Here is a great little story on how one GTM team made a software purchase decision. It’s something I believe is a good reminder if you’re still thinking in terms of feature comparisons and vendor evaluations.
Most teams are no longer trying to find the best tool, they’re trying to find something that works quickly enough to justify moving forward. Good enough is winning as long as it returns value quickly and is easy for the team to use.
A Different Starting Point
In a recent conversation with Tom Weiss, the Chief Product and Technology Officer at MX8 Labs, that shift showed up in a way that felt almost casual.
His team needed a CRM. They had tried stretching tools like ClickUp into that role, moved through a couple of alternatives, and ended up in a familiar place. Inconsistent usage, incomplete data, and very little confidence in what the pipeline actually looked like.
So he did what more operators are starting to do.
He opened ChatGPT and started asking questions.
Not to make the decision, but to get to a shortlist faster. From there, the process was straightforward. Spin up a trial, connect it to Gmail and Slack, and see if it works in practice.
Then came the filter that mattered more than anything else.
“If I can’t get a product working within half an hour, I dump it.”
There was no scoring model behind that. No formal evaluation framework. Just a very clear expectation around how quickly value should show up.
The Shift Beneath the Surface
We’re hearing versions of this more often.
Not always stated as directly, but visible in how decisions actually get made. The shortlist is smaller. The time spent evaluating is shorter. The emphasis has shifted from comparing capabilities to experiencing the product.
Part of that is driven by the environment GTM teams are operating in. There are now thousands of tools competing for attention, and most teams are under pressure to move faster without adding complexity or headcount.
Under those conditions, the cost of spending weeks evaluating options starts to outweigh the benefit of finding the absolute best fit.
So the question changes.
Not “which tool is best?”, but “which tool works for us right now?”
Where AI Fits (and Where It Doesn’t)
AI is clearly part of this shift, but not in the way most conversations frame it.
It’s not making the decision. It’s compressing the front end of the process.
Instead of searching, reading reviews, and building a long list of vendors, teams are increasingly starting with a generated set of options. They might refine it, challenge it, or add to it, but the initial field is narrower and faster to assemble.
From there, the decision moves into the product itself.
For buyers like Tom, what matters is what happens after login.
The 30-Minute Test
That’s where the 30-minute rule starts to matter.
- Can a team connect their core systems without friction?
- Can they understand how the workflow is supposed to operate?
- Can they do something that feels like real work, not just setup?
If the answer is yes, the tool stays in consideration. If not, it usually doesn’t matter what else it can do.
What’s interesting is that this isn’t a shortcut because teams are being careless. It’s a response to the volume of choice and the pressure to move.
Tom put it simply. He wasn’t trying to find the perfect system. He just wanted something that worked.
That mindset shows up in subtle ways. Once a tool clears that initial threshold, the rest of the evaluation often becomes lighter. The team starts using it, shaping it, and deciding based on real experience rather than hypothetical fit.
What Changes as a Result
When decisions are made this way, a few things start to shift.
- Long onboarding cycles become a liability rather than a sign of depth.
- Highly configurable systems can feel like friction instead of flexibility.
- Feature differentiation matters less if it takes too long to access.
At the same time, tools that guide users toward value quickly tend to create a different kind of momentum. Adoption happens earlier. Data becomes more consistent. The system starts reinforcing behavior instead of relying on discipline.
In MX8 Labs’ case, the biggest change wasn’t a new capability. It was that deals were actually getting tracked consistently. That alone improved visibility and confidence in the pipeline.
A Different Kind of Rigor
None of this means that GTM buyers are being less thoughtful.
If anything, the rigor is just moving to a different place.
Instead of trying to predict how a tool will perform, teams are testing it directly in their own environment. Instead of evaluating based on potential, they’re evaluating based on immediate experience. SaaS platforms have hit a level of maturity in 2026 that we expect things to work and be easy to use, and users can make this evaluation quickly once they are in.
Speed becomes a proxy for fit.
If something works quickly, it usually aligns with how the team already operates. If it doesn’t, no amount of additional functionality is likely to fix that gap.
Closing Thought
The 30-minute rule isn’t a formal framework, but it’s a useful signal.
It reflects a broader shift toward faster, more experience-driven decisions in a market where options are abundant and time is constrained.
The real question isn’t whether teams should adopt this approach.
It’s whether the tools they’re evaluating are designed to meet that expectation.
If a new user opened your product today, would they get to real value in the first session?
Or would they still be setting it up?
Now if you are curious what was the CRM that Tom and his team chose well you can read the full follow-up piece where we walk through the full details of that decision here.