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The Top-of-Funnel Math Reboot — 60-Min Training

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The Top-of-Funnel Math Reboot — 60-Min Training

Direct Answer

This is a build session, not a lecture. By minute 60 the team has rerun the math against their own numbers and named the one source to cut. Pair with st186 (pipeline math at the deal-stage layer) — st186 covers what happens *inside* pipeline; this session covers what flows *in*.


Section 1 — Frame the Four Reboots (0–5 min)

Open with the frame, said almost verbatim:

"We are going to redo top-of-funnel math from scratch. Four reboots: real coverage, conversion-by-source, demand vs capture, and which leads to kill. By the end of the hour each of you has new numbers and one source to turn off."

State the four myths we are killing:

No discussion. Move to the math.


Section 2 — Real Pipeline Coverage (5–20 min)

The "3x coverage" rule is a heuristic Jason Lemkin (SaaStr) has repeatedly called out as misleading — the real number is derived, not declared. The formula:

Required Coverage = Quota ÷ (Win Rate × Avg Deal Size), expressed as a multiple of quota.

Worked example. A team carrying $2M new-ARR quota with a 22% win rate on a $60K average ACV and a 90-day cycle:

Now run the inverse: at the same 22% win rate, "3x coverage" only funds $6M of pipeline → covers ~$1.32M of quota. The team is $680K short before the quarter starts and nobody noticed because the slide said 3x.

Bold-in-bullet rules for the room:

Each rep recalculates their own real coverage ratio in 4 minutes against last quarter's win rate and ACV.

flowchart TD A[Quota target] --> B[Divide by win rate × ACV] B --> C[Required qualified opps] C --> D[× ACV = pipeline $ needed] D --> E[÷ Quota = real coverage ratio] E --> F{Above or below current?} F -->|Below| G[Top-of-funnel gap — build now] F -->|Above| H[Capture problem, not demand problem]

Section 3 — Conversion-by-Source (20–30 min)

Aggregate top-of-funnel metrics lie. Mark Roberge (HubSpot's first SVP Sales) hammers this in *The Sales Acceleration Formula*: the average is a fiction; the source-level numbers are the truth. David Skok ("For Entrepreneurs") publishes the same finding in his SaaS funnel analyses — lead-to-customer conversion by source can vary 10x within the same company.

Run the table for each rep's last 90 days:

SourceLeadsMQLsSQLsClosed-wonLead → Won %
Inbound (organic search)80024095182.25%
Webinar1,2001804040.33%
Paid LinkedIn6001203561.00%
Outbound SDR0011022n/a — 20% SQL→Won
Partner referral4038281435.0%

The diagnostic moment in the room: partner referral converts 15x better than webinar, but webinar gets 30x the budget. That is not a top-of-funnel volume problem. That is a mix problem.

Rules:


Section 4 — Demand vs Capture (30–40 min)

The split most teams miss, popularized by Chris Walker and echoed in Bridge Group's SDR research: demand creation (the buyer learns the problem exists) is not demand capture (the buyer fills out a form). Most "top-of-funnel" budget is capture spend masquerading as demand spend.

The diagnostic:

ActivityDemand or Capture?What it actually does
Branded search adsCaptureIntercepts buyers already searching you
RetargetingCaptureRe-touches existing pipeline
Gated whitepapersCaptureHarvests already-interested form-fillers
Podcast sponsorshipDemandBuilds future buyer awareness
Founder LinkedIn contentDemandCreates the problem-aware buyer
Outbound to ICP cold listDemandManufactures awareness in a target account

If >70% of spend is capture, the team is harvesting a demand pool someone else built — and when that pool dries, pipeline collapses. Trish Bertuzzi (*The Sales Development Playbook*) makes the same point about outbound SDR teams pointed at lists with no demand work behind them: conversion craters.

The rule: target a 40/60 demand-to-capture split in B2B SaaS at $25K–$500K ACV. Reps mark every active source on the demand-vs-capture line and compute their team's ratio.


Section 5 — Kill the Wrong Leads First (40–55 min)

The counterintuitive lift. Trish Bertuzzi's Bridge Group SDR benchmarks show SDR teams running >40% unqualified MQL volume convert worse than teams running half the volume at higher quality, because reps drown.

The diagnostic question: "If we deleted the bottom 30% of MQLs by fit score, what would actually break?" Usually: nothing — except reps would finally work the top 70%.

Worked example:

The kill-list ranking criteria:

  1. Fit score (ICP match) below threshold.
  2. Source with lead-to-won under 0.5%.
  3. Stalled MQLs older than 60 days with no SQL conversion.
  4. Job-title patterns that historically never close (students, vendors, competitors).

Each rep names one source or segment they will turn off Monday. Out loud, in the room.

flowchart TD A[Audit last 90 days of MQLs] --> B{Lead-to-won by source} B -->|Top quartile| C[Double down] B -->|Bottom quartile| D[Kill or shrink] D --> E[SDRs reclaim 30%+ time] E --> F[SQL conversion rises] C --> G[Reallocate budget] F --> H[Same or higher wins on lower volume] G --> H

Section 6 — Commit & Recompute (55–60 min)

Each rep states, out loud, three things:

  1. My new real coverage ratio is X. (Not 3x.)
  2. The one source I am turning off Monday is Y.
  3. My demand-to-capture split is Z, and I am moving it toward 40/60 by [action].

Put a 30-day recheck on the calendar. Top-of-funnel math is not a one-time recompute; it drifts every quarter as win rates and source mix shift.


FAQ

Why is the "3x coverage" myth so sticky? Because it is simple and roughly right for a team running ~33% win rates with short cycles. Outside that narrow band — which is most B2B SaaS — it is wrong. Lemkin and Skok both publish the derivation.

Should outbound SDR be measured the same way as inbound? No. Outbound bypasses the MQL stage and is measured SQL-to-won directly. Mixing inbound MQL conversion with outbound SQL conversion produces nonsense averages.

Won't killing sources reduce pipeline? Short-term yes, by a small amount; medium-term no, because rep focus on higher-fit leads lifts conversion enough to net out positive. The math in Section 5 is the proof.

How does this connect to st186? st186 takes pipeline *after* it exists and runs the stage-conversion math through close. This session is upstream — it fixes what flows in. Run st214 first, then st186.


Sources

  1. Jason Lemkin, SaaStr — repeated essays debunking the "3x coverage" heuristic.
  2. Tomasz Tunguz — SaaS pipeline coverage and sales-cycle timing analyses.
  3. David Skok, *For Entrepreneurs* — SaaS funnel conversion-by-source frameworks.
  4. Mark Roberge, *The Sales Acceleration Formula* — source-level conversion vs aggregate averages.
  5. Trish Bertuzzi, *The Sales Development Playbook* — SDR qualification and quality-vs-volume.
  6. The Bridge Group — annual SDR Metrics & Compensation benchmark research.
  7. Chris Walker / Refine Labs — demand creation vs demand capture framework.
  8. Pulse RevOps library entry (st186) — pipeline math at the deal-stage layer.
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