Why the same rep hits 70% there and 0% at your company

Why the same rep hits 70% there and 0% at your company

The same mediocre rep hits 70% of quota at one company and 0% at yours. Jason Lemkin laid out the mechanics this week in The 0% Quota Club (And Why the Same Mediocre Rep Hits 70% at One Company and 0% at Yours). Three factors separate those outcomes: product-market fit, tight process, and substantial support. When a company has all three, mediocre reps hit 50-90% of quota. When one is missing, the same rep hits zero. Not low. Zero.

I run $300K/month in paid media and I've watched this play out from the demand side. Leads that should convert at 15% die at 2%. The creative isn't weak. The targeting isn't off. The sales motion behind the funnel isn't built to carry average performers, so it doesn't.

Most Series A and B founders I talk to are debugging the wrong layer. They're firing reps, tweaking comp plans, and booking sales trainers. The actual problem is that their GTM system cannot carry a mediocre rep across the finish line. Lemkin's three conditions are system outputs. None of them are rep-dependent. A great rep in a broken GTM system flames out in six months. A mediocre rep in a strong GTM system looks like a star. The founders who figure this out early stop making rep-level bets and start making system-level bets. That's a different resource allocation problem entirely, and most founders don't make the shift until they've burned through three headcount cycles.

PMF is a multiplier, not a baseline

Most PMF conversations treat it as binary: you either have it or you don't. Lemkin's framing pushes further. PMF functions as a multiplier. A company with strong PMF takes a mediocre rep from 0% to 70%. That's a 70-point lift from system quality alone, before training, territory, or comp.

The paid media equivalent is visible if you've run similar creative across two companies with different positioning clarity. A channel that converts at 8% for a company with a sharp ICP definition converts at 1.2% for a company still sorting out who it's selling to. The creative is nearly identical. The targeting is similar. The message is where the math falls apart.

If your blended CPA is climbing quarter over quarter and close rates are dropping, don't audit the rep first. Audit the message. Audit whether the promise at the top of the funnel is something your median rep can actually close on without coaching from your best rep on every single deal.

Tight process is what raises the floor

Salesforce published data showing that companies with documented sales processes close 33% more deals. More important than the volume lift: variance shrinks. Fewer zeros. Fewer star reps carrying 80% of revenue by themselves. When the process is tight, the floor rises and performance distributes more evenly across the team.

For a Series A company spending $50-150K/month on paid media, the process question is specific: what happens to a lead between click and closed-won? Most founders cannot answer that with precision. They know the SDR outreaches within some window, the AE runs a demo, legal takes a while. But they don't know the median time from MQL to first touch by channel. They don't know which cohorts stall at proposal stage versus which never make it to a second call.

That gap is where budget disappears. Not in the ad creative. Not in the targeting. In the handoff nobody has documented. A tight process closes that gap. Not because it produces better reps, but because it removes the decision points where a mediocre rep loses momentum.

Support is where attribution gets distorted

Lemkin's third variable is support: battlecards, demo collateral, onboarding capacity, BDR coverage, a clear discount ladder. Most founders underweight this because it's invisible in a standard dashboard.

What support actually does in a GTM system: it removes the reasons a mediocre rep would fail. They don't have to know your competitor's weak points on the fly because the battlecard tells them. They don't have to wing the pricing conversation because finance gave them a structured framework to work from.

When I'm running attribution analysis across channels, support quality shows up as a hidden variable. Companies with strong support infrastructure show narrow win-rate variance across reps. Companies without it show wide variance that reads like channel-level performance differences. Founders see the signal and pull back on the channel. What they should be doing is building the support layer that lets average reps close what the channel is sending them.

The channel scoring mistake that follows from all of this

Your GTM strategy needs to account for system maturity, not just channel CPA. If your process is loose and your support is thin, paid channels will underperform against benchmarks even when the demand-side work is solid. You'll kill a channel that would have converted at month nine because you pulled it at month three before the sales motion caught up.

I've watched this happen specifically in financial services. A founder pulled LinkedIn because CPA came in at 4x target. They shifted to content and outbound. Six months later they were back on LinkedIn with nothing to show for the detour. The channel wasn't the problem. The system couldn't close what the channel was delivering, and they misread that as a targeting failure.

When you score channels, you need a process maturity variable alongside volume and cost metrics. Without it, you're crediting or blaming the channel for a conversion problem that lives downstream in the sales org. One is a paid media problem. The other is a sales system problem. They look identical in a standard dashboard and they require completely different fixes.

How GTMVP fits in

GTMVP runs eight agents continuously: competitor mapping, positioning sharpening, angle generation, channel scoring, trend surfacing, and more. The piece that connects most directly to Lemkin's thesis is the GTM strategy intelligence layer. It's built to give Series A founders a read on whether their GTM system can support the channels they're running, not just whether the channels are performing in isolation. When a mediocre rep hitting 0% is actually a positioning problem or a channel-to-close-rate mismatch, GTMVP surfaces that signal before you've spent another $50K testing the wrong variable. If you're attributing poor channel performance to the channel when the real issue is a broken handoff or undefined competitive positioning, GTMVP will surface that distinction.

What to do this week

• Audit your MQL-to-close timeline by channel. If LinkedIn leads take 40 days and Google leads take 22, that's an audience fit signal, not a volume problem.
• Map every support asset your reps are actually using in live deals. If they're inventing answers to competitive objections, you have a battlecard gap, not a rep gap.
• Score your channels against your actual close rate, not category benchmarks. A 2% close rate requires a fundamentally different CPA target than a 12% close rate, and running them through the same model is how you cut the wrong channel.
• Pull win/loss data by rep and look for wide variance across similar territories. Wide variance means the system isn't carrying average performance. That's a system problem before it's a people problem.
• Run your positioning through this test: can a mediocre rep explain your differentiation in 90 seconds without any prep? If only your top two reps can do it reliably, you have tribal knowledge, not positioning.

If Lemkin's framework revealed cracks in your GTM system, the fastest next step is a structured audit. Run a GTMVP audit at /audit to get a clear read on where your channels, positioning, and process alignment actually stand, and review a sample output at /sample-report before you start.