Order History

This dataset provides a detailed record of customer purchase histories, including order metadata, item-level details, shipping and tracking information, and customer lifetime value metrics. It enables comprehensive analysis of purchasing behavior, order fulfillment, and customer value for e-commerce businesses. The data is structured for easy integration with analytics platforms and supports advanced segmentation and forecasting.

  • opened 7 times
  • last updated 29 Oct 2025
  • by GoMask
The brief that made it

Customer lifetime value analysis and segmentation

Sample rows

preview · 8 of 200 rows · all 23 columns
order_idstringpayment_methodstringcustomer_lifetime_valuefloatis_first_orderbooleanshipping_carrierstringcustomer_idstringcustomer_emailstringorder_datedatetimeorder_statusstringtotal_amountfloatcurrencystringshipping_street_addressstringshipping_citystringshipping_statestringshipping_postal_codestringshipping_countrystringtracking_numberstringitem_idstringitem_namestringitem_skustringitem_quantityintegeritem_pricefloatorder_notesstring
ORD00001credit_card389.09falseUPSCUST001maria.jones@gmail.com2022-09-14T15:23:44delivered124.98USD4126 Elm StBostonMA02118USAUPS02118US1234ITEM1001Wireless MouseSKU-WM-4126262.49Leave at back door
ORD00002debit_card2421falseSF ExpressCUST002li.zhao@163.com2023-01-05T10:18:27shipped489CNY88 Jiangsu RdShanghaiJiangsu200052ChinaSF200052CN7890ITEM1002Smartphone StandSKU-SS-88JS1489blank
ORD00003bank_transfer216.45falseDHLCUST003lucas.schmidt@web.de2023-11-22T12:04:15delivered43.25EURSteinstraße 53BerlinBerlin10119GermanyDHL10119DE4321ITEM1003Yoga MatSKU-YM-ST53143.25Gift wrap please
ORD00004bank_transfer19864falseblankCUST004anita.patel@yahoo.in2024-02-02T18:41:03processing1329INR5 MG RoadMumbaiMaharashtra400001IndiablankITEM1004Laptop StandSKU-LS-5MG11329blank
ORD00005paypal297.5trueUSPSCUST005thomas.brown@hotmail.com2023-06-17T09:22:51delivered297.5USD3371 Ridge AveDallasTX75204USAUSPS75204US3371ITEM1005Bluetooth HeadphonesSKU-BH-3371RA1297.5blank
ORD00006credit_card228.76falseLa PosteCUST006caroline.garcia@orange.fr2022-12-11T16:56:38returned59.99EUR126 Rue LafayetteParisIle-de-France75009FranceLAP75009FRG126ITEM1006Coffee Mug SetSKU-CM-RL126159.99Wrong color, please refund
ORD00007other23.77falseblankCUST007eva.hernandez@gmail.com2024-04-09T11:35:50pending0.01EURAvenida de America 7MadridMadrid28002SpainblankITEM1007Promotional Penblank10.01Sample order
ORD00008debit_card352.8falseInPostCUST008igor.kowalski@mail.pl2023-02-12T13:17:11delivered69.9PLNul. Piekna 2WarsawMazowieckie00-549PolandINP00549PLK2ITEM1008Book: Data Science 101SKU-DS-PIEK2169.9blank

What the 200 rows show

from the 200-row sample

Bank_transfer (payment method) stands out: mean customer_lifetime_value is 9,053, against 560.1 for the rest.

  • 19%is_first_order = true
  • 216.5median customer_lifetime_value
  • 6order statuses
  • 7currencies
  • 12shipping countries
  • 78.7median total_amount
Mean customer_lifetime_value by payment_method200 rows
05,00010k408.4credi…60 rows585.6debit…47 rows303.8paypal21 rows9,053bank_…42 rows2,479cash_…12 rows18.9other18 rows
customer_lifetime_value200 rows, in bands of 10k
09519018842321030k60kcustomer_lifetime_value →

Median 216.5, from 0.0 to 52,780.

shipping_carrier149 rows with a value · 51 left blank
  1. DHL24
  2. Correos19
  3. UPS17
  4. La Poste14
  5. FedEx14
  6. InPost13
  7. Swiss Post13
  8. USPS10
  9. JD Logistics8
  10. SF Express7
23 columns by typefrom the column list below
  • string 17
  • integer 1
  • float 3
  • datetime 1
  • boolean 1

Columns

23 columns in four groups
blueprint · 23 columns
columntypedescriptionexample
Text 17 columns
order_idstringUnique identifier for each orderuniqueORD00001
customer_idstringUnique identifier for the customer who placed the orderCUST001
customer_emailstringEmail address of the customermaria.jones@gmail.com
order_statusstringCurrent status of the order6 valuesdelivered
currencystringCurrency code for the order amount (ISO 4217)7 currenciesUSD
payment_methodstringMethod used for payment6 valuescredit_card
shipping_street_addressstringStreet address for shipping4126 Elm St
shipping_citystringCity for shipping addressBoston
shipping_statestringState or province for shipping addressoptionalMA
shipping_postal_codestringPostal or ZIP code for shipping address02118
shipping_countrystringCountry for shipping address12 countriesUSA
tracking_numberstringShipping carrier tracking numberoptionalUPS02118US1234
shipping_carrierstringName of the shipping carrieroptionalUPS
item_idstringUnique identifier for the item in the orderITEM1001
item_namestringName or description of the itemWireless Mouse
item_skustringStock Keeping Unit code for the itemoptionalSKU-WM-4126
order_notesstringAdditional notes or instructions for the orderoptionalLeave at back door
Numbers 4 columns
total_amountfloatTotal monetary value of the order0 or more124.98
item_quantityintegerQuantity of the item ordered1 or more2
item_pricefloatUnit price of the item at time of order0 or more62.49
customer_lifetime_valuefloatCalculated lifetime value of the customer at time of order0 or more · optional389.09
Dates and times 1 column
order_datedatetimeDate and time when the order was placed2022-09-14T15:23:44
True or false 1 column
is_first_orderbooleanIndicates if this is the customer's first orderoptionalfalse

Use it for

  • is first order19%37 of 200 rowsmean customer lifetim…408.4cred…585.6debi…303.8payp…9.1kbank…

    An e-commerce dashboard

    The is_first_order rate, customer_lifetime_value by payment_method and a breakdown of shipping_carrier. Excel, Power BI or Tableau.

  • Why do the 42 bank_transfer rows have a mean customer_lifetime_value of 9,053?

    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 orders with customer_id, customer_email and order_date to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 23 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 rows23 columns
Yours1,000 rows23 columnsshipping_street_address: UK only

blueprint · order-history

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 23 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
  • Order number unique per order
  • Order date and shipping date
  • Shipping address may differ from billing
  • Order status: pending, shipped, delivered, returned
  • Customer lifetime value accumulates orders
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
order-history

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