accounts
11,154 rows
- idtext · key
- nametext
- domaintext
- lead_sourcetext
- created_attime
A hose dataset · vertical
A SaaS whose MRR you can audit down to the invoice.
Trials, seats, invoices, declined cards and the retries that save some of them. Every metric is derived from the rows, none is stored.
2,696,399 rows · last row moments ago
The receipt
- seed
- 42
- scale
- 40
- start
- 2023-01-01
- fingerprint
- 8c84ed70186e
- license
- MIT
The whole dataset grows from this one seed. Everyone who downloads it gets the same rows with the same ids, today and next month, so whatever you build on it keeps working after the data refreshes.
App Events per day, last 90 days
Schema · 8 tables
users
16,508 rows
- idtext · key
- account_idtext
- nametext
- emailtext
- created_attime
- deactivated_attime
plans
6 rows
- idtext · key
- nametext
- seat_price_usd_monthreal
- seat_price_usd_yearreal
subscriptions
11,154 rows
- idtext · key
- account_idtext
- plan_idtext
- billingtext
- seatsint
- trial_ends_attime
- activated_attime
- canceled_attime
subscription_events
24,720 rows
- idtext · key
- subscription_idtext
- attime
- kindtext
- plan_idtext
- seatsint
- reasontext
invoices
18,015 rows
- idtext · key
- subscription_idtext
- period_starttime
- period_endtime
- amount_usdreal
- issued_attime
- statustext
- paid_attime
payments
23,131 rows
- idtext · key
- invoice_idtext
- attime
- outcometext
app_events
2,591,711 rows
- idtext · key
- user_idtext
- attime
- nametext
What the data claims
- Churn front-loads: the first three months are twice as dangerous as the back half of the year.
- One invoice in twelve fails on the first attempt. Dunning recovers about half.
- Annual cohorts retain more than 100% of their revenue while losing accounts.
- In year three the company raises prices, and you can watch it land.
- Usage decays in the weeks before a voluntary cancel.
Why this one
Every SaaS metrics guide explains MRR, net revenue retention and dunning with a chart, and none of them includes the table the chart came from. Quenchly is that table. It is a mid-market team-workflow product on per-seat plans, generated by hose as an operational billing schema: accounts, users, a price book, subscriptions with their change log, invoices, payment attempts, and raw product events.
Nothing is pre-aggregated. MRR is live subscriptions times seats times
the plan price. Churn splits into requested and payment-failure
cancels because the cancel event records the reason. Dunning
recovery is an invoice whose successful payment was not its first.
Daily active users come from app_events, the way they would from a
real analytics export.
The business has a history. Trials convert at about one in five and open a 14-day window. Churn front-loads into the first quarter of a subscription and settles near two percent a month. Usage falls in the weeks before a voluntary cancel, not after it. In its third year the company raises prices. The price book gains new rows and renewals migrate to them. Annual signups rush in during the month before. The same seed regenerates all of it, byte for byte.
The other datasets