Founder Stories: Value Creation at Axiom

Neil Patel is the CEO and co-founder of Axiom, a platform that lets customers stop sampling event data and observe every event—delivering 100% of their data for every operational and analytical need.

Building for Engineers Like Us

When we first started Axiom, everything we did was technical. My co-founder and I are both engineers by training, so it was natural that our focus was on the technical challenge — how to make ingesting, storing, and querying event data dramatically cheaper and faster.

At that stage, our version of “value creation” was simple: stop throwing data away. We wanted companies to stop sampling events, stop guessing which data mattered, and instead store and query everything. That idea felt powerful — especially to engineers who knew how painful it was to operate with partial visibility.

But back then, I thought of value purely in engineering terms. Cost reduction, performance, visibility — all important, but not enough. It took us some time (and a few humbling lessons) to realize that true value meant much more than technical efficiency.

Expanding the Definition of Value

Two moments really changed the way I thought about value creation.

The first was when we were hiring our Head of Product. During the interview process, he started asking big questions about our vision — not just what Axiom did, but what problems we wanted to solve for customers and how we’d evolve over time.

As we talked, something clicked. We realized we needed to articulate where Axiom could be exceptional, not just what it did technically. That conversation helped crystallize our thinking, and he eventually joined the company. Together, we started going out to customers and asking where they saw the most impact.

Those conversations showed us that our value didn’t sit in isolated use cases. The real magic of Axiom was how it could act as the connective layer — the glue between data sources, teams, and tools. Once we saw that, everything else started to align.

The second shift came when we began talking to larger enterprises. These companies weren’t just evaluating what Axiom could do today — they wanted to know if we’d still be relevant in three, five, or ten years. They wanted to see how our roadmap fit into their multi-year strategy for data and AI.

That forced us to get much better at telling a long-term story: how Axiom could stay ahead of the market, continue to save money, and keep unlocking new opportunities for insight and automation.

Now, every time I speak to a big customer, I think in those terms. They’re not just buying a product; they’re betting on a partner who will still deliver value years down the line.

“Every buyer wants to feel they’re making the right call. Our job is to make them heroes inside their companies — people who can look back and say, ‘That decision to go with Axiom still pays off today.’”

Building Relationships Through Curiosity and Honesty

If I had to name one thing that’s helped us most in selling Axiom, it’s genuine curiosity. We’re deeply interested in our customers’ problems — from the most technical engineer to the most senior decision-maker.

That curiosity helps us ask better questions and build trust. So does honesty. We’re transparent about where Axiom fits and where it doesn’t. If something’s not a good use case for us, I’ll say so. Engineers respect that — and it builds credibility fast.

We also push to get technical users into the product as early as possible. Once they can see the value firsthand, the conversation shifts from theory to proof.

Who We Sell To — and Why They Care

Our Champions are typically in platform engineering or DevOps — senior engineers or “Head of” roles. These are the people living the pain every day. Platform engineering is often underfunded, and anything that makes their lives easier while cutting costs feels almost like magic.

For them, the value is immediate:

• Moving from partial sampling to 100% observability.
• Eliminating engineering overhead spent pruning and archiving data.
• Keeping data far longer without blowing up costs.
• Moving from reactive firefighting to proactive insight.

Once they experience that, we start talking about the future value — what becomes possible when you have all your data in one place: richer analytics, better predictions, and faster experimentation.

Our Economic Buyers — usually CTOs or CIOs — care about those things too, but they start with cost. Most companies today are effectively leasing their own data — paying multiple vendors to store fragments for short retention periods. We show them how Axiom consolidates that, keeps costs predictable, and sets them up for the AI era.

But for these senior buyers, cost savings aren’t enough. They want to see how we fit into their three-year plan — how we’ll help them move faster, innovate safely, and stay ahead of their competitors. That’s where our conversations get really strategic.

Making Value Real

We’ve learned that value stories are more powerful when they’re experienced, not just told. That’s why we have a generous free tier and a low-cost team plan. In most cases, people become Axiom users long before they talk to our sales team.

If they’re not already on the platform, we’ll run a short Proof of Concept, usually four weeks. We try to get their data flowing into Axiom even before the PoC officially starts. The faster they can see results, the faster they understand the impact.

Seeing is believing — especially when “no sampling” suddenly means faster troubleshooting, fewer blind spots, and better insights across the board.

Learning From How Customers Use the Product

Because so many prospects are already using Axiom, we get a rich view of what they’re trying to achieve.

If we see them adding new data sources, we know they’re expanding use cases. If they start running more complex queries — say, moving from short time-window operational queries to deep analytical ones — that tells us they’re evolving from visibility to intelligence.

We analyze those patterns across tens of thousands of users, and it helps us anticipate where the next pockets of value will be.

We’ve even built a scoring system that flags customers likely to benefit from deeper use. It helps us guide conversations with both Champions and Economic Buyers — and it gives buyers confidence that Axiom will scale predictably with them.

Predictability matters. When customers can forecast cost and performance, they’re comfortable building internal tools or even customer-facing products on top of Axiom. That’s when we stop being a vendor and start being part of their infrastructure.

Communicating Value Back

For Champions, we want to make it as easy as possible to experience the “aha” moment. Once they see full data visibility at a fraction of the cost, the conversation takes care of itself.

Right now, every company is defining its AI strategy, and the fuel for AI is data — complete, long-term, accessible data. If you’re still sampling, you’re already behind. We show them that Axiom is the platform where they can record everything, keep it as long as they need, and do it efficiently.

For Economic Buyers, it usually comes down to two things:

1. Total Cost of Ownership (TCO). We benchmark their current costs — data ingestion, storage, tools, and people — against what it would look like with Axiom. The difference is often huge.
2. Strategic Alignment. We take their two- to three-year goals and show how Axiom enables them. Whether it’s platform consolidation, AI readiness, or cross-team analytics, we connect our roadmap to theirs.

Those two conversations — near-term savings and long-term enablement — are what close the big enterprise deals.

The Moment It Clicked

The first time I really felt the power of what we’d built was at AWS re:Invent 2023. We had “NO SAMPLING” printed across the booth, and it stopped people in their tracks.

Over five days, we spoke with thousands of engineers and executives. I personally talked to around 800 people. By Day 2, our meeting room was fully booked for the rest of the week.

Again and again, we heard the same reaction: “Where the hell have you been?”

That week confirmed that we were solving a real, urgent problem — one that customers immediately understood and cared about. It gave us huge confidence that Axiom wasn’t just a great product; it was something the market genuinely needed to exist.

Looking Ahead

Value creation for us started as a technical story about saving data. It’s evolved into something much bigger — helping companies see everything, act faster, and build confidently toward an AI-driven future.

When customers stop sampling their data, they stop sampling their potential. That’s the real value Axiom delivers — and it’s what keeps me excited every day.

This interview is adapted from Value Creation Explained by Rav Dhaliwal and Ben Wright, published by Crane Venture Partners.

Learn more at axiom.co.