When every product is turning into an AI solution, GTM playbooks and metrics are changing overnight. Products are selling faster, but with higher churn and longer CAC payback periods. Pricing models have been upended, complicating the traditional quota and compensation models of SaaS.
In short, the game has changed. We get daily questions from founders and GTM leaders from startups at every stage about the specific metrics underlying GTM performance. So, in partnership with our friends at Benchmarkit, we ran a survey to benchmark critical elements of performance from current, active startups.
Today, we’re releasing that data, along with our GTM Benchmarking Tool that shows the big picture of the data and lets you drill down to see how you compare. We homed in on specific data points that are simply not available elsewhere but make a huge difference in the daily and quarterly management of your GTM team, like win rate, the percentage of pipeline coming from different sources, and sales ramp timelines. You can filter by the metrics specific to your business, making a more direct comparison to other companies with your pricing model or at your growth rate.
Long term, this is part of our efforts to track GTM metrics in a robust, systematic way. We can’t wait to see the longitudinal data that comes from this. We know things like quota to comp and pipeline sources are changing in the AI era. And, we know the promise of AI is to reduce headcount in the sales and marketing org. With this data, we have the real numbers behind these questions. You can see some work we’ve already done around the difference between selling an AI vs. non-AI solution here.
Let us know how you use the tool and what other questions you have for us.
