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Fi is the AI agent inside Definite. Tell it what you’re trying to understand, and it connects your sources, defines the metrics, and builds the dashboard. One conversation, not a project.
Here’s what’s in it
The top row leads with the 4 numbers that matter most: Churned MRR, Logo churn rate, Contraction MRR, Gross revenue churn. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Churned MRR over time, Churned customers trend) show how the headline numbers have moved over time. A breakdown (Churned MRR by reason) splits the metric by dimension so you can see what's driving the total. A detail table (Churn and retention) rounds it out with the secondary metrics and their deltas. Every number is computed from the exact formulas shown in the metric table below. Composites are derived from their components, not pasted in, so the KPI tiles, breakdowns, and totals all reconcile to each other.
Churned MRR
Data ▾
| Period | Churned MRR |
|---|---|
| Jan | $12K |
| Feb | $9K |
| Mar | $13K |
| Apr | $12K |
| May | $10K |
| Jun | $12K |
| Jul | $12K |
| Aug | $10K |
| Sep | $15K |
| Oct | $11K |
| Nov | $16K |
| Dec | $16K |
Logo churn rate
Data ▾
| Period | Logo Churn |
|---|---|
| Jan | 1.6% |
| Feb | 1.5% |
| Mar | 1.5% |
| Apr | 1.7% |
| May | 1.8% |
| Jun | 1.4% |
| Jul | 1.5% |
| Aug | 1.3% |
| Sep | 1.4% |
| Oct | 1.5% |
| Nov | 1.6% |
| Dec | 1.4% |
Contraction MRR
Data ▾
| Period | Contraction MRR |
|---|---|
| Jan | $4K |
| Feb | $5K |
| Mar | $6K |
| Apr | $5K |
| May | $5K |
| Jun | $6K |
| Jul | $4K |
| Aug | $6K |
| Sep | $5K |
| Oct | $6K |
| Nov | $5K |
| Dec | $5K |
Gross revenue churn
Data ▾
| Period | Gross Revenue Churn |
|---|---|
| Jan | $15K |
| Feb | $14K |
| Mar | $18K |
| Apr | $17K |
| May | $14K |
| Jun | $18K |
| Jul | $16K |
| Aug | $16K |
| Sep | $20K |
| Oct | $17K |
| Nov | $21K |
| Dec | $21K |
Churned MRR over time
Data ▾
| Period | Churned MRR |
|---|---|
| Jan | $12K |
| Feb | $9K |
| Mar | $13K |
| Apr | $12K |
| May | $10K |
| Jun | $12K |
| Jul | $12K |
| Aug | $10K |
| Sep | $15K |
| Oct | $11K |
| Nov | $16K |
| Dec | $16K |
Churned MRR by reason
Data ▾
| Reason | Churned MRR |
|---|---|
| Price | $3K |
| Product fit | $4K |
| Competitor | $3K |
| Churned silently | $5K |
Churned customers trend
Data ▾
| Period | Churned Customers |
|---|---|
| Jan | 21 |
| Feb | 20 |
| Mar | 21 |
| Apr | 25 |
| May | 28 |
| Jun | 25 |
| Jul | 28 |
| Aug | 24 |
| Sep | 28 |
| Oct | 33 |
| Nov | 37 |
| Dec | 35 |
Churn and retention
- Why did churn spike in March?
- Which segment has the highest logo churn, and is it the same one with the highest revenue churn?
- Show me the accounts that churned last month and what they had in common.
- What is our churn rate if I exclude the seasonal segment?
- Break churned MRR out by plan instead of segment.
- Trace the March churn back to the canceled subscriptions in Stripe.
- Break churned MRR by reason and show which reason is growing fastest.
- Show logo churn versus revenue churn side by side so I can see if small accounts or large accounts are leaving.
- Add contraction MRR separately so I can see downgrades distinct from full exits.
Every metric traces back to your systems
This is the part a BI tool can’t fake. Each metric is defined once, in your warehouse, from a specific object in a specific source. Change the definition in one place and every tile, report, and answer moves with it. So the number on the screen is the number in the source.
| Metric | What it measures | How it's calculated | Sources |
|---|---|---|---|
| Logo Churn | The share of customers who left this month, counted by logo rather than by dollars. | Churned Customers ÷ prior Customers | Stripe |
| Gross Revenue Churn | Recurring revenue lost to downgrades and cancellations, before any offsetting expansion. | Contraction MRR + Churned MRR | Stripe |
| Gross Revenue Retention | The share of recurring revenue you'd retain with zero expansion, the floor under the base once upsell is stripped out. | (prior MRR − Contraction MRR − Churned MRR) ÷ prior MRR | Stripe |
| Net Revenue Retention | The clearest read on whether the product keeps earning its price: how much revenue this year's cohort of customers is worth versus last year, after expansion, contraction, and churn net out. | (prior MRR + Expansion MRR − Contraction MRR − Churned MRR) ÷ prior MRR | Stripe |
Have our agent watch for you
A churn dashboard tells you what happened, and Fi tells you why. The last step is not having to remember to check. Point Definite at the one number you can’t afford to miss, and it watches that number for you off the same definitions as your dashboard. When it moves, you hear about it before the next review instead of during it. One metric, one action, always reversible.
Built from whatever you already run on
Connect the systems you already use. Any source of these types works, and you don’t move data into a warehouse, because Definite is the warehouse.
No warehouse to stand up or connect. See how the platform models your data →
Build your churn dashboard
From signup to a working dashboard in one sitting. No data team required.
Connect your sources
Stripe, your CRM, accounting. Definite syncs and models them automatically.
Decide your metrics
Pick the numbers that matter or let Fi propose them from your data. Every metric gets one definition, governed in one place.
Ask Fi to build it
Describe what you need in plain language. Fi builds the dashboard, and you refine by asking follow-ups.