2,500 rows · 10 columns

SaaS subscriptions

Twenty-five hundred B2B subscription accounts with signup dates, plans, seat counts, MRR and churn dates. Built for cohort retention, survival analysis, and expansion-revenue maths.

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What is in it, and what is wrong with it

churned_at is empty for accounts that are still alive at the end of the observation window. That is right-censoring, and treating those blanks as "did not churn" will make your retention numbers optimistic. Churn hazard is highest in months 2–4 and decays after that, which is what most real self-serve products look like.

Schema

Column	Type	Description
account_id	string	Account identifier.
signed_up_on	date	First paid day.
plan	category	starter, team, business, or enterprise.
seats	integer	Seats at signup.
seats_now	integer	Seats at last observation (expansion or contraction).
mrr_usd	float	Monthly recurring revenue at last observation.
region	category	AMER, EMEA, APAC, LATAM.
industry	category	Self-reported industry.
channel	category	Acquisition channel.
churned_at	date	Cancellation date, or empty if still active.

First twelve rows

account_id	signed_up_on	plan	seats	seats_now	mrr_usd	region	industry
A22285	2023-01-04	starter	1	1	12.5	AMER	public sector
A20496	2023-01-06	starter	4	4	52.63	AMER	public sector
A21540	2023-01-06	team	24	27	282.33	EMEA	education
A22296	2023-01-07	starter	2	2	27.24	EMEA	media
A20104	2023-01-10	starter	2	2	25	EMEA	software
A20134	2023-01-11	team	20	21	198.38	APAC	healthcare
A20208	2023-01-13	team	18	21	228.93	EMEA	healthcare
A21104	2023-01-13	team	19	16	154.96	AMER	software
A20760	2023-01-14	team	14	14	151.04	APAC	public sector
A20174	2023-01-17	business	81	122	1050.9	EMEA	public sector
A20329	2023-01-17	starter	4	3	41.23	AMER	software
A20540	2023-01-19	starter	2	2	23.82	EMEA	public sector

Showing the first 8 of 10 columns. Open the full table in the Explorer.

Grain

One row per account.

Things to try

Draw a cohort retention triangle by signup month.
Compute net revenue retention, including expansion from seat growth.
Fit a Kaplan–Meier curve and compare plans — mind the censoring.
Which acquisition channel produces the highest 12-month LTV?

Load it

python

import pandas as pd

df = pd.read_csv(
  "https://datanemics.com/datasets/data/saas-subscriptions.csv"
)

Licence

Public domain, CC0 1.0. Synthetic data — no attribution required.