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After doubling revenue and tripling headcount in a span of three years, Analytics8 earned a spot among the fastest growing and most innovative companies on the Inc. 5000 list.
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AWS, dbt, Fivetran, Looker, Snowflake
We have clean and vetted data and logic that our teams have confidence in—that can’t be understated. We have positioned ourselves with a modern platform that will grow with us as our use cases and business evolves. And now that we have the data foundation in place, we can start to push that data more meaningfully into our machine learning models and use that to drive product innovation back to the consumer.
iFit is an interactive fitness platform offering live streaming and on-demand workouts for members to do from their homes, gym, or outside. To retain its members and subscriptions in a highly competitive market, iFit must have a great understanding of their customers so that it can provide a superior customer experience and offer a product that keeps them happy and engaged. In addition, iFit wanted to take advantage of a booming virtual fitness market and was looking for outside funding to help it reach its aggressive growth plans. Investors were keenly interested in iFit’s user base and how it was growing—so, it was imperative that iFit could provide this analysis quickly, something it was unable to do without help.
iFit uses many systems (including Zendesk, Google Ads, Facebook, Twitter, Adroll, Stripe, Salesforce, and Segment) to track details about member profiles and their workout preferences. But the manual process to compile data from these systems for analysis was time consuming, prone to errors, and didn’t give iFit a confident understanding of what its members liked and didn’t, why members left, and what could incentivize them to stay.
iFit engaged with Analytics8 to develop a solution that would integrate all of its data and enable analytics so it could uncover the information the company needed to meet customer demands and grow its business.
We started by conducting a Data and Analytics Strategy Assessment. To kick off the process, we conducted interviews with business users to identify their daily processes and understand how they used their data. During these discussions, Analytics8 identified the key metrics iFit wanted to measure and profiled multiple source systems to outline the best system of record that would support their analysis.
With an understanding of iFit’s requirements and technical environment, the assessment concluded with a roadmap that detailed how to integrate data from iFit’s multiple systems into a cloud-based data repository to allow for unified analysis and simple addition of new data sources. The roadmap also outlined recommendations for the people, processes, technologies, and specific analytics that will help iFit use its data to better understand its customers, improve its offerings, and be able to answer questions from potential investors.
With the roadmap as a guide, Analytics8 deployed, configured, and implemented the recommended technologies and built iFit’s modern data architecture.
We moved very quickly from the roadmap to build the architecture and deploy the rest of the solution to enable end-users the ability to analyze their data in ways they hadn’t been able to do previously. We built a data warehouse in Snowflake, leveraged Fivetran to migrate historical data as well as current data, and used dbt to transform this operational data for source systems into the analytics model we designed.
As data was migrated into the Snowflake data warehouse, we were able to combine data from multiple source systems and model the data in a way that allowed for fast analysis. Within only two weeks, Looker was deployed “on top” of that data to further increase the end-user’s data analysis capabilities. We then built dashboards using Looker that allowed users to perform analysis on the fly and get immediate insight into their customer data. The dashboards tapped directly into the data warehouse, ensuring the data was accurate and up to date.
The dashboards we built analyze data about churn, workouts, membership, renewals, and retention—information that provided critical insights and analysis that outside investors were looking for.
The data and analytics solution we built allows iFit to move from disjointed analysis to drawing insights from a rich, unified dataset about its membership. iFit can now:
Armed with its new data strategy and analytics solution, iFit is poised to take advantage of the virtual fitness market, grow its member base, ensure customer satisfaction, and be better positioned to obtain outside funding to grow its business and fulfill its mission.
iFit is an interactive fitness platform that brings together fitness activities that take place in the home, gym, and outside, all with a single login and device. The company’s product provides maps, visualizations, and workouts for those working out on iFit-enabled equipment.
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