• Other
  • 18 columns
  • 200 rows
  • 8 formats

Small Retailer Sales Transactions

This dataset provides detailed transaction-level sales data from small local retailers, including product, payment, and retailer information. It enables comprehensive analysis of sales trends, business performance, and consumer behavior, supporting decision-making for retail operations and market research.

  • opened 6 times
  • last updated 5 Sept 2025
  • by GoMask
The brief that made it

Sales trend analysis for small retailers

Sample rows

preview · 8 of 200 rows · all 18 columns
transaction_idstringretailer_countrystringunit_pricefloatis_refundedbooleanretailer_postal_codestringtransaction_datedatetimeretailer_idstringretailer_namestringretailer_street_addressstringretailer_citystringretailer_statestringproduct_idstringproduct_namestringproduct_categorystringquantityintegertotal_amountfloatpayment_methodstringcustomer_idstring
TXN00001USA3.99false606012024-03-05T09:14:23R001SuperMart Downtown123 Main StChicagoILP0001Organic Milk GallonGrocery27.98debit_cardC10001
TXN00002USA89.99false981012024-03-05T10:22:41R002ElectroHub98 Elm AveSeattleWAP0002Bluetooth HeadphonesElectronics189.99credit_cardC10002
TXN00003USA42.5false100012024-03-05T18:10:10R003Fashionista45 Oak StNew YorkNYP0003Summer DressApparel142.5mobile_paymentC10003
TXN00004USA7.99false328012024-03-06T08:59:57R004HealthStuff Pharmacy200 Pine AveOrlandoFLP0004Vitamin C TabletsHealth323.97cashblank
TXN00005USA4.25false941052024-03-06T16:30:45R005Urban Supplies500 Market StSan FranciscoCAP0005Kitchen Towels PackHousehold28.5debit_cardC10004
TXN00006USA699.99false787012024-03-07T20:05:01R006TechWorld77 Tech BlvdAustinTXP0006Smartphone X20Electronics1699.99credit_cardC10005
TXN00007UK12.99falseSW1A 1AA2024-03-08T12:11:11R007Happy Home16 Queens RdLondonENGP0007Scented Candles SetHousehold451.96otherblank
TXN00008USA14.5false021112024-03-08T15:27:36R008BookBarn22 Library RdBostonMAP0008Mystery NovelBooks114.5credit_cardC10006

What the 200 rows show

from the 200-row sample

Germany (retailer country) stands out: mean unit_price is 198.8, against 22.1 for the rest.

  • 5%is_refunded = true
  • 12.0median unit_price
  • 5payment methods
  • 8product categories
  • 11retailer states
  • 12retailers
Mean unit_price by retailer_country200 rows
010020025.4USA143 rows198.8Germany23 rows4.0Canada19 rows13.3UK15 rows
unit_price200 rows, in bands of 200
0100200195112000108001,600unit_price →

Median 12.0, from 0.59 to 1,500.

retailer_postal_code200 rows · top 10 of 35 values
  1. 9810113
  2. 8020211
  3. 1011710
  4. M5V 1K410
  5. 7520110
  6. W1A 1AA8
  7. 328017
  8. 787017
  9. SW1A 1AA7
  10. 802047
18 columns by typefrom the column list below
  • string 13
  • integer 1
  • float 2
  • datetime 1
  • boolean 1

Columns

18 columns in four groups
blueprint · 18 columns
columntypedescriptionexample
Text 13 columns
transaction_idstringUnique identifier for each sales transactionuniqueTXN00001
retailer_idstringUnique identifier for the retailer where the transaction took place12 retailersR001
retailer_namestringName of the retailerSuperMart Downtown
retailer_street_addressstringStreet address of the retailer locationoptional123 Main St
retailer_citystringCity where the retailer is locatedoptionalChicago
retailer_statestringState or region where the retailer is located11 states · optionalIL
retailer_postal_codestringPostal or ZIP code of the retaileroptional60601
retailer_countrystringCountry where the retailer is located4 countries · optionalUSA
product_idstringUnique identifier for the product soldP0001
product_namestringName of the product soldOrganic Milk Gallon
product_categorystringCategory or type of the product sold8 categories · optionalGrocery
payment_methodstringMethod of payment used for the transactioncash · credit_card · debit_card · mobile_payment · otherdebit_card
customer_idstringUnique identifier for the customer (if available)optionalC10001
Numbers 3 columns
quantityintegerNumber of units sold in the transaction1 or more2
unit_pricefloatPrice per unit of the product at the time of sale0 or more3.99
total_amountfloatTotal amount for the transaction (quantity * unit_price)0 or more7.98
Dates and times 1 column
transaction_datedatetimeDate and time when the transaction occurred2024-03-05T09:14:23
True or false 1 column
is_refundedbooleanIndicates if the transaction was refundedfalse

Use it for

  • is refunded5%10 of 200 rowsmean unit price by re…25.4USA198.8Germ…4.0Cana…13.3UK

    A dashboard

    The is_refunded rate, unit_price by retailer_country and a breakdown of retailer_postal_code. Excel, Power BI or Tableau.

  • Why do the 23 Germany rows have a mean unit_price of 198.8?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable transactions with transaction_date, retailer_id and retailer_name to fill a screen in front of a buyer.

Not quite right?

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Same 18 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows18 columns
Yours10,000 rows18 columnsretailer_street_address: UK only

blueprint · small-retailer-sales-transactions

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 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
  • Include timestamp and transaction value
  • Segment by product category
  • Flag discount applied
  • Track payment method
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
small-retailer-sales-transactions

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