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Your demand gen dashboard, every program measured to pipeline.

Lead volume, MQLs, SQLs, cost per acquisition, and pipeline contribution in one view, reconciled from ad platforms, CRM, and pipeline, so every program traces through to the pipeline it created.

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

What’s in a demand gen dashboard?

A demand gen dashboard is the single governed view of how marketing programs turn into pipeline: how many leads each program generates, how they qualify, what each acquisition costs, and how much pipeline results. The version worth investing on reconciles ad platforms, the CRM, and the pipeline, so demand gen is measured by the pipeline it creates, not by the leads it claims.

Demand gen teams measure leads. Sales teams measure pipeline. The gap between them is where budget gets wasted. When lead volume, MQL-to-SQL, CAC, and pipeline contribution all come from governed definitions, demand gen programs are measured by the pipeline and revenue they produce.

Who it’s forHeads of demand gen, marketing leaders, and RevOps who own the lead-to-pipeline handoff.

CadenceRefreshed daily; reviewed in the weekly demand gen review and at budget planning.

Built fromHubspot, Google Ads, Facebook Ads, Salesforce

§ 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 to see demand gen performance: lead volume, MQL to SQL conversion, cost per acquisition, and how much pipeline each program is creating.
✦ Fi
Here's your demand gen dashboard, on your Hubspot, Google Ads, Facebook Ads and Salesforce data.
Here’s what’s in it

The top row leads with the 4 numbers that matter most: Lead volume, MQLs, CAC, SQLs. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Lead volume over time, CAC trend) show how the headline numbers have moved over time. A breakdown (MQLs by channel) splits the metric by dimension so you can see what's driving the total. A detail table (Demand gen efficiency) 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

Lead volume

6.2K▼ 2.5%
Data ▾
PeriodLead Volume
Jan2.8K
Feb3.5K
Mar3.3K
Apr3.2K
May3.3K
Jun3.4K
Jul3.6K
Aug4.3K
Sep5.4K
Oct5.0K
Nov6.3K
Dec6.2K

MQLs

2.3K▲ 3.4%
Data ▾
PeriodMQLs
Jan1.4K
Feb1.6K
Mar1.3K
Apr1.7K
May1.4K
Jun1.9K
Jul1.7K
Aug2.1K
Sep1.9K
Oct2.6K
Nov2.2K
Dec2.3K

CAC

$3K▲ 8.5%
Data ▾
PeriodCAC
Jan$3K
Feb$3K
Mar$2K
Apr$3K
May$3K
Jun$2K
Jul$2K
Aug$2K
Sep$2K
Oct$3K
Nov$3K
Dec$3K

SQLs

620▼ 13.8%
Data ▾
PeriodSQLs
Jan398
Feb437
Mar399
Apr475
May465
Jun449
Jul523
Aug650
Sep597
Oct542
Nov719
Dec620

Lead volume over time

2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodLead Volume
Jan2.8K
Feb3.5K
Mar3.3K
Apr3.2K
May3.3K
Jun3.4K
Jul3.6K
Aug4.3K
Sep5.4K
Oct5.0K
Nov6.3K
Dec6.2K

MQLs by channel

Paid Search Paid Social Organic Email Referral 0 100 200 300 400 500 600
Data ▾
ChannelMQLs
Paid Search491
Paid Social504
Organic507
Email253
Referral540

CAC trend

1,500 1,800 2,100 2,400 2,700 3,000 3,300 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodCAC
Jan$3K
Feb$3K
Mar$2K
Apr$3K
May$3K
Jun$2K
Jul$2K
Aug$2K
Sep$2K
Oct$3K
Nov$3K
Dec$3K

Demand gen efficiency

MQL → SQL Rate27.0%▼ 16.6%
SQL → Close Rate18.9%▲ 25.7%
Ad Spend$323K▲ 3.2%
✦ Fi
Anything else I can do for you?
You
Which demand gen program produces the most pipeline per dollar?Show me MQL-to-SQL by program over the last quarter.Why did pipeline contribution drop last month when lead volume was up?What would pipeline look like if I doubled spend on the top program?Break pipeline contribution by channel instead of program.Trace this month's pipeline back to the demand gen programs that generated the leads.Break pipeline contribution by program to see which programs create the most pipeline.Add CAC trend by channel over six months.Show me lead volume alongside pipeline contribution by channel.
  • Which demand gen program produces the most pipeline per dollar?
  • Show me MQL-to-SQL by program over the last quarter.
  • Why did pipeline contribution drop last month when lead volume was up?
  • What would pipeline look like if I doubled spend on the top program?
  • Break pipeline contribution by channel instead of program.
  • Trace this month's pipeline back to the demand gen programs that generated the leads.
  • Break pipeline contribution by program to see which programs create the most pipeline.
  • Add CAC trend by channel over six months.
  • Show me lead volume alongside pipeline contribution by channel.
First version in a dayFree to start, flat pricingNo infrastructure to set up
§ 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.

Salesforce
◆ LeadLead VolumeMQLsSQLsMQL → SQL RateSQL → Close Rate
◆ ContactLead VolumeMQLsMQL → SQL Rate
◆ DealSQLsMQL → SQL RateSQL → Close Rate
Hubspot
◆ ContactLead VolumeMQLsMQL → SQL Rate
◆ DealSQLsMQL → SQL RateSQL → Close Rate
Google Ads
◆ CampaignCACAd Spend
◆ AccountCAC
◆ Ad GroupAd Spend
◆ Ad (Creative)Ad Spend
Facebook Ads
◆ CampaignCACAd Spend
◆ AdAd Spend
MetricWhat it measuresHow it's calculatedSources
CACWhat it costs in sales and marketing to win one new customer.S&M Spend ÷ New CustomersGoogle Ads, Facebook Ads
MQL → SQL RateThe share of marketing-qualified leads that sales accepts as qualified, the handoff health check between the two teams.SQLs ÷ MQLsSalesforce, Hubspot
SQL → Close Rate—Won Deals ÷ SQLsHubspot, Salesforce
§ Then do something about it

Have our agent watch for you

A demand gen 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 demand gen 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 demand gen measures leads generated and pipeline measures qualified opportunities — different systems, different dates, different definitions of 'sourced.' The reconciliation map above shows which system each metric comes from, so lead volume traces through to the pipeline it created.
The lead generation dashboard focuses on volume, cost, and source. The demand gen dashboard extends through to pipeline contribution — not just how many leads, but how many of them became SQLs and how much pipeline resulted. Both use the same governed definitions.
Ad platforms (Google Ads, Meta) for paid programs, a CRM (HubSpot) for leads and MQL scoring, and a pipeline system (Salesforce) for SQLs and pipeline value. Definite syncs and models all stages.
It is a live ECharts dashboard running on a deterministic synthetic dataset, labeled illustrative. CAC is computed from S&M spend over new customers, MQL-to-SQL from the formula in the metric table. Connect your systems and Fi builds the same view from your data.
A BI tool charts the leads marketing claims and the pipeline sales reports, separately. This reconciles ad platforms, the CRM, and the pipeline to one set of definitions, so demand gen programs are measured by the pipeline they create — and Fi traces any SQL back to the program that sourced it.
Tell Fi what you need, the way the prompt above reads. Fi connects your ad platforms, CRM, and pipeline, proposes the demand gen metrics, and you refine by asking follow-ups. The first version measures every program to pipeline without a spreadsheet.

Your answer engine
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