The 5 GTM metrics that actually matter

We're measuring the wrong things, and everyone in the room is happy about it.

MQL count is up. Impressions are strong. The dashboard looks excellent in the quarterly deck.

Meanwhile win rates are flat, cycles keep stretching, and nobody can say where deals are actually dying.

The comfortable dashboard

Look at what most GTM dashboards are made of.

MQLs, which reward volume over quality and produce the standing argument where marketing hits target and sales complains about lead quality. Website traffic, which is fine for visibility and says nothing about whether anyone bought. Content downloads, which measure interest and get read as intent.

Social engagement is fun to report. Email open rates are noise wearing a percentage sign, because the click is the signal.

None of these are lies. They're just numbers that can only come back good, and a number that can only come back good is decoration.

They persist because they're easy. Every tool ships with them, nobody has to negotiate a definition, and no department has to admit anything in order to report them.

The indicting number

One test sorts a real metric from a comfortable one.

Can it come back bad in a way that names something specific to fix? If yes, it earns its hour. If the worst possible reading is "we could do more of that," it's decoration.

Call it an indicting number. A number willing to accuse somebody, including us.

Five of them predict revenue in a SaaS go-to-market motion, and none of them flatter anyone in a quarterly deck. That's the point.

They're also harder to pull, which is the other reason they go untracked. An indicting number usually requires somebody to agree on a definition first, and agreeing on a definition is where most measurement projects quietly die.

Where the cliff is

Win rate by stage tells us where deals fall off. The whole-funnel number never does.

Pull it from the CRM monthly. Work out what percentage of deals advance from demo to evaluation, evaluation to proposal, proposal to close.

Before any of that means anything, the stages have to mean the same thing to every rep. If two people can put the same deal in different stages, the number is measuring their habits rather than our buyers.

Then watch a single stage across a quarter. When the same one leaks month after month, that's a diagnosis rather than a bad month.

Deals dying after the demo point at messaging that isn't landing. Deals falling apart in evaluation point at enablement.

Find the cliff. Fix what's underneath it.

The clarity clock

A lengthening sales cycle is usually a clarity problem in disguise.

When buyers take longer, they're uncertain. Uncertain about the value, or about whether what we do is worth what we charge.

Track it monthly and use the median, because a couple of enterprise outliers will drag the average somewhere useless.

Watch the spread as closely as the trend. Deals closing in a month and deals closing in half a year, in the same quarter, means the message is inconsistent or the ICP has gotten too wide.

Cycle length varies by segment and deal size, so compare it against our own history instead of somebody's benchmark.

The second purchase

Attach rate is the percentage of customers who buy a second product after the first. Most companies don't track it, and the ones who start usually find something uncomfortable.

It's the cleanest read on whether our product lineup makes sense to anyone outside the building.

When attach rate is low, the instinct is to look at the product. Look at the positioning first. Buyers didn't understand that Product B existed for them, because nobody made the case that Product A was incomplete without it.

Repositioning an add-on from something nice to have into something the first purchase needs in order to pay off is a messaging job. It moves attach rate without a single change to the product or the price.

Track it quarterly and set targets by product combination.

The whole motion in one number

Sales velocity is the only one of the five that reads the go-to-market motion end to end.

Here's the arithmetic.

(Opportunities x average deal size x win rate) / sales cycle length in days

Volume, deal size, win rate, and speed all sit in one expression. When velocity rises, something is working. When it flattens, something has broken and the four inputs tell us which.

That's the useful part. Improving win rate through better enablement raises velocity without new headcount, new features, or a bigger pipeline number, and the formula shows exactly how much.

Calculate it monthly. Segment by product, region, and rep, because the segments where velocity runs highest are the ones where our motion already works.

Fingerprints on the deal

Marketing-sourced pipeline is the vanity metric that survived the purge. It rewards volume and encourages campaigns that generate leads nobody closes.

Pipeline influenced measures something harder. It's the total value of closed-won deals where marketing showed up inside the deal, not just at the top of it.

First touch doesn't count. A battle card pulled into a competitive cycle counts. So does a case study sent the week of the decision, or a calculator that got presented in a negotiation.

One custom field in the CRM builds this. Sales tags every deal where they used a marketing asset, and the reporting takes care of itself.

It's self-reported, so it drifts. Reps forget, and the field goes blank on the busiest weeks. Read it as a direction rather than an audited figure and it still beats anything sourced.

It changes the sentence marketing gets to say in an exec review. "We generate leads" becomes "we help close deals," and those are different value stories with different budgets attached.

If most closed-won deals carry no marketing fingerprints at all, sales isn't using what we make. That's an enablement problem, and now it has a number.

The monthly hour

Once a month, one hour, all five numbers on one page.

Find the widest gap between where a number is and where it should be. Name the likely cause, which is nearly always positioning, enablement, or an ICP that drifted while nobody was looking.

Then run one experiment. Only one, because changing two things at once means learning nothing.

Win rate is sliding at demo stage, so the hypothesis is that the positioning isn't landing, so the demo intro gets rewritten to open with customer outcomes instead of features. Watch that stage for thirty days and decide from the result.

Repeatable, unglamorous, and it works.

Put the page in front of the people who can act on it, which usually means sales leadership and whoever owns the roadmap. A number that only marketing ever reads can indict all it likes and nothing happens.

A go-to-market motion is only as honest as the numbers we're willing to let accuse us.

The five above never flatter anybody. They just point.

What to do next

If the dashboard is green and the revenue conversation keeps going sideways, the gap is usually positioning showing up as a metrics problem.

That's what a Bare Strategy positioning audit is for. We find the stage where deals actually die and the words that are causing it.

If that's where you are, start here. The first conversation is free.