SaaS

Account

Every customer account (a company), with the signals that frame the whole relationship: industry, size and region, the plan tier they are on, a revenue size band, the channel that acquired them, their success-manager owner, a product-health score, and where they sit in the lifecycle (trial, active, at-risk, churned). The dimension you slice the entire business by. What each acquisition channel costs is in Marketing Spend.

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Invoices

Every invoice and how it was paid — amount, tax, discounts and credits, payment status, and where it sits in the dunning cycle when a payment fails. This is where voluntary revenue meets involuntary churn: failed payments and collections stages that quietly erode the customer base.

This is the model's revenue mart, and it carries two figures on purpose: amount is what was billed on every invoice regardless of outcome, and net_amount is what was actually recognised — zero for a voided or written-off invoice, equal to amount otherwise. Any revenue total should sum net_amount, never amount. The four collection signals — status, dunning_stage, is_failed and paid_at — always agree with each other: a paid invoice always has a paid_at and never is_failed or a write-off, and is_write_off is exactly dunning_stage = 'write_off'.

Fields

SAFE_DIVIDE(COUNTIF(is_failed), COUNT(invoice_id))

Relationships

Marketing Spend

Marketing investment by channel, campaign and day — cost, leads, and signups — attributed to the cohort of accounts each channel brings in rather than to individual accounts. The numerator and denominator of customer acquisition cost, and the starting point for payback analysis.

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SAFE_DIVIDE(SUM(cost), SUM(signups))

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Plan

The price book: every sellable plan and price point — four tiers (Starter, Pro, Business, Enterprise), each offered monthly or annually, with its list price and whether it is currently sellable. The reference that gives every subscription its list pricing.

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Subscription

The billing spine: one row per subscription showing which account is on which plan, at what monthly recurring revenue and seat count, on what cadence, and with any negotiated discount. It also reveals which subscriptions stay on a plan one tier below the account's under grandfathered pricing. The source of truth for what each customer pays today.

Fields

SAFE_DIVIDE(SUM(active_mrr), COUNT(DISTINCT IF(active_mrr > 0, account_id, NULL)))

CASE WHEN discount_pct IS NULL OR discount_pct = 0 THEN 'List price' WHEN discount_pct < 0.12 THEN 'Light (5-11%)' WHEN discount_pct < 0.19 THEN 'Moderate (12-18%)' ELSE 'Deep (19%+)' END

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Subscription Events

The movement history behind recurring revenue: one row per subscription change — new, expansion, contraction, reactivation, or churn — with the signed revenue and seat deltas and the running revenue after each change. This is what reconstructs the revenue waterfall and the retention rates the business lives or dies by.

Running revenue reconciles with each subscription's own contracted rate. A subscription still on the books finishes the series on that rate; a subscription that churned was carrying it in the period immediately before the churn and the series steps away from it — so a churn reads as revenue lost from a customer's full rate, not as a downgrade on the way up to it.

Fields

SUM(IF(event_type IN ('new', 'expansion', 'reactivation'), mrr_delta, 0))

-SUM(IF(event_type IN ('contraction', 'churn'), mrr_delta, 0))

mrr_gained - mrr_lost

SAFE_DIVIDE(mrr_gained, mrr_lost)

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Support Tickets

Every support interaction — priority, topic, satisfaction score, time to first response, and resolution time. Support experience is an early churn-risk signal: unhappy, slow-to-resolve accounts are the ones that quietly leave — read it beside how much they use the product, in Usage (daily).

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Trials

Every trial and how it ended — converted to paid or not — with when it started and expired, where it came from (self-serve, sales-assisted, product-led upsell), and the plan it was evaluating. The top of the funnel for new recurring revenue.

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Usage (daily)

Daily product engagement at the account-and-user level: active minutes, high-value actions taken, and how many distinct features were touched — the breadth signal for activation. The behavioral pulse that explains why accounts expand, stall, or churn.

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User

The people inside each account: one row per user seat, with role, seat type, when they were invited, and how recently they were active. Seat-level activity is what turns a licensed account into an adopted one — and idle seats are early signs of shrinking value.

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Relationships