ClearScore Dataset | UK Consumer Transaction Data | 1.4m users.
# | transaction_reference |
user_id |
user_reference |
age_band |
salary_band |
derived_gender |
account_reference |
provider_group_name |
account_type |
account_balance |
account_created_date |
account_last_refreshed_date |
transaction_date |
transaction_amount |
transaction_description |
credit_debit_flag |
merchant_business_line |
merchant_name |
purpose_tag |
bank_code |
postcode_area |
lsoa_code |
msoa_code |
data_warehouse_created_date |
data_warehouse_updated_date |
insert_update_flag |
merchant_business_line_id |
priority |
min_debit_tolerance |
max_debit_tolerance |
merchant_category |
is_merchant_business_line |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | 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 | Xxxxxxxxxx | Xxxxxx |
3 | 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 |
4 | 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 | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx |
5 | 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 | Xxxxxxx |
6 | 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 |
7 | 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 | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx |
8 | 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 |
9 | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx |
10 | 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 | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
transaction_reference
|
String | e9a70e9e-05e2-4c60-8194-e12c18ea715232AACE064A589C2A2365A... | |
user_id
|
String | 08db3d97-7eab-85e6-d0ed-bf68dc5f89c4 | |
user_reference
|
String | 4684f3b79ab40a79aa51a972af4d17a19e11dec6627be41f2ca1e9981... | |
age_band
|
String | 35-39 | |
salary_band
|
String | 60K to 70K | |
derived_gender
|
Boolean | f | |
account_reference
|
String | e9a70e9e-05e2-4c60-8194-e12c18ea7152 | |
provider_group_name
|
String | HSBC | |
account_type
|
String | Current | |
account_balance
|
Float | 287.41 | |
account_created_date
|
DateTime | 2023-04-15T00:00:00+00:00 | |
account_last_refreshed_date
|
DateTime | 2023-07-13T00:00:00+00:00 | |
transaction_date
|
DateTime | 2022-10-24T00:00:00+00:00 | |
transaction_amount
|
String | £67.50 | |
transaction_description
|
String | iceland foods flintshire | |
credit_debit_flag
|
String | Debit | |
merchant_business_line
|
String | Iceland | |
merchant_name
|
String | Iceland | |
purpose_tag
|
String | Food, Groceries, Household | |
bank_code
|
String | VIS | |
postcode_area
|
String | AL3 5 | |
lsoa_code
|
String | E01023670 | |
msoa_code
|
String | E02004932 | |
data_warehouse_created_date
|
DateTime | 2023-04-15T00:00:00+00:00 | |
data_warehouse_updated_date
|
DateTime | 1900-01-01T00:00:00+00:00 | |
insert_update_flag
|
String | I | |
merchant_business_line_id
|
Integer | 377 | |
priority
|
Integer | 2500 | |
min_debit_tolerance
|
Integer | 0 | |
max_debit_tolerance
|
Integer | 50000 | |
merchant_category
|
String | Supermarket | |
is_merchant_business_line
|
Boolean | t |
Attribute | Type | Example | Mapping |
---|---|---|---|
Age Bucket
|
35 - 39 | ||
Salary Band
|
£24k - £29k | ||
Derived Gender
|
M | ||
String | PR3 1 | Postal Code |
Description
Country Coverage
History
Volume
1.4 million | Users |
1.8 million | Accounts |
Pricing
Suitable Company Sizes
Delivery
Categories
Related Searches
Related Products
Frequently asked questions
What is ClearScore Dataset UK Consumer Transaction Data 1.4m users.?
Analyse spend, consumer loyalty, to granular demography and merchant brand level, for 330+ listed entities and 1.4k+ merchants in the UK & EU. Includes Credit, Debit & Savings in one place to provide a full view of consumer spending. We are not an aggregator, all our data is direct from source.
Who can use ClearScore Dataset UK Consumer Transaction Data 1.4m users.?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Credit Card Data. Get in touch with ClearScore to see what their data can do for your business and find out which integrations they provide.
How far back does the data in ClearScore Dataset UK Consumer Transaction Data 1.4m users. go?
This product has 5 years of historical coverage. It can be delivered on a hourly, daily, weekly, monthly, quarterly, yearly, and on-demand basis.
Which countries does ClearScore Dataset UK Consumer Transaction Data 1.4m users. cover?
This product includes data covering 2 countries like United Kingdom and France. ClearScore is headquartered in United Kingdom.
How much does ClearScore Dataset UK Consumer Transaction Data 1.4m users. cost?
Pricing information for ClearScore Dataset UK Consumer Transaction Data 1.4m users. is available by getting in contact with ClearScore. Connect with ClearScore to get a quote and arrange custom pricing models based on your data requirements.
How can I get ClearScore Dataset UK Consumer Transaction Data 1.4m users.?
Businesses can buy Credit Card Data from ClearScore and get the data via S3 Bucket and SFTP. Depending on your data requirements and subscription budget, ClearScore can deliver this product in .csv format.
What is the data quality of ClearScore Dataset UK Consumer Transaction Data 1.4m users.?
You can compare and assess the data quality of ClearScore using Datarade’s data marketplace. ClearScore appears on selected Datarade top lists ranking the best data providers, including Best Credit & Debit Card Transaction Data Providers: Q1 2023.
What are similar products to ClearScore Dataset UK Consumer Transaction Data 1.4m users.?
This product has 3 related products. These alternatives include Consumer Edge Vision Consumer Transaction Data USA Data 100M+ Credit & Debit Cards, 12K+ Merchants, 800+ Parent Companies, 600+ Tickers, ClearScore Dataset Individual Tickers UK Consumer Transaction Data 1.4m users., and Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India. You can compare the best Credit Card Data providers and products via Datarade’s data marketplace and get the right data for your use case.