI), Competitive Intelligence, and Market Share Analysis. Global businesses and organizations buy Ecommerce Data from Measurable AI to fuel their analytics and enrichment.
Who can use Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Ecommerce 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 Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets cover?
This product includes data covering 24 countries like USA, Japan, Germany, India, and United Kingdom. Measurable AI is headquartered in Hong Kong.
How much does Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets cost?
Pricing information for Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets 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 Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets?
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 Granular SKU-Level Transaction Data Global Ecommerce Transactional Data for Emerging Markets?
This Tabular Data has 3 related products. These alternatives include Granular Consumer Transaction Data Ecommerce Data for Emerging Markets, Gener8 SKU-Level Transaction/ Receipt Data 27M+ Transactions & 140+ Global and UK Retailers GDPR-Compliant, 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 Ecommerce Data providers and products via Datarade’s data marketplace and get the right data for your use case.
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Transactional e-receipts data for emerging markets
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