in query performance
in data infrastructure costs
in subscribers
Region: North America
Industry: Healthcare
Department: BI/Analytics/Data Science
Company Background: BODi is an interactive, inclusive “Health esteem” platform comprised of an app and an online streaming service of different workouts
BODi helps people create sustainable healthy habits and live fulfilling lives. More than 2 million subscribers use BODi’s online platform which offers on-demand workouts, nutritional programs and supplements, and mindset classes. BODi ingests and analyzes large amounts of subscriber and order data to support its customer retention and engagement initiatives.
BODi’s previous data architecture consisted of multiple data processing and storage technologies. Order data was stored in an on-premises data warehouse, while BODi’s online interaction data was kept in the cloud.
An enterprise data lake housed data from BODi’s online fitness community, mobile app, and marketing campaigns. “Our inability to connect data sources at scale increasingly became an issue—especially with millions of subscribers and orders per year,” says Armen Rostamian, Vice President of Marketing Intelligence & Analytics at BODi.
Siloed data prevented BODi from achieving a 360-degree view of the customer, inhibited marketing and distributor insights, and made it difficult to correlate behaviors that impact health goals. According to Rostamian, “We had a nutritional supplement mindset and a fitness workout mindset, but we weren’t able to have a wellness mindset.” Technical constraints led to additional complexity and delayed time to insight by up to 48 hours.
Seeking to effectively leverage data to support customer health and business outcomes, BODi centralized data ownership into a single data analytics team and began reimagining its data architecture.
BODi chose Snowflake’s Data Cloud™ to serve as the “core layer” of its data architecture. “It’s hard for me to even come up with a comparable competitor to the solution that Snowflake provided,” Rostamian says.
Snowflake’s near-infinite scaling of storage and compute solved BODi’s latency issues and allowed technical staff to focus on eliminating complexity and unifying data. According to Rostamian, “With the power of Snowflake’s computation, we centralized the work around the data and ultimately achieved a single source of truth for customer, distributor, and financial data sets.”
Consolidating video consumption, purchase history, and other interactions in Snowflake provided increased levels of transparency into BODi’s customer journey. “For the first time, we were able to understand the customer’s full interaction with the brand at scale and focus on the highest value customer actions,” Rostamian says.
Snowflake’s ability to work with Alteryx made it easier to deliver actionable self-service insights for BODi’s analytics users. By combining Snowflake’s powerful infrastructure with Alteryx’s intuitive interface for analytical problem-solving, BODi makes the data stack more accessible from start to finish. Teams can get the data they need, transform it with Alteryx, and share insights at scale across teams.
Doing the first 80% in data analytics and the last 20% in departments that are closest to the data allows us to efficiently support the data needs of the entire organization.
Armen Rostamian, Vice President of Marketing Intelligence & Analytics
BODi
BODi’s self-service analytics environment, powered by Snowflake and Alteryx, efficiently delivers meaningful insights to users across the organization.
According to Rostamian, “Now we’re able to work together and have a handoff point that enables a less expensive route to the best outcome.” For example, BODi’s royalty department closely monitors qualified video views that result in royalty payments. BODi’s marketing and fitness teams also depend on self-service video consumption insights despite maintaining different definitions for “qualified” views.
Leveraging data as the foundation for sales promotions helps BODi’s marketers develop creative campaigns that drive engagement with distributors. Successful campaign execution has resulted in more engaged distributors focused on sales. “We’re able to accurately execute complex monthly promotions faster than ever while investing fewer resources,” Rostamian says.
Using Snowflake to centralize data for approximately 80 customer attributes provides a customer 360 across multiple touchpoints. Machine learning (ML) models use data stored in Snowflake to assess customer loyalty, predict their future activity levels, and estimate their propensity to purchase.
BODi’s customer scoring system provides marketers with a single data point for recommending relevant content and developing campaigns that resonate. According to Rostamian, “We’re able to arm marketers with KPIs that are much more actionable and directly link to revenue.”
Modernizing BODi’s data architecture makes it easier to support the diverse forecasting needs of multiple departments. Just as BODi helps people take a holistic approach to their health with multiple nutrition and fitness approaches, the BODi team empowers multiple teams to access data insights. A unified, self-service stack with Snowflake and Alteryx makes it efficient for different functions to drive outcomes from the same data process.
Alteryx and Snowflake enable us to have variations in our forecasting that are use-case specific.
Armen Rostamian, Vice President of Marketing Intelligence & Analytics
BODi
For example, BODi’s finance team relies on Alteryx and Snowflake for its ongoing revenue forecasting initiatives. Operations teams analyze a variety of ingredient-related variables to make informed procurement decisions. Marketers compare baseline forecasts to incremental activities.
Region: North America
Industry: Healthcare
Department: BI/Analytics/Data Science
Company Background: BODi is an interactive, inclusive “Health esteem” platform comprised of an app and an online streaming service of different workouts
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