Achieving Instant Value with a Modern Data Platform

Building Les Mills International a modern data platform using Snowflake and Wherescape RED achieved instant value whilst accelerating time to insights.

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As part of building digital fitness, leading wellness solutions provider Les Mills International (LMI) has long recognised the value of data. In partnership with Qrious it has designed and architected a modern data platform delivering business insights using data from multiple systems.

Built on AWS and Snowflake using WhereScape RED automation, LMI has easy access to curated operational data for reports assessing past performance and providing insights to guide future growth.

LMI is the Les Mills group parent company. Les Mills on Demand (LMOD) is a video workout business established as a rapid-growth start-up, extending LMI wellness programs to individual customers at home with unlimited access to programs taught in 21,000 gyms internationally.

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The challenge

While LMI had clear notions of how data can deliver a competitive edge, it was hampered by its technology systems. “We had an immature BI environment and platform,” says Casey Toia, Head of Analytics at Les Mills International, “but we did have a great team of analysts who know how to run reports, pull them into Excel and use the data.”

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This prompted the engagement of Qrious. “We wanted help identifying the best platform and then bringing in BI and data specialists to establish and develop it. With the right platform and systems, we could empower our analysts with the capability to readily access data and deliver the insights we’re looking for.”

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Qrious performed a thorough series of workshops and meetings, conducting interviews with 66 people across LMI’s global operations. This was filtered down into a set of feedback and a roadmap with a list of projects and operational actions for LMI that included LMOD.

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With the right platform and systems, we could empower our analysts with the capability to readily access data and deliver the insights we’re looking for.

– Casey Toia, Head of Analytics, Les Mills International

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The solution

Based on LMI’s existing systems, Qrious recommended Snowflake running on AWS. “At LMI, AWS was already being utilised across the business, and we have S3 buckets feeding Snowflake where possible,” says Toia.

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S3 is AWS’s object storage, while ‘buckets’ refer to storage locations for data extracted from operational systems.

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“This turned out ideally, as with Snowpipe (Snowflake’s continuous data ingestion service) it is less costly to put data into S3 and then Snowflake – and costs like that can really interfere with your ROI numbers.”

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Among the recognised advantages of Snowflake over other platforms is that it is easier for analysts to work with, flexible, requires little or no support and can run locally and globally.

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Other elements include WhereScape RED for data warehouse automation, and Stitch for data acquisition from sources including MailChimp and Salesforce.

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The results

To date, Qrious has delivered the architecture and initial development projects. Data is flowing freely into LMI’s Snowflake platform, which tracks records which would otherwise not be collected. This includes LMOD app data such as the videos customers are watching, when ‘pause’ is pressed, subscription status and more.

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Historical Analysis

As a data-driven organisation, LMI uses data for both historical and forward-looking views. Says Toia: “The historical analysis evaluates decisions already made, for example, if we were to spent X amount on Facebook advertising for our direct-to-consumer app, then we could ask ourselves how many customers did we acquire, what was the cost per acquisition, and is it therefore worth investing more.”

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That one example, he says, is representative of multiple small yet essential data tasks which support continuous business optimisation. “We also use historical data to understand how we can deliver better customer experiences. Using the example of the B2C app again, we will be able to check the success of new videos released on our on-demand platform with metrics on when, for how long and how many times they are watched. And at an even more granular level, we can identify and analyse the features in the videos that capture customer interest.”

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Data from multiple sources of the business are combined and contextualised, including that from financial, marketing, sales and other systems contributing to multi-dimensional views of performance.

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Predictive Analysis

With the forward-looking view, KPIs for business metrics like net repeatable revenue are analysed and tracked. “With our targets, it becomes a mathematical exercise to get there, particularly when you have an idea of how marketing and advertising investments pay off in terms of customer acquisitions. We also look at things like profit level, customer numbers and so on. The data effectively tells us how achievable forward-looking objectives are.”

Despite the sophistication, it is still relatively early days as LMI continues exploring its data journey. “Thanks to Qrious, we have a platform which greatly condenses cost (compared to traditional approaches) while accelerating time to insights. As we work towards enabling more reporting and insights from Snowflake, leveraging data value wherever possible, we’re shifting from backward to forward-looking. We’re using data to create, understand and optimise our customer experiences.”

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Key outcomes

Agility and speed

Data is flowing freely into LMI’s Snowflake platform. Analysts are working faster, more efficiently and saving money.

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Business optimisation

Data from multiple sources of the business are combined and contextualised, contributing to multi-dimensional views of performance.

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Time to Insight

The lifecycle of planning/delivery to insights has been drastically reduced. The time to insight is now a matter of days not months.

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Competitive edge

LMI are now using data to create, understand and optimise their customer experiences. This allows the business to meet and exceed customer expectations and gain a competitive edge.