Kouros Esfahany is Chief Technology Officer of Locality, where he leads the ongoing evolution of the company’s technology platform, spanning LocalX, Darwin, and Collective. He also drives continued innovation across Audience Engine, advancing the data and AI capabilities that help advertisers plan, activate, and measure local TV performance with greater precision. He brings more than two decades of engineering and technology leadership from roles including Chief Technology Officer at XR Extreme Reach and eBay, and SVP of Engineering at FreeWheel, with deep expertise in bridging long-term technology vision with practical business outcomes.
Why Locality, and why now? What made this feel like the right move for you?
Local advertising is changing fast. Scale and precision are finally converging and Locality has the platform and data foundation to turn that change into outcomes.
What drew me to Locality was its strong cross-platform footprint and a clear commitment to centralizing its data strategy. With Audience Engine turning more than 25 billion local signals into predictive, actionable audiences, Locality isn’t just participating in the market- it’s pushing it forward with real-time, performance-driven outcomes.
Why now is simple: the market is demanding a more intelligent, more efficient way to connect buyers with premium local TV inventory. My focus is accelerating the technology that brings those pieces together- using automation, AI-driven insights, and integrated data- so execution gets faster and outcomes get better.
You’ve been at places like eBay and FreeWheel… when you look back, what did you learn there that shaped how you think today? And how does that apply to local?
In enterprise and ad-tech, a consistent lesson is that technology only matters when it reliably produces business outcomes at scale. At large platforms, you learn that “good ideas” fail without operational rigor- clear ownership, measurable feedback loops, and disciplined execution. At FreeWheel, I saw firsthand how complex it is to unify systems and workflows across linear and digital environments, and how critical it is to build platforms that can evolve without breaking the business.
I bring that same approach to local: build a unified foundation, instrument everything, and compress the distance between insight and action. That means not treating automation and AI as experiments, but as practical tools embedded directly into planning, activation, and optimization loops so teams move faster, and performance improves in ways customers can see.
When you look at local advertising right now, what feels like it’s changing faster than people realize?
What’s changing fastest is the expectation that local can deliver both reach and precision and do it with speed. Advertisers don’t want separate playbooks for broadcast and streaming; they want a unified workflow where planning, buying, optimization, and measurement are connected and accountable. That shift is accelerating as broadcast and streaming converge, and it’s raising the bar for data quality, identity, and real-time decisioning.
The second accelerant is data infrastructure. When you centralize data and operationalize it (not just report on it), you can move from manual workflows to audience-centric execution and closed-loop measurement. That’s the path to compounding performance improvements over time- because every campaign makes the platform smarter.
Everyone throws around the word “convergence”… but what makes it so hard to pull off?
“Convergence” is hard because it’s not a branding exercise, it’s an execution problem across data, workflow, and measurement. Broadcast and streaming each have distinct strengths, and buyers need a clearer, more consistent way to plan, execute, and measure across markets while still understanding the unique value each delivers. That requires unifying systems without flattening the differences that matter.
It also demands a shared data spine. Without centralized, operationalized data, teams end up stitching together tools and reports, which slows everything down and makes performance harder to prove. Pulling convergence off means building a unified platform that reduces friction for planners and produces consistent outcomes for advertisers at scale.
What separates tech that’s just “good” from tech that drives results? And what are you most excited to build at Locality over the next year?
“Good” tech ships features. Results-driven tech changes the economics: it reduces cost, increases throughput, and lowers risk and you can measure the impact. I’m a big believer that automation and AI should be deployed into well-understood workflows where they reclaim senior time, shorten planning-to-execution cycles, and improve consistency. That’s how you convert manual effort into margin and create operating leverage.
Over the next year, I’m excited to accelerate Locality’s platform evolution, advancing the capabilities across LocalX, Darwin, Collective, and Audience Engine so the marketplace becomes more intelligent and efficient for both buyers and inventory owners. The goal is simple: tighter feedback loops, faster execution, and more predictable performance across local markets.
What do you do outside of work that helps you reset a bit?
I reset by protecting a few non-negotiables each week- time for family, a bit of exercise, reading, exploring new ideas, and quiet time to think. That rhythm helps me show up with energy and clarity, especially in a role where good decisions depend on perspective as much as speed.
If someone walked away from this conversation, remembering one thing about how you think, what would you want it to be?
That execution is the whole game. Convergence, AI and Data, only matter if they show up as faster planning, better decisions, and measurable outcomes for advertisers. My job is to compress the distance between insight and action, so our teams and our advertisers move faster and see the results they need to move their businesses forward.
