We Put “Reasoing AI” to the Test—Here’s What We Learned in Sales & Marketing

Most of us have seen AI hype before, but does it truly cut through the noise? Over the past few weeks, we decided to find out by integrating a new Reasoning Model (R1) into our own platform. Instead of chasing vague promises, we wanted to see if AI could deliver tangible, day-to-day value—specifically, in how we identify and qualify leads.

Our Experiment

We let R1 loose on all the usual sales and marketing chores that soak up hours of valuable time. Think scouring LinkedIn for the right contact, analyzing partial data in random spreadsheets, and pulling bits and pieces of context from different websites. Could an AI model actually do the heavy lifting we typically associate with a seasoned business dev or marketing ops guru?

Surprising Outcomes

Turns out, R1 didn’t just “fetch” data; it thought through how each profile or contact fits into our bigger business goals. Almost like it had a tiny boardroom in its head, discussing each lead’s relevance and synergy. Our time spent defining target groups dropped dramatically (in some cases by 75%), and lead qualification went down by roughly 90%.

But the real “wow” moment was watching R1 explain why certain leads made more sense than others. We often found ourselves nodding along—“Yes, that’s exactly the logic we’d use!”—only we hadn’t spelled it out for the model. It was just there, connecting the dots in ways that felt surprisingly human.

From Hype to Impact

What does this mean for sales and marketing teams? It’s a glimpse of AI stepping beyond the “cool tech” label and into the realm of tangible, everyday impact. Less sifting through irrelevant data, more time spent talking to the right people. Less guesswork, more clarity. And, crucially, less of that sinking feeling when you realize you’ve been barking up the wrong tree for days.

Join the Conversation

We’re sharing this story because we know there’s plenty of skepticism out there. AI can feel like smoke and mirrors—until it proves itself. If you’re curious about how we got R1 to play so nicely with our data, or if you’ve got your own tales of AI success (or failure!), let us know in the comments. Let’s compare notes and see how we can make AI a truly practical ally rather than just another buzzword.

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