Inside Arbol’s Multi-Thread GTM Strategy: Why Running 20 Experiments Beats Betting on One

“Almost every early effort fails.” In a recent episode of Category Visionaries, Arbol founder Sid Jha shared this sobering reality of entering regulated markets. But rather than letting this paralyze them, Arbol turned it into a strategic advantage.

The Multi-Thread Philosophy

Instead of betting everything on a single approach, Sid developed what he calls a multi-thread strategy: “You try 20 things, 30 things – all try to be cohesive. You’re not trying to just do 20 random projects. They should be cohesive. They should be among the same kind of theme. But you have to put a lot of threads out there… because 19 out of 20 of them will likely not get anywhere.”

Maintaining Coherence Across Experiments

The key to Arbol’s approach wasn’t just running multiple experiments – it was ensuring they all served a larger strategic vision. As Sid explains, their focus was on “connecting two very different groups together in a platform. So one group, the clients are the ones who need the climate insurance… On the other side is the question of okay, but it’s all great to have the product, but how do we write this insurance?”

The Power of Small Tests

This multi-thread approach began with their first transaction: “I remember it taking almost six months to arrange the first transaction, which was a grand total of $3,000 in gross revenue.” While the revenue was minimal, each experiment provided crucial insights about market needs and regulatory requirements.

Finding the Low-Hanging Fruit

With climate risk affecting nearly every industry, Arbol needed to be strategic about where to focus. As Sid notes, “Almost every industry on the planet is affected by climate. It could be an oil rig that’s facing possible hurricane. It could be a ski resort facing a warming winter with no snow… But really the work is in figuring out where is the low hanging fruit.”

Technology as a Unifying Thread

While running multiple experiments, Arbol used technology as a consistent foundation. “What we do is with data, right? So the payouts are linked to data. That’s what parametric insurance is. So it could be crop yield data, it could be wind speed data, it could be temperature data.”

Learning Through Failure

The multi-thread approach helped Arbol learn from failures without betting the company on any single initiative. As Sid recalls, “We put in an application for a government program, and it was over a year’s worth of work, hundreds of pages we put together. We got to the final stage, and then it was rejected.”

Scaling What Works

The strategy paid off dramatically. From that initial $3,000 transaction in 2019, Arbol grew to “about a couple of million” in 2020, followed by $70 million in 2021, and closed 2022 with $171 million in gross revenue.

The Future Vision

This multi-thread approach wasn’t just about finding what worked – it was about building understanding for future expansion. As Sid explains, “There’s a lot of interconnections now in these industries and any sort of climate event, seasonal weather event that happens in one part of the world can have cascading effects.”

For founders entering complex markets, Arbol’s multi-thread strategy offers a crucial lesson: instead of betting everything on a single approach, run multiple cohesive experiments that build toward a larger vision. The key is maintaining enough coherence across experiments that learnings from one area can inform your strategy in others.

This approach requires more patience than traditional “bet the company” strategies. But as Arbol’s journey shows, it can also lead to more sustainable growth and deeper market understanding.