GTM Metrics That Actually Matter Now
The metrics we use to measure go-to-market were designed for a different era, one where human effort was the primary driver of outcomes. Modern buying, and AI-augmented teams, need a different scorecard.
Activity metrics made sense when human effort was the primary driver of outcomes. If a rep made more calls, sent more emails, and booked more meetings, more revenue followed, roughly, on average. So we built a whole scorecard around counting the effort: MQLs, SQLs, dials, opportunities created.
Two things broke that logic. First, modern buyer journeys are non-linear, multi-threaded, and increasingly digital: the tidy funnel the activity metrics assume barely exists anymore. Second, AI now does a growing share of the effort. When an agent can make the calls, send the follow-ups, and prep the meetings, "number of activities" stops measuring anything you actually care about.
The metrics we use to measure GTM success were designed for a different era. If you can't influence a metric, you shouldn't be measuring it.
The test: can you actually influence it?
That last line is the whole filter. A good metric is one your team can move with a decision. A vanity metric goes up and to the right regardless of what anyone does: impressive on a slide, useless for steering. As you rebuild your scorecard, put every number through that single test: if we can't influence it, why are we measuring it?
Three swaps worth making
The shift isn't about adding more dashboards. It's about replacing effort-era proxies with outcome-era truths:
- Customer lifetime value over deal size. A big first deal that churns in a year is a loss dressed as a win. What matters is the total value of the relationship, not the size of its opening move.
- Time to value over sales-cycle length. How fast you close is about your process. How fast the customer gets value is about their success, and their success is what renews.
- Net revenue retention over new-logo acquisition. In the consumption era, the revenue you keep and grow inside existing accounts dwarfs the revenue you win from new ones. NRR is the number that reflects it.
The metric almost nobody tracks: coverage
There's one more number worth adding, and it's the one that quietly caps all the others. Call it coverage: the share of your accounts that get real, ongoing attention rather than a quarterly check-in and a hope.
For most teams, coverage is brutally low: the top ten or twenty accounts get a person's focus, and the long tail gets a newsletter. Every retention and expansion metric you care about is bounded by it, because you can't drive value in an account nobody is watching. As AI lets attention scale past the handful a human can hold, coverage becomes both measurable and moveable for the first time, and it's the leading indicator behind NRR itself.
This is why we obsess over giving every account continuous attention and measuring the book by NRR, time-to-value, and coverage rather than activity counts. The old scorecard measured how hard your team worked. The new one measures whether your customers are succeeding, and whether every one of them is being watched.
Measure outcomes, not effort: net revenue retention, time to value, and how much of your book is actually covered.
See the book, covered →
Outcom.AI