A Technical Product. A Non-Technical Buyer.
Third Axiom's flagship product, Axiom-One, was an enterprise analytics platform built for large shippers and 3PLs like UPS Healthcare and Ascent Global Logistics — companies with the resources and the analysts to make sense of complex data.
It was a hard sell to mid-size logistics providers. But our market research pointed to real opportunity — and real hunger — at that level, so we launched Axiom-Apps: a lighter, out-of-the-box version of the same analytics engine, built for mid-size freight brokers.
The launch flopped. We booked demos, but no one signed up — not even for the free trial. Discovery calls told us why: most mid-size brokers didn't actually know what they needed out of their analytics. They knew something was wrong with their margins; they didn't know how to ask a tool to find it.
Our buyers weren't analysts. They were freight brokers running their business on spreadsheets, manually pulling numbers to answer questions like which carriers were eating their margin or missing delivery windows. They didn't know what a "data story" was, let alone how to find one in their own data.
We needed two things at once: real usage from this new mid-market segment, so we could learn what actually mattered to them and what we still needed to build — and a way to build category awareness in an industry that was reluctant to change and skeptical of AI.
Selling the product straight wasn't going to get us there. We needed a way in.
One program. Three strategic objectives.
After our first launch failed, we relaunched with the Analytics Adopters Program — one program built around three strategic objectives: expand reach with a co-marketing partnership to get in front of brokers we couldn't access on our own, close the education gap that was actually blocking conversion, and build a product feedback loop that let us test and improve Axiom-Apps quickly.
Here's how the trifecta played out:
I partnered with Tai TMS, a transportation management system already embedded in our ICP's daily workflow, to bring the program to life. Tai TMS brought credibility with mid-size brokers who already trusted their platform; we brought the analytics education brokers needed. It also gave us a channel we could keep returning to — we leaned on our ongoing relationship with Tai TMS to keep promoting the program well past its initial launch, extending its reach far beyond a single campaign.
We gave brokers 12 weeks of free access to Axiom-Apps' three core analyses — Carrier Management, Lane Management, and Customer Management — paired with hands-on guidance from our team. Rather than dropping users into a complex tool and hoping they'd figure it out, we sent a series of bite-sized analytics activities straight to their inbox over the first 30 days — starting with data prep and basic filtering, building up to scorecards and change monitoring, and finishing with more advanced capabilities such as forecasting and rate change analysis. Each activity taught one concept and one workflow inside the product, so brokers who'd never done more than a pivot table were building real analytical fluency long before their 12 weeks were up. In exchange for showing up, brokers earned a discount on their first year.
The curriculum did double duty: a guided on-ramp for brokers, and a built-in research engine for us. Regular feedback sessions surfaced exactly which analyses landed, which fell flat, and what a mid-market broker actually needed next — insight no demo, survey, or sales call could have given us. That signal let us improve the product on the fly and chart a roadmap grounded in real market behavior, not one-off requests.
Real Usage. Real Feedback. Real Pipeline.
The relaunch worked. Where an unguided free trial had produced demos and no sign-ups, the Analytics Adopters Program got mid-size brokers actually using Axiom-Apps, gave us structured feedback on what to build next, and turned analytics education into qualified pipeline — all in a single quarter.
Brokers who came in never having done more than a spreadsheet pivot table were identifying margin-eroding lanes and carriers within their first 30 days — exactly the kind of product-led insight no demo could have surfaced.
“This program has completely changed the way I approach analytics. Learning a small piece of the application every week starting with the basics made it easy to build a foundation without feeling overwhelmed.”
David Decovnik, Truckload Operations, Concept Logistics