To maintain the quality product their customers have come to love and expect, Skullcandy strives to be innovative in both product design and manufacturing. Their commitment to continue producing unique, high-quality headphones led Skullcandy’s Jesse Mease, Warranty Return Data Specialist, and Mark Hopkins, CIO, on a two-year project to better understand how their products fail and how they can reduce returns and keep their products affordable. Essentially, they wanted the ability to fix problems proactively by using historical data to predict the failure rates for new products within the first 90 days, and which specific part or function would fail.
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We are able to deploy a model or test a hypothesis within a day. The integration with our BI tool is seamless.
I love the ease of use that Kraken makes getting started with Machine Learning.
We’ve been able to analyze customer repurchasing patterns on our retail website, score leads, and forecast future sales.
Users can easily connect to data, pick which data to use in the model, see model metrics, and export results. It’s incredibly easy to make edits to the model or run new data through (with no coding and no variables to keep track of!), and we’ve been able to create a data pipeline to really streamline the process from source data to predictions.
Really helped to break open big data mystery and allowed us to take actionable insights