How to Operationalize GTM Data to Improve Your SaaS Metrics: SaaS Metrics Palooza 2024
scaleMatters CEO & Founder Scott Stouffer presented at Benchmarkit's SaaS Metrics Palooza 2024. Here's the video replay along with 6 key takeaways.
Optimizing your Go-to-Market motion is a journey of continuous experimentation and iteration. No company begins with a perfect blueprint or a flawlessly tuned engine. Success comes from trying new approaches, learning what works, and refining over time.
However, there’s a right way and a wrong way to run GTM experiments. While creativity and innovation are crucial, they must be paired with a disciplined approach to measuring and analyzing outcomes.
Every company runs experiments, whether consciously or unconsciously. For instance:
Testing Ads: If your paid search ads are attracting the wrong audience—people outside your Ideal Customer Profile (ICP)—it wastes money and creates inefficiencies. Adjusting messaging in ads can be a quick fix, but without proper measurement, you won’t know if the change worked.
Evaluating Sales Processes: When a new sales tactic is introduced, companies often proceed without clear expectations or metrics to determine success.
Incorporating Product Features: If your product team launches a new feature and your sales team updates their demo, the change is often rolled out without considering it as an experiment.
These examples highlight a common issue: many companies fail to think through how to precisely measure the impact of their experiments.
Too often, companies:
For example, when tweaking ad messaging to attract higher-quality leads, it’s not enough to measure clicks or visits to your site. These metrics might just indicate more non-ICP traffic. The only reliable indicator of success would be an increase in the number of legitimate opportunities that sales teams identify from those leads.
Companies serious about Go-to-Market efficiency treat every adjustment as a structured experiment. Here's how:
Document Expected Outcomes
Before launching any experiment, define what success looks like. What is the desired outcome? Which metrics will change?
Establish Pass/Fail Criteria
Set specific thresholds that indicate whether the experiment succeeded or failed.
Set a Duration for Testing
Determine how long the experiment will run and commit to evaluating results only after sufficient data is collected.
Create Dashboards for Tracking Metrics
Build dedicated reporting panels or dashboards to monitor how key metrics are trending before, during, and after the experiment.
Start Small
Pilot the experiment with a limited group, such as a subset of sales reps or a small portion of your target audience. Roll it out more broadly only if it passes the test.
Monitor Closely
Keep a close eye on metrics during the test. For example, if you're testing a new demo, watch for changes in demo-to-pipeline conversion rates.
Gather Qualitative Feedback
Encourage team members—such as product marketing—to listen to calls, review demos, or observe prospect interactions to capture qualitative insights.
Structured experimentation reduces wasted spend across marketing and sales by identifying failing initiatives faster. It ensures that only successful tactics and strategies are scaled, avoiding inefficiencies and missteps.
Take the example of a new product feature added to the sales demo. By treating this as an experiment, a company can:
This deliberate approach minimizes wasted effort and maximizes learning.
B2B SaaS companies with a continuous process for experimenting, gathering rapid feedback, and iterating will lead in this era of efficient growth.
When you approach GTM experiments with discipline and structure, you create a culture of continuous improvement. The result? A more efficient, effective, and aligned Go-to-Market motion that drives growth while reducing waste.
That’s how serious companies win at GTM experimentation.
scaleMatters CEO & Founder Scott Stouffer presented at Benchmarkit's SaaS Metrics Palooza 2024. Here's the video replay along with 6 key takeaways.
If I had a dollar for every time I heard a CEO, CRO, or VP of Sales say, “We need better forecasting,” I’d have retired long ago.
How can modern GTM analytics tools help businesses react more quickly to market changes compared to traditional data storage, especially when...