Huel Creates the Perfect Blend of Data to Drive Product and Service Improvements

Behind Huel’s plant-based products is a powerful mission: To offer nutritionally complete, convenient, affordable food with minimal impact on animals and the environment.

Behind every nutrition drink, powder and bar is a wealth of data that informs product development, customer service and go-to-market strategy. However, as Huel has rapidly grown from startup to a household name, it needed a new way to manage its expanding data ecosystem.

Working alongside Snowflake, Huel deployed the AI Data Cloud on Amazon Web Services (AWS) to automate key data processes, simplify security and governance, and build a single source of truth that supports every team across Huel.

In 2015, Huel started selling their ready-to-drink meals and powders directly to customers. Just four years later, it had become a household name in its native U.K. and began selling products further afield in the EU, U.S. and Japan.

When a business grows so quickly, it’s imperative to invest in critical systems that can keep pace. “What we needed was something that could support different phases of our growth,” recalls Luke Whittaker, Lead Data Engineer at Huel. “A traditional data warehouse would have been way too big for us then. But now it might not be able to keep up. So scalability was a key concern.”

Huel wasn’t just interested in scaling size though. It also needed to consider how its data platforms could adjust to changing requirements. For instance, as the brand started selling products through conventional retail chains, it needed to get meaningful insights into how those customers engage with its products — and link those insights back to data from Huel’s own ecommerce platforms.

After considering several tools, Huel landed on Snowflake’s AI Data Cloud due to its scalability, simplicity and familiar SQL-based environments. “We considered a few options, but quickly realized Snowflake was the right choice for our use case,” Whittaker says. “Its ease of use and the breadth of the platform were exactly what we needed.”

Within a single month, Huel deployed Snowflake and began integrating it with other tools across its data stack, including dbt and Amazon S3 storage. Acting as the central hub for Huel’s data workloads, Snowflake processes and blends data from across Huel’s operations to deliver vital insights.

For example, all customer feedback data is pulled into Snowflake directly from ZenDesk and is used to create reports on any customer issues. This insight is then fed to product and ecommerce teams so they can quickly adjust Huel’s website and products — and deliver the very best customer experience possible.

Huel has already made the most of faster, richer analytics in Snowflake to make smart, data-driven decisions around its expansions into different regions. For example, it carefully tracks how every product performs across all channels, in all territories, and updates these reports regularly so product and marketing teams can quickly see when they need to pivot. 

“We have a trading tracker used across the whole business,” explains Whittaker. “It has our North Star KPIs for leadership, but goes down to a layer of granularity where we can see things down to the market, product and channel level. That’s helped us understand where some products perform differently across markets, for example.”

Going from a startup approach to a complete cloud data platform can be complicated. Thanks to Snowflake’s SQL-based platform though, Huel’s data team was able to get up to speed quickly. “Everyone in the team was comfortable with SQL, so we could move quickly,” says Whittaker. “If we’d chosen a platform that demanded extensive engineering, that would have been a real blocker.”

Speed didn’t mean Huel had to compromise on security either. The data team was able to integrate Snowflake access with Google Workspace Single Sign-On, making it fast, secure and easy to manage. And with Snowflake’s Trust Center, Whittaker is able to get further recommendations on how to resolve other security issues across Huel’s platform.

With a wealth of data stored in Snowflake, Huel can also automate many of its data processes. These automations have stacked up to save approximately 200 hours a month across the organization. That means teams can spend less time on manual data management, and stay focused on the most impactful parts of their work.

Even at the earliest stages of its Snowflake journey, Huel benefited from significant time and cost savings. In fact, in a single piece of analysis performed within weeks of going live in Snowflake, the platform generated enough value to pay for itself over the next two years.

Moving forward, Whittaker and the Huel data team are keen to do more with Snowflake’s feature set and find new levels of efficiency. “My goal is to make Snowflake the one tool we use for everything data-related,” says Whittaker.

Huel is also particularly interested in exploring ways to use new AI and machine learning solutions. Teams are already testing generative AI agents to streamline workflows and rapidly generate complex SQL for deep analysis and forecasting, but Whittaker is keen to see how this could be taken further: “We already save hundreds of hours each month through automation. By bringing everything AI-related into Snowflake and Cortex AI, I think we can take that number even further.”

Whatever comes next for Huel, the data team knows it has a flexible, easy-to-use platform ready to support its ambitions. “Speed of insights is essential to our goal of making nutrition easy for a broad audience and continuing to keep our customers happy,” says Ollie Scheers, Chief Technology Officer at Huel. “Snowflake delivers that consistently. There’s no overly complex pipelines, engineering or integrations getting in the way — just the data people need, when they need it.”