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Your Intercom marketing funnel dashboard, every conversation traced to pipeline.

Lead volume, MQLs, SQLs, and stage conversion rates modeled from Intercom contacts, conversations, and segments, reconciled with Salesforce for the sales handoff, so every stage is measured by the same definition.

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

What’s in a intercom marketing funnel dashboard?

A marketing funnel dashboard built on Intercom traces how contacts move from first conversation to MQL to SQL to close. Lead volume comes from Intercom contacts and segments, conversion stages reconcile with Salesforce deals, and every handoff is governed by one definition.

Intercom captures conversations and contacts but does not track pipeline stages. Without reconciliation, marketing sees engagement and sales sees a different funnel. This dashboard bridges the gap so every stage conversion is a real number tied to actual Intercom contacts.

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

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

Built fromIntercom, 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
Show me the full funnel from our Intercom contacts — lead volume, MQL to SQL rate, and where the drop-off is — reconciled with Salesforce so marketing and sales see the same numbers.
✦ Fi
Here's your intercom marketing funnel dashboard, on your Intercom 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

5.2K▲ 16.0%
Data ▾
PeriodLead Volume
Jan3.3K
Feb3.1K
Mar3.1K
Apr3.0K
May3.4K
Jun4.8K
Jul4.7K
Aug5.5K
Sep4.6K
Oct5.8K
Nov4.5K
Dec5.2K

MQLs

2.5K▼ 4.6%
Data ▾
PeriodMQLs
Jan1.7K
Feb1.8K
Mar1.8K
Apr2.0K
May2.0K
Jun1.6K
Jul2.1K
Aug1.7K
Sep2.3K
Oct2.1K
Nov2.6K
Dec2.5K

MQL → SQL rate

30.2%▲ 10.9%
Data ▾
PeriodMQL → SQL Rate
Jan17.8%
Feb23.3%
Mar20.8%
Apr27.3%
May28.0%
Jun37.0%
Jul28.4%
Aug33.5%
Sep30.3%
Oct29.6%
Nov27.2%
Dec30.2%

SQLs

758▲ 5.8%
Data ▾
PeriodSQLs
Jan309
Feb409
Mar368
Apr550
May552
Jun586
Jul585
Aug563
Sep685
Oct626
Nov716
Dec758

Lead volume over time

3,000 3,500 4,000 4,500 5,000 5,500 6,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Data ▾
PeriodLead Volume
Jan3.3K
Feb3.1K
Mar3.1K
Apr3.0K
May3.4K
Jun4.8K
Jul4.7K
Aug5.5K
Sep4.6K
Oct5.8K
Nov4.5K
Dec5.2K

MQLs by channel

Paid Search Paid Social Organic Email Referral 0 100 200 300 400 500 600 700
Data ▾
ChannelMQLs
Paid Search509
Paid Social375
Organic663
Email638
Referral324

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
Jan17.8%
Feb23.3%
Mar20.8%
Apr27.3%
May28.0%
Jun37.0%
Jul28.4%
Aug33.5%
Sep30.3%
Oct29.6%
Nov27.2%
Dec30.2%

Funnel conversion rates

Lead → MQL Rate48.5%▼ 17.7%
MQL → SQL Rate30.2%▲ 10.9%
SQL → Close Rate17.1%▲ 16.2%
✦ Fi
Anything else I can do for you?
You
Which Intercom segment produces the most MQLs that actually convert to SQL?Show me MQL-to-SQL rate by Intercom tag over the last quarter.Trace this month's SQLs back to the Intercom conversations that started them.Where is the biggest drop-off between Intercom contacts and Salesforce opportunities?What would SQL volume look like if MQL-to-SQL improved by 5 points?Break MQL-to-SQL rate by Intercom segment to see which contacts convert best.Show lead volume by Intercom tag alongside conversion rate.Add a stage-by-stage drop-off trend filtered to Intercom conversations that triggered an MQL.
  • Which Intercom segment produces the most MQLs that actually convert to SQL?
  • Show me MQL-to-SQL rate by Intercom tag over the last quarter.
  • Trace this month's SQLs back to the Intercom conversations that started them.
  • Where is the biggest drop-off between Intercom contacts and Salesforce opportunities?
  • What would SQL volume look like if MQL-to-SQL improved by 5 points?
  • Break MQL-to-SQL rate by Intercom segment to see which contacts convert best.
  • Show lead volume by Intercom tag alongside conversion rate.
  • Add a stage-by-stage drop-off trend filtered to Intercom conversations that triggered an MQL.
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
Intercom
◆ ContactLead VolumeMQLsMQL → SQL RateLead → MQL 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, Intercom
Lead → MQL Rate—MQLs ÷ Lead VolumeIntercom, Salesforce
SQL → Close Rate—Won Deals ÷ SQLsSalesforce
§ Then do something about it

Have our agent watch for you

A intercom 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 intercom 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

Intercom counts contacts by conversation state and segment membership, while your CRM scores MQLs on different criteria and dates. This dashboard maps each metric to a specific Intercom or Salesforce object so there is one definition of an MQL and one SQL.
Intercom for contacts, conversations, and segments that feed lead volume and engagement. Salesforce for the MQL-to-SQL handoff and pipeline stages. Definite syncs both and models the full funnel into governed definitions.
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 Intercom and Fi builds the same view from your data.
Tell Fi what you need, the way the prompt above reads. Fi connects Intercom and Salesforce, proposes the funnel metrics, and you refine by asking follow-ups. The first version measures every handoff without a spreadsheet.
Yes. Because Definite reconciles Intercom contacts with Salesforce deals, you can trace any SQL back to the conversation or segment that started the relationship — something neither system shows on its own.

Your answer engine
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