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Your marketing funnel dashboard, every stage measured to conversion.

Lead volume, MQLs, SQLs, conversion rates at each stage, and cost per acquisition in one view, reconciled from ad platforms and your CRM, so every handoff is measured by the same definition.

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

What’s in a marketing funnel dashboard?

A marketing funnel dashboard is the single governed view of how leads move from first touch to closed deal: how many leads enter, how many become MQLs, how many convert to SQLs, and how many close. The version worth optimizing on reconciles ad platforms and the CRM, so every stage conversion is a real number.

Marketing says the funnel is healthy, sales says the leads are bad, and the truth depends on whose spreadsheet you trust. When lead volume, MQL-to-SQL, and SQL-to-close all come from governed definitions modeled on the same systems, the funnel tells one story.

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

CadenceRefreshed daily; reviewed in the weekly pipeline review and at marketing-sales alignment.

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 the full funnel: lead volume, MQL to SQL rate, SQL to close rate, and where the drop-off is, with every stage reconciled to the CRM.
✦ Fi
Here's your marketing funnel 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, MQL → SQL rate, 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, MQL → SQL rate 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 (Funnel conversion rates) 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

5.0K▼ 3.5%
Data ▾
PeriodLead Volume
Jan3.9K
Feb4.0K
Mar3.2K
Apr3.8K
May4.2K
Jun4.3K
Jul3.4K
Aug4.5K
Sep3.9K
Oct5.1K
Nov5.1K
Dec5.0K

MQLs

2.3K▲ 2.6%
Data ▾
PeriodMQLs
Jan1.6K
Feb1.6K
Mar1.8K
Apr1.8K
May2.0K
Jun1.7K
Jul1.9K
Aug2.1K
Sep2.2K
Oct1.9K
Nov2.3K
Dec2.3K

MQL → SQL rate

38.3%▲ 21.6%
Data ▾
PeriodMQL → SQL Rate
Jan26.0%
Feb23.4%
Mar23.8%
Apr21.8%
May24.4%
Jun30.1%
Jul22.3%
Aug23.2%
Sep24.6%
Oct39.6%
Nov31.5%
Dec38.3%

SQLs

886▲ 24.7%
Data ▾
PeriodSQLs
Jan404
Feb367
Mar435
Apr402
May497
Jun512
Jul425
Aug479
Sep532
Oct754
Nov711
Dec886

Lead volume over time

3,000 3,300 3,600 3,900 4,200 4,500 4,800 5,100 5,400 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodLead Volume
Jan3.9K
Feb4.0K
Mar3.2K
Apr3.8K
May4.2K
Jun4.3K
Jul3.4K
Aug4.5K
Sep3.9K
Oct5.1K
Nov5.1K
Dec5.0K

MQLs by channel

Paid Search Paid Social Organic Email Referral 0 100 200 300 400 500 600 700
Data ▾
ChannelMQLs
Paid Search519
Paid Social548
Organic338
Email662
Referral245

MQL → SQL 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 ▾
PeriodMQL → SQL Rate
Jan26.0%
Feb23.4%
Mar23.8%
Apr21.8%
May24.4%
Jun30.1%
Jul22.3%
Aug23.2%
Sep24.6%
Oct39.6%
Nov31.5%
Dec38.3%

Funnel conversion rates

Lead → MQL Rate46.7%▲ 6.3%
MQL → SQL Rate38.3%▲ 21.6%
SQL → Close Rate11.5%▼ 30.7%
✦ Fi
Anything else I can do for you?
You
Where is the biggest drop-off in the funnel right now?Which channel produces the most MQLs that actually convert to SQL?Show me MQL-to-SQL rate by channel over the last quarter.What would SQL volume look like if MQL-to-SQL improved by 5 points?Break lead volume by source instead of channel.Trace this month's SQLs back to the campaigns that generated the leads.Break MQL-to-SQL rate by channel to see which source produces the best leads.Add a stage-by-stage drop-off trend over six months.Show me lead volume by source alongside conversion rate.
  • Where is the biggest drop-off in the funnel right now?
  • Which channel produces the most MQLs that actually convert to SQL?
  • Show me MQL-to-SQL rate by channel over the last quarter.
  • What would SQL volume look like if MQL-to-SQL improved by 5 points?
  • Break lead volume by source instead of channel.
  • Trace this month's SQLs back to the campaigns that generated the leads.
  • Break MQL-to-SQL rate by channel to see which source produces the best leads.
  • Add a stage-by-stage drop-off trend over six months.
  • Show me lead volume by source alongside conversion rate.
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 VolumeMQLsMQL → SQL RateSQLsLead → MQL RateSQL → Close Rate
◆ ContactLead VolumeMQLsMQL → SQL RateLead → MQL Rate
◆ DealMQL → SQL RateSQLsSQL → Close Rate
Hubspot
◆ ContactLead VolumeMQLsMQL → SQL RateLead → MQL Rate
◆ DealMQL → SQL RateSQLsSQL → Close Rate
MetricWhat it measuresHow it's calculatedSources
MQL → SQL RateThe share of marketing-qualified leads that sales accepts as qualified, the handoff health check between the two teams.SQLs ÷ MQLsSalesforce, Hubspot
Lead → MQL Rate—MQLs ÷ Lead VolumeHubspot, Salesforce
SQL → Close Rate—Won Deals ÷ SQLsHubspot, Salesforce
§ Then do something about it

Have our agent watch for you

A marketing funnel 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 marketing funnel 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 marketing counts an MQL when a lead scores above threshold, and sales counts an SQL when a rep accepts it — often on different dates and with different inclusion criteria. The reconciliation map above shows which CRM object each metric comes from, so there is one definition of an MQL and one SQL.
Ad platforms (Google Ads, Meta) for lead generation, a CRM (HubSpot, Salesforce) for lead scoring, MQL/SQL stages, and the handoff to pipeline. Definite syncs and models all stages into governed definitions.
Lead-to-MQL measures how many raw leads become marketing qualified. MQL-to-SQL measures how many of those convert into sales qualified opportunities. When both come from governed definitions, the gap tells you whether the problem is lead quality or sales follow-up.
It is a live ECharts dashboard running on a deterministic synthetic dataset, labeled illustrative. MQL-to-SQL rate is computed from SQLs over MQLs, by the formula in the metric table. Connect your CRM and Fi builds the same view from your data.
A BI tool charts the funnel marketing and sales each report separately and inherits the argument. This reconciles ad platforms and the CRM to one MQL and one SQL definition, so the funnel tells one story — and Fi traces any SQL back to the campaign.
Tell Fi what you need, the way the prompt above reads. Fi connects your CRM and ad platforms, proposes the funnel metrics, and you refine by asking follow-ups. The first version measures every handoff without a spreadsheet.

Your answer engine
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