---
title: "Executive GTM Reporting"
type: playbook
evidence_type: method
category: "Revenue Systems"
publisher: "LeanScale"
date_modified: 2026-08-11
word_count: 3532
topics: ["forecasting", "revenue-operations"]
canonical_url: https://knowledge.leanscale.team/playbooks/executive-reporting-playbook/
source: "LeanScale Knowledge Hub — https://knowledge.leanscale.team"
license: "Free to quote and cite with attribution to LeanScale."
---

# Executive GTM Reporting

**Evidence type:** method (what we prescribe)

Every Executive GTM Reporting project moves through the same four phases. This is a project you win in the Blueprint — by the time you're building charts, the hard decisions are already made or already wrong. 1 Blueprint Clear the data gate, pick the mode, settle the definitions.

## Four phases, one motion.

Every Executive GTM Reporting project moves through the same four phases. This is a project you win
in the Blueprint — by the time you're building charts, the hard decisions are already made or already wrong.
1
Blueprint
Clear the data gate, pick the mode, settle the definitions.
Output Signed-off metric spec
2
Build
Five dashboards, the pack, drill-through — then reconcile.
Output Live dashboards + pack
3
Enable
Teach the definitions, hand over the exec email, hyper-care.
Output Execs who trust it
4
Maintain
Catch definition drift and reload goals every period.
Output Numbers that stay true
Start Here

## Kick off a project in one paste.

Copy this prompt, drop in the customer name, and send it to your Claude. If Vasco is implemented it reads
from there; if not, it will ask you to connect their Salesforce or HubSpot before it does anything else.
paste into Claude Copy prompt
# Executive GTM Reporting — kick off
Build an Executive GTM Reporting pack for my customer [Customer Name] ,
following the LeanScale Executive GTM Reporting playbook.
# Data source — resolve this first, before anything else
Check whether Vasco is implemented for this customer. If it is, pull from Vasco.
If it is NOT, stop and prompt me to connect their CRM (Salesforce or HubSpot)
so you can pull live data. Ask before you assume. If they warehouse their GTM
data somewhere else (Snowflake, BigQuery), ask me for that connection instead.
# Then run the Blueprint checklist and get my answers before building
1. Which mode? (native CRM dashboards / custom-built dashboard / reporting pack)
2. Who owns expansion — sales or CS?
3. Goal structure — board, executive and field-level targets for the period?
4. Attribution model — first touch, last touch, or multi-touch?
5. Which segments are meaningful? (rep, channel, territory, region,
industry, product, firmographic)
# Defaults — apply unless I say otherwise
- Conversion rate = cohort by CREATED DATE, then won / (won + lost). Open deals excluded.
- Timeframe = rolling 13 months.
- No filters other than a date filter.
- KPIs as plain numbers across the top, charts below, split into labelled sections.
- Every chart gets a View Details drill-through to the underlying records.
Show me the metric spec for sign-off BEFORE you build a single chart.
1
Phase 1

## Blueprint.

Blueprint on this motion is almost entirely
about agreement, not discovery. You are clearing one gate, picking one mode, and settling a handful of
definitions in writing — so that when an executive challenges a number in the first review, you are
quoting a decision they already signed off on rather than defending a choice you made alone.
The gate — read this before you scope
This playbook assumes the data is already good . If stages don't mean anything, if half the
opportunities have no close date, if lead source is free text — that's a data infrastructure
project, and it comes first . Beautiful reporting on bad data just publishes the mess faster, and
you'll own the mess the moment you put your name on the chart.
Decision 1

## Pick the mode.

Three ways to ship the same metric spine. The choice is about who reads it and how often — not about
which is most impressive.
Native CRM
Mode 1 · Salesforce or HubSpot
Lives where the reps already are, and refreshes itself.
Best when leaders will actually log in, and the numbers need to be self-serve daily.
Watch HubSpot: custom formula fields are a paid tier. Without them, cohort conversion rate is painful.
Custom-built
Mode 2 · pulled out, built by us
Pull the data out, build the dashboard as a web app.
Best when the math is beyond what the CRM can express — cost per SQL, blended cohort rates, quadrant matrices.
Usually the highest-impact of the three. It's also the only mode where you fully control the definitions.
The reporting pack
Mode 3 · board & investors
The long deck a founder sends to a board or an investor.
Best when the audience reads it once a quarter and needs the story, not the tool.
Ships as an HTML deck, in their brand, produced by LeanScale.
If they already run Tableau, Power BI or Looker — common in
older instances — that's a fourth vessel, not a fourth opinion. Same spine, their tool. And in HubSpot,
lists and segments are a related but separate build: they fuel sequences and campaigns, not executive reporting.
Decision 2

## Five questions, answered before you build.

1
Who owns expansion?
The single highest-leverage question on the project. If sales owns it,
expansions become their own pipeline on the sales dashboard, usually with a renewals section beside it. If
CS owns it, it sits in customer success and the sales dashboard needs a post-expansion
handoff view instead. Some companies report all bookings as one number — new business plus expansion stacked
together. LeanScale does it that way : $10k expansion plus a $20k new deal is a $30k forecast.
2
What's the goal structure?
Most companies need three, and they are three different numbers: board-level
(what was committed externally), executive-level (what leadership is managing to), and
field-level (the quota actually carried by reps, usually the largest). Every headline metric
gets reported against whichever of these the viewer cares about — so capture all three up front.
3
What's the attribution model?
First touch, last touch, or multi-touch — and whether they think in sourced
versus influenced . This decides what marketing's headline number can even claim. Don't design
the marketing dashboard before this is settled.
4
Which segments actually matter?
Rep, lead channel, territory, region, industry, product, firmographic tier (enterprise /
mid-market / SMB). Pick the ones this company genuinely runs on. Every headline metric will be cut by these,
so a segment you add here is real work in every dashboard downstream — and a segment you miss means rebuilding.
5
Where does the data actually live?
Ideally Vasco is implemented and you read from there. If not, you're
connecting straight into Salesforce or HubSpot. And check before you assume the CRM is the whole story —
some customers keep the real numbers in Snowflake or another warehouse , and finance data
almost never lives in the CRM at all.
Decision 3 · the one that gets challenged

## Settle conversion rate.

This is the most argued-about number on any of these projects, and the definition changes the answer by
tens of points. Write ours down, get it agreed, and move on.
The LeanScale definition
Group every deal by the date it was created — not the date it closed.
Divide won by everything that reached a decision: won + lost .
Deals still open don't count yet — they're not a loss, they're not a win.
Headline pairs are SQL→Close for sales and MQL→SQL for marketing. Apply the same rule to any two stages.
The worked example
Ten deals created in Q1. Four are won, four are lost, two are still open.
50 %
Q1-created conversion rate
4 won ÷ (4 won + 4 lost). The 2 open deals are excluded until they resolve.
The exception: very long sales cycles . If most of a
cohort is still open a year later, the cohort isn't ripe and the number will mislead — say so rather than publishing it.
If · Salesforce
Build it natively
Cohort-by-created-date conversion is straightforward with formula fields and reporting types. Do it in the CRM.
If · HubSpot on a lower tier
Pull it out and compute it
Custom properties and calculated fields sit behind a paid package. Rather than fight the tier, extract the deals and compute the cohort math outside the CRM — this is exactly what Mode 2 is for.
The default timeframe
Rolling 13 months — technically 13, not 12, so that this August sits directly beside last
August with everything in between. It makes year-over-year an eyeball comparison instead of a calculation.
Year-to-date is the common alternative when a client asks; rolling 13 is what you build unless they do .
The standard

## The metric spine.

What gets reported, by function. This is the opinion the whole playbook defends — it doesn't change when
the mode changes. Every one of these is cut by the segments you agreed in question four.
Sales
CRO · VP Sales
Bookings to goal — the headline.
Open pipeline & coverage to quota.
Created pipeline to goal — counted the moment a deal becomes an SQL. This is the leading indicator; the other two are lagging.
Forecast for the period, with the weighting logic visible underneath it.
Cycle and conversion — SQL→close headline, plus stage-to-stage.
Average deal size and average deal length, tracked over time .
Win/loss by closed-won and closed-lost reason.
Slippage — past-due close dates, by rep.
Deal health, where a tool like Gong supplies it.
Marketing
CMO · Demand gen
Created pipeline — the headline, broken down by lead channel.
MQL→SQL — the golden conversion metric. MQL→SAL is nice-to-have; this is the one that matters.
MQL→SQL cycle time , not just the rate.
Full-funnel: lead→MQL→SQL→won, stage by stage.
Cost per MQL / SQL / win — channel spend ÷ outcome. Hard in a CRM, which is why this often forces Mode 2.
Hand-raisers, tracked distinctly from nurtured leads.
Activity: last touch, activities per deal, contacts per deal.
Ads clicked and viewed; event spend by event.
PQLs , where a product-usage threshold defines one.
Customer Success
CCO · VP CS
NRR and GRR — always both, never one.
Total ARR under management, by CSM and by region.
Renewals, and expansions if CS owns them.
Churn, and churn by reason.
Customer health — share of the book in poor / average / good, on whatever methodology exists.
Lifecycle staging — implementation, onboarding, early adoption, mature adoption — plus how long each transition takes.
Last contacted , read against lifecycle stage. Quietly one of the most useful tiles on the board.
Referenceability — accounts willing to be a reference or a case study.
Account tiering and ICP scoring.
Partnerships
If a partner team exists
No new metrics — the same spine, cut by partner .
Bookings, created pipeline and open pipeline by partner.
Churn and net retention by partner.
Partner name is simply the primary segment.
The Executive view
CEO · board · the consolidated one
Every headline above, with none of the segment drill-downs . That restraint is the whole design.
ARR waterfall for the period.
Bookings to goal, overall.
Created pipeline to goal; open pipeline to target.
Churn against the budgeted churn.
MQL→SQL and SQL→won , plus overall cycle. We deliberately do not headline MQL→won — it hides which half of the funnel is broken.
Out of scope
Different playbooks
Rep dashboards — an individual's working view is a different audience and a different design.
CRM hygiene dashboards — data quality monitoring belongs with data infrastructure.
Deep single-question conversion studies.
Say no to these here, then scope them properly.
2
Phase 2

## Build.

With the spec signed off, building is fast. What
makes it good is uniformity — every dashboard laid out the same way, every chart openable, and one honest
reconciliation before anything is published.
The standard layout

## Every dashboard is built the same way.

1
KPIs across the top, as plain numbers
Core metrics as numeric tiles before any chart appears. For sales that order is
bookings → open pipeline → created pipeline → funnel metrics (cycle and conversion). Each one
carries its goal: bookings to goal, open pipeline to quota, created pipeline to goal.
2
Then charts, split into labelled sections
Use a text tile as a section header — Forecast , Pipeline ,
Funnel — so the eye always knows where it is. It's a small thing that makes a long dashboard
read as clean rather than endless.
3
Same chart, different stacks
Don't invent a new visual per segment. Start with total bookings to plan, then repeat that
same chart stacked by enterprise / mid-market / SMB, then by rep, then by channel. One chart, many
stacks — it's faster to build and far faster to read.
4
One date filter. No others.
Every filter beyond a date filter makes the dashboard messier and hands one executive a
view nobody else in the room is looking at. LeanScale ships no filters unless the client asks.
If they want to see it by rep and by territory, those are cards, not controls.
5
Every chart opens into its rows
A View Details action on every chart, showing the underlying records with
the relevant columns. When someone asks "conversion rate is 25% — what's in that?", the answer is a click:
here are the wins, here are the losses, here's the total in the window. That's the math and the data
proof behind the chart , and it's what turns a pretty dashboard into one people trust.
What "View Details" returns
Clicking the Q1-created conversion tile
Account Created Closed Stage Amount Rep Channel In the math?
Northwind 12 Jan 3 Mar Closed Won $48,000 A. Rivera Paid social Numerator
Contoso 19 Jan 28 Mar Closed Lost $32,000 J. Okafor Events Denominator
Initech 4 Feb — Negotiation $60,000 A. Rivera Outbound Excluded — still open
The third row is the point. Showing why a deal is excluded is what stops the
definition argument from restarting every quarter.
Platform notes

## Salesforce and HubSpot.

Salesforce
Cohort conversion is easy — formula fields and joined report types carry it.
Dashboard components map cleanly to the KPI-then-chart layout.
Use report folders per function so the pack can link straight to the source report.
Dynamic dashboards only if they genuinely need per-viewer scoping — otherwise it fragments the conversation.
HubSpot
Check the tier first. Custom properties and calculated fields are gated by package — cohort math may be unavailable.
When it's gated, extract and compute outside rather than approximating inside.
Lists and segments are a separate build — they serve campaigns, not executives.
Watch multi-currency: confirm whether deals are recorded in local or company currency before reporting a total.
Two charts that always earn their place

## The impact matrices.

Conversion rate on the X axis, volume or dollars on the Y. Four quadrants, and the top-right one is the
answer. Reliably the most-discussed chart in the room.
Lead channel impact matrix
Marketing · where the next dollar goes
Volume of pipeline
Unicorns · scale these
Volume, low quality
Great, but small
Cut or fix
Referral
Paid social
Events
Cold outbound
Conversion rate →
Rep efficiency matrix
Sales · who is burning volume
Bookings closed
Closing and converting
Burning the volume
Efficient, needs volume
Coach urgently
Rivera
Okafor
Chen
Bauer
Conversion rate →
Top-left is the finding that changes behaviour: high volume,
low conversion . A channel or a rep burning through everything they're given. It never shows up in a bookings chart.
Mode 3 in detail

## The reporting pack.

Ships as an HTML slide deck, like the rest of our assets. Every slide follows one anatomy — and the
anatomy is what makes it readable by someone who wasn't in any of the meetings.
1 · Title
Bookings to plan — Q3
2 · The story
Two sentences: what should I take from this?
Not a description of the chart. The conclusion the chart supports — written before the reader forms their own.
3 · The chart
With the numbers you're pointing at highlighted on the chart itself
4 · Insights, down the right
Two or three bullets.
• Enterprise is 64% of bookings on 31% of deals
• Mid-market slipped two weeks on average cycle
• One rep carries 40% of the quarter — concentration risk
Highlights and callouts, not commentary. If a bullet
doesn't contain a number, cut it.
Running order

## How the pack is assembled.

1
Executive summary — what's green, what's red
Quantitative and specific, with named call-outs. "Enterprise is outperforming
on a 34% close rate against 19% in mid-market" — not "sales performance was strong." If a line has no number
in it, it doesn't belong on this slide.
2
ARR waterfall
The first chart after the summary, always. New, expansion, contraction, churn, ending ARR —
the shape of the business in one visual before anything is broken apart.
3
Then, in order: bookings → pipeline → marketing → CS → partnerships
Each section opens with a transition slide that breaks it apart, and each
gets its own mini executive summary . Churn — and churn by reason — sits inside the CS section.
4
Brand it as theirs, signed by us
Their colour scheme, their font, their logo. Our logo appears once as
"Produced by LeanScale." Where possible, link each chart to the live CRM report behind it so
the reader can drill in themselves.
5
Draft the executive email with it
The pack ships with a drafted email telling the client how to present this to their
own executive stakeholders — the three things to lead with and the one thing to be ready to defend.
They shouldn't have to write that themselves.
The part that actually bites — do this before you publish
Reconcile the new numbers against what they've been quoting. Your cohort conversion rate will
not match the number in last quarter's board deck. Neither will created pipeline, once it's counted at SQL.
Find every gap yourself, write down exactly where it comes from, and get it accepted before the
pack goes out — never in the meeting. A number that moves without warning costs more trust than a number that
was simply wrong. Where the sales cycle allows, run the old and new definitions side by side for one
period before you retire the old one.
3
Phase 3

## Who is actually reading this.

CRO / VP Sales
The daily reader
Lives in coverage and forecast.
Will challenge the conversion definition first.
CEO / founder
Weekly at most
Wants the consolidated view and the ARR waterfall.
At a smaller company, this is the only reader that matters.
VP Finance
The one you don't plan for
Shows up unannounced and reconciles your numbers against theirs.
Assume they will. Make it easy.
Write like an executive reads
Every tile name and every tile description is short and executive. If a tile needs a paragraph
to explain what it is, it's the wrong tile. Names describe the decision, not the query.
The cadence

## Handover and hyper-care.

Wed · before
Definition pre-brief
Walk the metric spec and the reconciliation with the exec sponsor privately . Every surprise gets absorbed here, not in the review.
Fri · 2pm
Go live
Dashboards published, pack delivered, executive email drafted and sitting in the sponsor's hands.
Mon · after
Office hours
First real exec meeting has happened. Catch the questions it raised while they're still fresh.
Fri · +1 week
Office hours
A full week of use. This is when definition disagreements finally surface — resolve them into the spec, not into a one-off chart.
What ships with it
The metric spec — every definition, in writing, signed off.
This audio brief , cloned for their team.
The drafted executive email for presenting the pack upward.
A change log of definitions, so a future change is visible rather than silent.
What you teach
The conversion definition , and why open deals are excluded. Teach this twice.
Why there's no filter beyond the date filter.
How to use View Details — most people never discover it unless shown.
That a new territory, product or partner needs telling us , or it silently falls outside the segments.
4
Phase 4

## Maintain.

Reporting drifts quietly, which is exactly what
makes it dangerous. Nothing breaks and no one gets an error — the number just stops being true.
Trigger · silent

### Someone adds a stage

A new stage lands in the pipeline and every stage-to-stage conversion rate changes overnight.
Nobody is told. This is the most common way a trusted dashboard quietly becomes wrong.
Trigger · every period

### Goals get reset

Board, executive and field targets all reload each quarter. A dashboard reporting against
last quarter's goal is worse than no dashboard — it's confidently wrong. Reload them on a calendar.
Trigger · event

### Expansion changes hands

If expansion moves from CS to sales — increasingly common — the whole dashboard split moves
with it, and bookings stops meaning what it meant last quarter. Rebuild the split, don't patch it.
Trigger · data

### Attribution decays

Channels go untagged, lead source drifts back toward free text, and marketing's headline
number slowly stops reconciling. Audit against the attribution playbook rather than fixing it in the chart.
Trigger · clock

### The quarterly audit

Every quarter: re-run the reconciliation, confirm each definition still matches the spec,
confirm goals are current, and check that no tile has quietly become one nobody opens.
The Repo

## What you're cloning.

The template carries the spec, the defaults and the checklist — so the judgement calls are the only thing left to make.
AGENTS.md
Read this first
The kickoff checklist and the data-source resolution step.
The five Blueprint questions as a form to fill in.
metric-spec.md
The sign-off artifact
Every definition, written out, with the conversion rule pre-filled.
This is what the client signs, and what you quote later.
pack/
The HTML deck
Slide anatomy, transitions and mini-summaries scaffolded.
Brand tokens in one file — swap for theirs.
The executive email template.
LeanScale · Delivery OS
The Executive GTM Reporting playbook — the internal standard for building the dashboards and board packs
a leadership team actually runs the business on.

## Canonical

https://knowledge.leanscale.team/playbooks/executive-reporting-playbook/