Sample customer data

Name: Sample customer data
Creator: DataBrighten
License: https://creativecommons.org/publicdomain/zero/1.0/

1,000 × 13rows × columns in the 1,000-row file

Updated 3 November 2026. Fictional U.S. businesses and people, generated with a fixed seed.

CSV XLSX JSON SQL

textnumberdateyes/no

Largest file10,000rows; also 100 and 1,000

Columns13with a data dictionary below

Dates2019-01-03 – 2024-12-28range in the file

LicenceCC0synthetic, free for any use

What is in it

Each row is one fictional customer account: contact details on reserved example domains and 555-01xx numbers, city, signup date, segment, orders so far, lifetime spend and whether they ordered in 2024.

First rows

point at a column to light it up

customer_idtext	first_nametext	last_nametext	emailtext	phonetext	citytext	statetext	signup_datedate	segmenttext	total_ordersnumber	total_spentnumber	last_order_datedate	is_activeyes/no
CU10001	Ryan	Jackson	ryan.jackson0@example.com	(212) 555-0190	Omaha	NE	2019-08-30	Small Business	7	1353	2019-11-23	FALSE
CU10002	Michael	Chen	michael.chen@example.com	(617) 555-0184	Hartford	CT	2019-05-21	Consumer	2	174.9	2024-09-30	TRUE
CU10003	David	Nelson	david.nelson@example.com	(206) 555-0147	Chicago	IL	2024-12-26	Consumer	3	245.05	2024-12-28	TRUE
CU10004	Sofia	Ramirez	sofia.ramirez@example.com	(617) 555-0195	Nashville	TN	2024-04-26	Consumer	2	115.31	2024-12-05	TRUE
CU10005	Laura	Torres	laura.torres@example.com	(305) 555-0176	Charlotte	NC	2023-12-26	Consumer	3	259.43	2024-05-08	TRUE
CU10006	Ryan	Davis	ryan.davis@example.com	(206) 555-0158	Minneapolis	MN	2021-07-03	Consumer	4	264.53	2023-01-26	FALSE
CU10007	Rebecca	Sanchez	rebecca.sanchez@example.com	(305) 555-0179	Atlanta	GA	2024-04-03	Consumer	1	91.5	2024-05-24	TRUE
CU10008	Barbara	Ramirez	barbara.ramirez7@example.com	(512) 555-0113	Austin	TX	2024-04-14	Enterprise	22	14129.96	2024-12-28	TRUE
CU10009	Michael	White	michael.white@example.com	(702) 555-0188	Denver	CO	2019-02-13	Consumer	7	651.35	2023-09-07	FALSE
CU10010	Jennifer	Hill	jennifer.hill@example.com	(212) 555-0167	Los Angeles	CA	2022-05-21	Consumer	3	144.81	2023-10-26	FALSE

Customers by segment

customers, 1,000-row file

Show as a table

segment	value
Consumer	718
Small Business	211
Enterprise	71

Source: DataBrighten synthetic data (seed 42), computed from the file you can download here.

Data dictionary

Column	Type	Meaning
customer_id	text	Customer number
first_name	text	Fictional first name
last_name	text	Fictional last name
email	text	Email (example.com, not real)
phone	text	Fictional number in the 555-01xx range reserved for fiction
city	text	City
state	text	Two-letter state code
signup_date	date	Account created (2019-2024)
segment	text	Consumer, Small Business or Enterprise
total_orders	integer	Orders placed so far
total_spent	decimal	Lifetime spend (USD)
last_order_date	date	Most recent order (blank if none)
is_active	boolean	Ordered in 2024 (TRUE/FALSE)

Practice questions

answers checked in SQL and in Python

How many customers are active (ordered in 2024)?

469 of 1,000

Excel

=COUNTIF(M:M,TRUE)

SQL

SELECT COUNT(*) FROM customers WHERE is_active

File: customers-1000

Average lifetime spend by segment?

Enterprise $13,507.62; Small Business $1,866.74; Consumer $377.45

Excel

=AVERAGEIF(I:I,"Enterprise",K:K)

SQL

SELECT segment, ROUND(AVG(total_spent),2) AS avg_spent FROM customers GROUP BY segment ORDER BY avg_spent DESC

File: customers-1000

Which state has the most customers?

CA (151), TX (123), NY (102)

SQL

SELECT state, COUNT(*) AS n FROM customers GROUP BY state ORDER BY n DESC, state LIMIT 3

File: customers-1000