All dashboards/Sales & RevOps

Your CRM dashboard, tied back to the deals.

Open pipeline, win rate, average deal size, and booked revenue in one view, modeled from the CRM, so every number traces back to the deals it came from.

See how to build one in Definite
What’s in a CRM dashboard?

What’s in a CRM dashboard?

A CRM dashboard is the single governed view of the sales motion: how much pipeline is open, how fast it converts, what size deals are closing, and how much revenue is booked. The version worth running a forecast on is modeled from the CRM in your warehouse, so the pipeline the reps are working is the pipeline on the screen.

Every CRM report uses different filters, different stage definitions, and a different close-date cutoff. When pipeline, win rate, and booked revenue live in one set of governed definitions modeled on Salesforce or HubSpot, the number in the pipeline review is the number in the forecast, and you stop re-deriving it in every meeting.

Who it’s forRevOps leads, sales managers, and CROs who own the forecast.

CadenceRefreshed daily; reviewed in the weekly pipeline review and at forecast commit.

Built fromSalesforce, Hubspot, Pipedrive

§ How it works

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.

You
I need one view of what the CRM is actually saying: open pipeline, win rate, deal size, booked revenue, and how fast deals are moving through stages.
✦ Fi
Here's your CRM dashboard, on your Salesforce, Hubspot and Pipedrive data.
Here’s what’s in it

The top row leads with the 4 numbers that matter most: Open pipeline, Win rate, Avg deal size, Booked revenue. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Pipeline over time, Win rate trend) show how the headline numbers have moved over time. A breakdown (Booked revenue by segment) splits the metric by dimension so you can see what's driving the total. A detail table (CRM health) 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.

Illustrative data

Open pipeline

$9.35M▼ 8.6%
Data ▾
PeriodOpen Pipeline
Jan$6.79M
Feb$7.11M
Mar$6.12M
Apr$7.18M
May$7.24M
Jun$8.06M
Jul$7.34M
Aug$7.70M
Sep$8.74M
Oct$8.76M
Nov$10.23M
Dec$9.35M

Win rate

54.2%▼ 1.4%
Data ▾
PeriodWin Rate
Jan51.3%
Feb52.0%
Mar51.5%
Apr50.9%
May56.2%
Jun43.4%
Jul55.2%
Aug48.4%
Sep58.5%
Oct58.3%
Nov55.0%
Dec54.2%

Avg deal size

$12K▼ 5.4%
Data ▾
PeriodAvg Deal Size
Jan$11K
Feb$10K
Mar$13K
Apr$11K
May$9K
Jun$14K
Jul$11K
Aug$13K
Sep$9K
Oct$10K
Nov$13K
Dec$12K

Booked revenue

$1.19M▲ 4.6%
Data ▾
PeriodBooked Revenue (Closed Won)
Jan$894K
Feb$670K
Mar$903K
Apr$848K
May$795K
Jun$948K
Jul$1.05M
Aug$1.08M
Sep$945K
Oct$1.16M
Nov$1.14M
Dec$1.19M

Pipeline over time

6,000,000 7,000,000 8,000,000 9,000,000 10,000,000 11,000,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodOpen Pipeline
Jan$6.79M
Feb$7.11M
Mar$6.12M
Apr$7.18M
May$7.24M
Jun$8.06M
Jul$7.34M
Aug$7.70M
Sep$8.74M
Oct$8.76M
Nov$10.23M
Dec$9.35M

Booked revenue by segment

Enterprise Mid-Market SMB 0 100,000 200,000 300,000 400,000
Data ▾
SegmentBooked Revenue (Closed Won)
Enterprise$320K
Mid-Market$404K
SMB$468K

Win rate trend

0 0.2 0.4 0.6 0.8 1 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodWin Rate
Jan51.3%
Feb52.0%
Mar51.5%
Apr50.9%
May56.2%
Jun43.4%
Jul55.2%
Aug48.4%
Sep58.5%
Oct58.3%
Nov55.0%
Dec54.2%

CRM health

Avg Sales Cycle (days)43▼ 6.5%
Pipeline Coverage7.6×▼ 12.1%
New Pipeline$3.02M▲ 6.2%
✦ Fi
Anything else I can do for you?
You
Why did win rate drop last month when pipeline was growing?Which reps have the most pipeline but the lowest conversion?Show me the deals that slipped out of this quarter's commit.What is pipeline coverage if I use the trailing three-month win rate instead of the all-time average?Break booked revenue out by segment instead of the total.Trace this month's booked revenue back to the opportunities in Salesforce.Break win rate by segment and flag any segment that dropped quarter over quarter.Add pipeline velocity by stage so I can see where deals stall.Show me booked revenue by rep, not just the team total.
  • Why did win rate drop last month when pipeline was growing?
  • Which reps have the most pipeline but the lowest conversion?
  • Show me the deals that slipped out of this quarter's commit.
  • What is pipeline coverage if I use the trailing three-month win rate instead of the all-time average?
  • Break booked revenue out by segment instead of the total.
  • Trace this month's booked revenue back to the opportunities in Salesforce.
  • Break win rate by segment and flag any segment that dropped quarter over quarter.
  • Add pipeline velocity by stage so I can see where deals stall.
  • Show me booked revenue by rep, not just the team total.
§ Why the numbers tie out

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.

DealOpen PipelineWin RateAvg Deal SizeBooked Revenue (Closed Won)Avg Sales Cycle (days)Pipeline CoverageNew Pipeline
ActivityAvg Sales Cycle (days)
DealOpen PipelineWin RateAvg Deal SizeBooked Revenue (Closed Won)Avg Sales Cycle (days)Pipeline CoverageNew Pipeline
DealOpen PipelineWin RateAvg Deal SizeBooked Revenue (Closed Won)Avg Sales Cycle (days)Pipeline CoverageNew Pipeline
ActivityAvg Sales Cycle (days)
MetricWhat it measuresHow it's calculatedSources
Win RateThe 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, Hubspot, Pipedrive
Avg Deal SizeBooked revenue per closed-won deal, the lever between volume and value.Booked Revenue (Closed Won) ÷ Won DealsSalesforce, Hubspot, Pipedrive
Pipeline CoverageThe early-warning gauge on the forecast: how many times your open pipeline covers the quota you have to hit.Open Pipeline ÷ QuotaSalesforce, Hubspot, Pipedrive
§ Then do something about it

Have our agent watch for you

A CRM 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.

Autonomous agent · watch churn
Watch
A metric you choose
net revenue churn
Judge
One condition
> 5% week-over-week
Act
One action
alert #revenue + open doc
◄──── then waits · cooldown 24h before it can act again ────
Scoped to a single metric and a single action. You arm it; you can disarm it anytime.
§ The data that powers it

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 →

§ Get started

Build your CRM dashboard

From signup to a working dashboard in one sitting. No data team required.

01

Sign up

Free to start. No credit card, no infrastructure to set up.

Create your account
02

Connect your sources

Stripe, your CRM, accounting. Definite syncs and models them automatically.

03

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.

04

Ask Fi to build it

Describe what you need in plain language. Fi builds the dashboard, and you refine by asking follow-ups.

§ FAQ

Common questions

Usually because each CRM report filters deals differently — different stage inclusions, different close-date logic, different owner scopes. The reconciliation map above shows which CRM object each metric comes from, so there is one definition of pipeline and one win rate, modeled in your warehouse instead of re-derived from a filtered view.
Salesforce, HubSpot, and Pipedrive. Definite syncs deals, stages, and activities from each, models them into governed metrics, and reconciles the numbers so pipeline and revenue agree regardless of which CRM you run.
Open pipeline is the total value of deals currently in play. New pipeline is the value of deals created in a given period. Both matter: open pipeline is what you are working, new pipeline is what you are generating. When both come from governed definitions, the gap between them is the pipeline you consumed.
It is a live ECharts dashboard running on a deterministic synthetic dataset, labeled illustrative. Win rate is computed from won and lost deals, pipeline coverage from the formula in the metric table. Connect your CRM and Fi builds the same view from your data.
A dashboarding tool visualizes whatever CRM export you give it. This is the output of a governed pipeline model: the CRM is synced, the stage definitions are modeled once, and the numbers trace back to the deals. The difference matters when the forecast goes to the board.
Tell Fi what you need, the way the prompt above reads. Fi connects your CRM, proposes the pipeline and revenue metrics, and you refine by asking follow-ups. No SQL, no analyst queue, no waiting for the weekly CRM export.

Your answer engine
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