Most analytics tools tell you what happened yesterday. But that simply isn't good enough anymore.

If you're building on top of an LLM, powering a personalization engine, or letting an agent make a decision in the session, yesterday's batched dashboard is increasingly the wrong input. You need behavioral data that is accurate, enriched with context, and available the moment an event happens.

That shift is exactly why the "Real-Time Analytics Platform of the Year" category now exists, and why we are pleased to share that Snowplow has been named its winner in the 2026 Data Breakthrough Awards. 

The program had over 3,500 nominations this year, with winners across categories including Box, MongoDB, Fivetran, Dremio, and Grafana. Good company to be in.

But this post is less about the award itself and more about what the category says. Because "real-time analytics platform of the year" is a phrase that would not have meant much five years ago. Now though, it means a lot. 

Why the category matters

For many years, real-time analytics was seen as a nice-to-have. You’d have a live dashboard here, a streaming use case there. But for the most part, teams ran on batched pipelines and hourly refreshes, and it worked. 

Then AI changed the rules of the analytics game. 

An LLM-powered agent answering a customer question needs to know what the customer did thirty seconds ago, not last week. A personalization engine picking the next product needs the full session, live. A fraud system flagging a suspicious transaction cannot wait for the overnight job.

Decisions are now moving out of the dashboard and into the application. And applications need event-level behavioral data, in real time, with enough context that a model can actually reason over it. 

Here is how the judges put it:
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"Snowplow delivers real-time context infrastructure and validated behavioral data, powering historical analysis, AI models, and real-time decisioning at the same time. Most analytics platforms force you into closed systems that tell you what happened yesterday. Snowplow takes a different approach: customer context infrastructure that collects granular behavioral data and delivers it in real time to your own data systems."
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— Steve Johansson, Managing Director, Data Breakthrough

The part worth underlining: historical analysis, AI models, and real-time decisioning at the same time. Snowplow's event stream powers your warehouse, your AI layer, and your operational systems. 

What this looks like in practice

HelloFresh operates across 18 markets and processes millions of customer interactions daily. But under its previous analytics stack, behavioral data took up to 36 hours to become available. For a company trying to personalize experiences in the moment, that delay was crippling. As David Castro Gavino, Global VP of Data at HelloFresh, put it: "When we're trying to personalize this experience, it's really hard to optimize that journey when we don't have the data to drive that change."

After switching to Snowplow, that 36-hour wait dropped to under 5 seconds, with over 99% of events available in real time. But speed was only part of the story. Data accuracy jumped to 95% parity with backend systems (up from 33%), and the team captured 67% more anonymous session data, giving them a far more complete view of the customer journey.

HelloFresh now has AI-ready behavioral data powering personalization, multi-touch attribution, and real-time experimentation across its global operations. One event stream feeding the warehouse, the AI layer, and operational systems at the same time.

A Big Thank You

The real credit for this award goes to our customers, who push us to build for production workloads rather than demos. And to the Snowplow team who ship it.

If you want to go deeper on what real-time behavioral data makes possible, our real-time personalization guide is the best place to start. And if you are evaluating a real-time behavioral data foundation for your own AI or personalization workloads, get in touch. We’ll be happy to talk through the specific workload you are trying to support.