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Headcount
Live Users

Live Users

The count of active, billable user seats on live (revenue-generating) subscriptions at a point in time — the paying headcount of your customer base.

Count

Formula

Live Users=Starting Live Users+New Live Users+Upsell Live UsersChurned Live UsersDownsell Live Users\text{Live Users} = \text{Starting Live Users} + \text{New Live Users} + \text{Upsell Live Users} - \text{Churned Live Users} - \text{Downsell Live Users}

Built from

What it measures

The sum of every active, billable seat assigned to a live, revenue-generating contract at a point in time. Trial seats, suspended licenses, freemium access, and read-only logins are excluded — only seats on contracts actively billing count. Built as a waterfall: prior period balance plus inflows (new-logo activation seats and expansion seats) minus outflows (churn and downsell). Each contract contributes its seat count only for the months it is live and generating revenue.

Why it matters

Live Users is the paying-seat depth gauge of your customer base. Total Logos tells you how many live customers you have; Live Users tells you how deeply each has been deployed on a contract that is actually billing. You use it to measure seat-based land-and-expand within the live revenue base, separate genuine adoption from licenses merely issued, and forecast seat-priced revenue. Boards watch it because Live Users rising alongside Live ARR signals durable stickiness and expansion momentum, while Live Users rising faster than Total Logos signals existing customers deepening their footprint. Finance pairs it with ARPU to model seat-pricing unit economics.

How to read it

Read Live Users as a trend against Total Logos, never as a lone snapshot. Divide Live Users by Total Logos to get average adoption per customer: 3,260 users over 815 logos is 4 seats each. If Live Users grow 15% while logos grow 5%, your existing customers are expanding their footprint — bullish. If logos grow faster than users, you are landing customers at thin seat counts and land-and-expand is weak. Always pair with ARPU: rising users with falling ARPU means you are adding lower-value or lower-tier seats. And always break the move into its five components — flat Live Users can hide strong new-logo activation being fully offset by deep churn, signaling a leaky base even when the headline looks stable.

What good looks like

Good

Live Users grow every month and grow faster than Total Logos — expansion is layering seats onto live contracts, driving land-and-expand traction with adoption deepening across the base.

Watch

Live Users grow in lockstep with Total Logos, or stall — either new customers land lean with few initial seats, or existing customers are not expanding their live seat count over time.

Bad

Live Users shrink or flatten while Total Logos grow — new live logos are thinner than the seats churned or downsold, signaling weakening product stickiness or adoption velocity.

Watch-outs

  • Counting trial, freemium, or suspended seats as Live Users. Only seats on active, billable, revenue-generating contracts count. Including trials, frozen licenses, or seats on inactive contracts inflates the base, overstates ARPU, and breaks alignment with Live ARR.
  • Confusing Live Users with Monthly Active Users (MAU) or Daily Active Users (DAU). Live Users is a billing seat count — every subscribed seat at period end, login or not. MAU and DAU count users who actually engaged. You might have 3,260 Live Users but only 2,400 MAU. Use Live Users for revenue forecasting and unit economics; use MAU/DAU for engagement.
  • Double-counting during contract transitions. When a customer moves from an old contract to a new one (renewal with a term or tier change), count seats only on the active contract as of month-end, never both — avoid the cliff effect.
  • Treating the snapshot as an average. Period-end Live Users will not equal the average of daily counts when churn or expansion is lumpy mid-month. Always use period-end for consistency; if you report an average, label it and compute it the same way every month.
  • Ignoring the live-vs-total variance. If Live Users and Total Users diverge sharply, you have a backlog of underutilized or suspended seats — a sign of onboarding friction, weak adoption, or billing hygiene gaps. Track the gap and investigate.

Worked example

Hypothetical

Live Users=3,200+45+35182=3,260\text{Live Users} = 3{,}200 + 45 + 35 - 18 - 2 = 3{,}260

Open January with 3,200 Live Users across your live logos. During January, 15 new contracts activate with 45 seats (+45), existing live customers add 35 expansion seats (+35), two live contracts churn losing 18 seats (−18), and one live customer downsells from 6 to 4 seats (−2). Closing Live Users is 3,260.

Variants & windows

The same metric re-expressed by a mechanical transform — a trailing window, a growth rate, a per-unit scaling, or a book/segment cut. Each is computed from Live Users above.

  • Contracted Users Contracted book
  • Contracted Users Growth Rate Growth rate · Contracted book
  • Contracted Users Growth Rate (T3M) Growth rate · Trailing 3-month · Contracted book
  • Contracted Users TTM Growth Rate Growth rate · Trailing 12-month · Contracted book
  • CONTRACTED_USERS_PERCENTAGE As a percentage · Contracted book
  • Users Growth Rate Growth rate
  • Users Growth Rate (T3M) Growth rate · Trailing 3-month
  • Users Growth Rate (TTM) Growth rate · Trailing 12-month
  • USERS_PERCENTAGE As a percentage

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