True to brand reputation, Etsy's (NASDAQ: ETSY) IT infrastructure was crafted in-house for years. In fact, the company once showed off its homegrown tech infrastructure -- 3000 servers kept the site running in the days before Etsy's April 2015 IPO -- and dismissed cloud computing as insufficiently responsive to their needs.
In subsequent years, investors were saying the same thing of Etsy. CEO Josh Silverman has since begun turning things around for the company and focused on streamlining operations, firing 8% of the workforce and canceling in-house projects like craft tutorial site Etsy Studio. He's also reassessed how Etsy's IT infrastructure can support an online retailer as big data shapes e-commerce.
Embrace the Machine
Machine learning -- i.e. using different high-speed computing tools to analyze pools of data so large that they require computing power beyond the usual spreadsheet or relational database management system -- is emerging as a competitive advantage for online retailers. Machine learning can suggest related items shoppers might like to buy, customize a website to reflect a customer's demographic profile or shopping history, or help a retailer optimize its pricing strategy.
Another appeal to analyzing big data: machine learning's predictive capacities, i.e. the ability to forecast what shoppers will do at certain times of the year or in response to certain events. Target (NYSE: TGT) has one of the most notorious cases of big data's predictive capacities getting ahead of customer -- it correctly sussed out a teen customer's pregnancy before her parents did -- but machine learning boosted its revenue by 15-30%. Recommendations generated by machine learning and personalized for each shopper are responsible for 55% of Amazon's (NASDAQ: AMZN) sales.
Etsy's already got recommendations engines in place -- go to the front page of the site as a registered user and you'll see the products the site thinks you'll like -- but CTO Mike Fisher said the company's aiming to boost its use of machine learning tools as it pursues its stated focus of boosting site sales.
The company cited an example of that in its recent earnings call, talking about how machine learning has refined search results by context-specific ranking, offering a user results that take into account factors like the user's location, age, recent activity on Etsy and history of favorites.
Swapping DIY Servers for the Cloud
Machine learning takes considerable computing resources -- and here's where the cloud comes back into play. Cloud services offer their customers access to the computing power necessary for big data crunching. In December 2017, Etsy announced they were moving to Google (NASDAQ: GOOG)(NASDAQ: GOOGL) Cloud. The company's spin:
The side benefits: Moving to the cloud can reduce overhead costs in-house -- a priority for the company, which has reduced its workforce by 8% and reigned in spending.
And in the most recent quarterly results, Etsy outlined its tech priorities:
This is Etsy signaling to investors -- and to shoppers -- that it's going to be harnessing the machine-learning advantages that come with Google Cloud and using them to enhance its two primary revenue streams (sales and seller services).
The remainder of 2018 will likely see the company continue to highlight how it's able to boost sales thanks to its new big data focus.
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John Mackey, CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool’s board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. Lisa Schmeiser has no position in any of the stocks mentioned. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), and Amazon. The Motley Fool recommends Etsy. The Motley Fool has a disclosure policy.