Retail Purchase Transaction Records

This dataset provides granular, item-level retail purchase transaction records, including customer, product, store, and payment details. It is ideal for mining sales patterns, segmenting customers, powering recommendation systems, and forecasting demand across retail locations. The schema supports robust analytics for operational and strategic retail decision-making.

  • last updated 21 Jul 2025
  • by GoMask
The brief that made it

Sales pattern mining and trend analysis

Sample rows

preview · 8 of 200 rows · all 20 columns
transaction_idstringtransaction_statusstringunit_pricefloatcustomer_loyalty_tierstringtransaction_datetimedatetimestore_idstringstore_namestringcustomer_idstringproduct_idstringproduct_namestringproduct_categorystringquantityintegertotal_amountfloatdiscount_amountfloatpayment_methodstringcashier_idstringstore_citystringstore_statestringstore_postal_codestringstore_countrystring
TXN000001completed799.99Gold2023-01-01T10:25:11STR00001MetroMart DowntownCUST001PROD000014K Ultra TV 55inElectronics1749.9950credit_cardCSH0001ChicagoIL60616USA
TXN000002completed4.29Silver2022-12-25T15:00:43STR00002MetroMart SuburbsCUST002PROD00002Organic Milk 1galDairy28.580debit_cardCSH0002NapervilleIL60540USA
TXN000003completed79.99Platinum2023-07-04T18:42:19STR00003Seattle Urban MarketCUST003PROD00003Bluetooth SpeakerElectronics163.9916mobile_paymentCSH0003SeattleWA98101USA
TXN000004completed2.49Gold2023-12-31T23:59:59STR00004London City MarketCUST004PROD00004Artisan BaguetteBakery49.960credit_cardCSH0004LondonLDNE1 6ANUK
TXN000005completed59.99Bronze2023-11-24T13:20:05STR00005Madrid Fresh FoodsCUST005PROD00005Jamón IbéricoGourmet153.996cashCSH0005MadridMD28001Spain
TXN000006completed5.99Silver2023-07-04T14:12:33STR00001MetroMart DowntownCUST006PROD00006Organic Eggs DozenDairy15.990credit_cardCSH0006ChicagoIL60616USA
TXN000007completed16.99Gold2023-02-14T19:30:47STR00006Seoul Express MartCUST007PROD00007Kimchi Jar 2LWorld Foods233.980mobile_paymentCSH0007SeoulKR-1104524South Korea
TXN000008completed7.49Silver2023-03-17T08:45:22STR00007Vancouver OrganicsCUST008PROD00008Gluten-Free GranolaHealth Foods322.470debit_cardCSH0008VancouverBCV5K0A1Canada

What the 200 rows show

from the 200-row sample
  • 9.0median unit_price
  • 5store countries
  • 6payment methods
  • 14product categories
  • 16store cities
  • 18store states
transaction_status200 rows by value
0100200193completed97%4refunded2%3cancelled2%
unit_price200 rows, in bands of 100
09519018852011030400800unit_price →

Median 9.0, from 1.1 to 800.0.

customer_loyalty_tier190 rows with a value · 10 left blank
  1. Silver66
  2. Gold57
  3. Platinum35
  4. Bronze32
20 columns by typefrom the column list below
  • string 15
  • integer 1
  • float 3
  • datetime 1

Columns

20 columns in three groups
blueprint · 20 columns
columntypedescriptionexample
Text 15 columns
transaction_idstringUnique identifier for each purchase transactionuniqueTXN000001
store_idstringUnique identifier for the retail store where the transaction occurredSTR00001
store_namestringName of the retail storeoptionalMetroMart Downtown
customer_idstringUnique identifier for the customer making the purchaseCUST001
customer_loyalty_tierstringLoyalty program tier or segment for the customer (e.g., Silver, Gold, Platinum)Bronze · Silver · Gold · Platinum · optionalGold
product_idstringUnique identifier for the product purchasedPROD00001
product_namestringName or description of the purchased productoptional4K Ultra TV 55in
product_categorystringCategory or department of the purchased productoptionalElectronics
payment_methodstringPayment method used for the transaction6 valuescredit_card
cashier_idstringUnique identifier for the cashier processing the transactionoptionalCSH0001
transaction_statusstringStatus of the transaction (e.g., completed, refunded, cancelled)completed · refunded · cancelledcompleted
store_citystringCity where the retail store is locatedoptionalChicago
store_statestringState or province where the retail store is locatedoptionalIL
store_postal_codestringPostal or ZIP code of the retail storeoptional60616
store_countrystringCountry where the retail store is located5 countries · optionalUSA
Numbers 4 columns
quantityintegerNumber of units of the product purchased in the transaction1 or more1
unit_pricefloatPrice per single unit of the product at the time of transaction0 or more799.99
total_amountfloatTotal amount paid for the product(s) in this transaction (quantity * unit_price, minus discounts)0 or more749.99
discount_amountfloatTotal discount applied to this transaction (if any)0 or more · optional50
Dates and times 1 column
transaction_datetimedatetimeDate and time when the transaction was completed2023-01-01T10:25:11

Use it for

  • median unit pr…9.0200 rowsmean unit price by tr…38.0comple…26.2refund…44.2cancel…

    An e-commerce dashboard

    Unit_price by transaction_status and a breakdown of customer_loyalty_tier. Excel, Power BI or Tableau.

  • What pattern can you find in 200 rows?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable transactions with transaction_datetime, store_id and store_name to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 20 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows20 columns
Yours1,000 rows20 columnsstore_city: UK only

blueprint · retail-purchase-transaction-records

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row is a unique purchase transaction.
  • Fields include timestamp, store ID, product ID, customer segment, and amount.
  • No transactions with negative prices.
  • Returned items are captured with a flag.
Rows
Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
retail-purchase-transaction-records

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