Executive GTM Reporting — Delivery Playbook

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

# 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Phase 3

Enable.

The deliverable isn't a dashboard. It's an executive who trusts the number enough to make a decision on it — and that trust is built in how you hand it over.

Know the room

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.

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

A new segment appears

New territory, new product line, new partner, new channel. Each needs a home in the segment model or it falls into "other" and disappears from every cut.

Trigger · structural

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 Executive GTM Reporting playbook.

The audio brief.

Four phases, one motion.