Describe your dashboard. Fi builds it.
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: ARR, Net revenue retention, Booked revenue, Pipeline coverage. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (ARR over time, Net new MRR by movement) show how the headline numbers have moved over time. A breakdown (New pipeline by stage) splits the metric by dimension so you can see what's driving the total. A detail table (Sales & marketing return) 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.
ARR
Data ▾
| Period | ARR |
|---|---|
| Jan | $6.92M |
| Feb | $7.40M |
| Mar | $7.86M |
| Apr | $8.40M |
| May | $8.92M |
| Jun | $9.56M |
| Jul | $10.39M |
| Aug | $11.26M |
| Sep | $12.21M |
| Oct | $13.20M |
| Nov | $14.09M |
| Dec | $15.39M |
Net revenue retention
Data ▾
| Period | Net Revenue Retention |
|---|---|
| Jan | 99.1% |
| Feb | 99.8% |
| Mar | 99.9% |
| Apr | 100.3% |
| May | 99.9% |
| Jun | 100.8% |
| Jul | 100.7% |
| Aug | 101.1% |
| Sep | 101.0% |
| Oct | 101.4% |
| Nov | 100.5% |
| Dec | 101.8% |
Booked revenue
Data ▾
| Period | Booked Revenue (Closed Won) |
|---|---|
| Jan | $677K |
| Feb | $810K |
| Mar | $891K |
| Apr | $696K |
| May | $736K |
| Jun | $752K |
| Jul | $1.10M |
| Aug | $1.04M |
| Sep | $1.16M |
| Oct | $1.41M |
| Nov | $1.25M |
| Dec | $1.34M |
Pipeline coverage
Data ▾
| Period | Pipeline Coverage |
|---|---|
| Jan | 8.6× |
| Feb | 8.0× |
| Mar | 7.3× |
| Apr | 8.4× |
| May | 9.0× |
| Jun | 8.3× |
| Jul | 7.9× |
| Aug | 7.8× |
| Sep | 8.1× |
| Oct | 7.3× |
| Nov | 8.0× |
| Dec | 8.5× |
ARR over time
Data ▾
| Period | ARR |
|---|---|
| Jan | $6.92M |
| Feb | $7.40M |
| Mar | $7.86M |
| Apr | $8.40M |
| May | $8.92M |
| Jun | $9.56M |
| Jul | $10.39M |
| Aug | $11.26M |
| Sep | $12.21M |
| Oct | $13.20M |
| Nov | $14.09M |
| Dec | $15.39M |
New pipeline by stage
Data ▾
| Stage | New Pipeline |
|---|---|
| Discovery | $735K |
| Evaluation | $894K |
| Proposal | $1.08M |
| Negotiation | $886K |
Net new MRR by movement
Data ▾
| Period | New MRR | Expansion MRR | Contraction MRR | Churned MRR |
|---|---|---|---|---|
| Jan | $41K | $13K | $6K | $12K |
| Feb | $41K | $16K | $6K | $11K |
| Mar | $39K | $17K | $5K | $12K |
| Apr | $43K | $18K | $6K | $10K |
| May | $44K | $17K | $5K | $13K |
| Jun | $48K | $22K | $6K | $11K |
| Jul | $63K | $21K | $4K | $11K |
| Aug | $63K | $27K | $5K | $12K |
| Sep | $69K | $29K | $5K | $14K |
| Oct | $69K | $34K | $6K | $14K |
| Nov | $68K | $27K | $6K | $16K |
| Dec | $87K | $38K | $4K | $12K |
Sales & marketing return
- Which Salesforce Deal owner is driving the bookings miss this month?
- Is pipeline coverage enough to hit the number if our Salesforce win rate holds?
- Trace this quarter's ARR back to the Stripe subscriptions behind the closed Deals.
- Which Google Ads channel is actually returning on spend, and which one isn't?
- Show me the Salesforce Deals behind the bookings gap in March.
- Why did net new MRR slow down — is it fewer new Deals or more churn in Stripe?
- Break booked revenue out by Salesforce Deal owner so I can see who's carrying the quarter.
- Add pipeline coverage against next quarter's target using Salesforce stage probabilities.
- Show net revenue retention by segment, flagging any cohort under 100%.
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 |
|---|---|---|---|
| ARR | Your monthly recurring revenue annualized, the figure a board or investor anchors on. | MRR × 12 | 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 |
| Pipeline Coverage | The early-warning gauge on the forecast: how many times your open pipeline covers the quota you have to hit. | Open Pipeline ÷ Quota | Salesforce |
| Net New MRR | How much your recurring revenue actually grew this month after new business, expansion, contraction, and churn net out, the single number that says whether the base is compounding. | New MRR + Expansion MRR − Contraction MRR − Churned MRR | Stripe |
| Win Rate | The cleanest read on sales effectiveness: the share of decided deals you win, won divided by won-plus-lost. | Won Deals ÷ (Won Deals + Lost Deals) | Salesforce |
| ROAS | Revenue attributed back to ad spend per dollar spent, the headline efficiency number for paid. | Attributed Revenue ÷ Ad Spend | Google Ads, Stripe |
Have our agent watch for you
A salesforce kpi 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 salesforce kpi 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.