SALT LAKE CITY, June 11, 2019 /PRNewswire-PRWeb/ -- Big Squid, the global leader in automated machine learning, today announced that Skullcandy, the original lifestyle audio brand, has partnered with Big Squid to use automated machine learning to forecast product returns, identify failing parts, and improve manufacturing.
With this partnership, Skullcandy continues its legacy of innovative problem solving by pairing its manufacturing processes with predictive analytics.
Big Squid CEO, Chris Knoch, believes Skullcandy is just scratching the surface on their machine learning applications. "Skullcandy is an incredibly creative and innovative company and I am thrilled to see how they scale Kraken and machine learning across their entire organization in the future."
CIO Mark Hopkins explains, "What we wanted to know with this project is if there is a way we can predict what's going to go wrong with new products we introduce, and if so, because we haven't introduced them yet, how can we engineer products so that problem doesn't occur?" Answering this question led Skullcandy and Big Squid to create two separate projects.
To understand the factors driving warranty returns and impacting customer sentiment, Skullcandy's Warranty Return Data Specialist, Jesse Mease, worked with the Customer Service and Data Science teams at Big Squid to build a custom Natural Language Processing program that identified repeating words and phrases. Jesse then used Sisense, a business intelligence tool, to visualize and filter the results in a custom dashboard, giving him the ability to quickly identify potential problems.
"In Sisense I was tracking down a newly launched product and saw customer reviews indicating a recurring failure mode," said Zach Mayott, Sustaining Engineer for Skullcandy. "Our engineers took this data, filtered down to a problem, and sent the problem to manufacturing. Had we not had this data we wouldn't have known the products were failing in the field."
Chris Knoch went on to elaborate on the integration between Sisense and Kraken. "We have worked very hard to make Kraken as easy to use as possible and part of that is its seamless integration with technologies already being used by data and analytics teams. We can't wait to see what they do next."
The second project involved using Skullcandy's historical return data and machine learning to predict month by month product returns. Using Kraken, Big Squid's automated machine learning platform, Skullcandy was able to build predictive models that accurately forecast how many products will be returned in any given month. With this information, they are able to identify correlations between features and attributes that have failed historically and make improvements to future products.
This partnership further demonstrates Big Squid's commitment to BI and bringing machine learning to non-data scientists.
About Big Squid:
Machine Learning is helping companies become data-driven faster than ever before. Big Squid empowers businesses to understand their data and to take action on it in ways that traditional business intelligence and analytics tools are not yet able to do. Our AutoML platform, Kraken, was designed to augment your existing analytics capabilities. Kraken quickly surfaces true statistical insights and diagnostic analytics and empowers business analysts to deliver predictive and prescriptive analytics solutions all within your existing data and analytics infrastructure.
SOURCE Big Squid
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