Special Feature
Part of a ZDNet Special Feature: Turning Big Data into Business Insights

How Wayfair used big data and omnichannel retail to transform shopping

Online home goods retailer Wayfair developed visual search capabilities to leverage big data and improve the customer experience. Here's how.

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Image: Wayfair

No longer just a techie buzzword, big data is transforming the retail sector to improve customer experiences and increase profits.

"Today, we are seeing many retailers begin to pivot from exploratory technology pilots and experiments in big data to making permanent investments and changes to organizational structures and capabilities," said Rob Holston, leader of the Global Consumer Products and Retail Data and Analytics group at EY Consulting. Retailers are also leveraging data and analytics to optimize the consumer experience, which can drive over 60 percent improvement in profitability, he added.

"Increasingly, the customer experience is the brand versus the product, and companies have been making changes to their business model and adding new capabilities to create a differentiated experience," Holston said. "Data and analytics are central capabilities to defining, unlocking, and sustaining value through differentiated customer experiences. Retailers know that data and analytics is an investment in relevance and survival."

Home goods e-commerce company Wayfair was born in the digital ecosystem in 2002, and its roots have always sat deep in the world of big data, according to Matt Zisow, Wayfair's director of product. The team embraces big data in both philosophy and practice, Zisow said, using it to improve the customer experience, optimize the company's web presence, source products, and make business decisions.

SEE: Big data policy (Tech Pro Research)

"As a company, we know that data democracy is critical to our success," Zisow said. "We don't want to limit the power of big data to insights that just a few people have access to. Whether you're in marketing, logistics or engineering, the ability to see and manipulate data is what keeps our organization moving forward and continuously innovating."

Decision making using big data must be weighed with one goal in mind: Improving the customer experience. To achieve this, Wayfair tapped big data in its Search with Photo feature, unveiled in May, in which customers can snap a picture of an item they like in a store or someone's home, and use that image to search for visually similar items in Wayfair's product catalogue.

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"We knew that everyone has a unique vision for their home and ideas and inspiration can come from anywhere. A sofa in a friend's house, a Pinterest board, a barstool at a favourite restaurant, or a pillow featured in a design magazine, can all spark ideas for decorating one's home," said Steve Conine, Wayfair co-founder and co-chairman. "And while finding a look you love may be easy, finding the specific products to bring that look to life can be time-consuming and require a lot of searching. With visual search, shoppers can now search for and find a particular product or style instantly."

Search with Photo taps Wayfair's computer vision system, which the company built in-house using deep learning techniques and its massive proprietary data sets. The data collected from this visual search feature creates a powerful feedback loop, which makes Wayfair's results more useful for customers, Zisow said.

"We're not just using data to make those matches across our data set: we're measuring whether someone stays on-site after submitting a visual search query, whether they buy an item and when they return to shop at Wayfair again," Zisow said. "Not only do we use data to find answers, we use it to find new questions that we hadn't even thought of asking as well. By continuously analyzing the entire feedback loop, we use data to keep working toward that goal of improving the customer experience in ways that are significant and measurable."

SEE: Microsoft Power BI: Getting started with data visualization (free PDF) (TechRepublic)

Wayfair measures the impact of offerings such as Search with Photo in part by measuring loyal repeat customers. In the second quarter of 2017, orders per customer and repeat customers both increased year-over-year. Repeat customers placed more than 61 percent of total orders in the second quarter of 2017, compared to about 58 percent in the second quarter of 2016. And repeat customers placed 2.6 million orders in the second quarter of 2017, an increase of 55 percent year-over-year.

"When we see more customers returning, we find that to be an indication that we're making the right decisions when it comes to the customer experience," Zisow said.

Search with Photo reduces friction between a customer seeing a product they love and getting it to their home. Other companies can identify areas where there may be friction, and use big data to smooth them out to find success, Zisow said.

"Big data isn't just a buzzword or a passing fad; it is a fundamental, increasingly 'table stakes' capability for companies in all sectors," Zisow said. "If you're not actively investing in your company's ability to gather and harness your data in ways that matter to your customers, you're almost certainly falling behind your competition, even if you don't know it."

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