Data by Design: Letting the Customer Decide What’s In Fashion

Fashion matters — from the clothes you wear to the mug you drink your coffee from. We live in a world where items are considered in style based on the latest trends being promoted by fashion influencers, and those trends don’t last long.

For brands and retailers, understanding their existing and target consumers helps to define and deliver winning products and experiences. The good news is that there’s a lot of data in the digital world — and it has a massive amount of value. The problem isn’t the lack of data, in fact, but instead it’s that we have too much, coming at us too fast and in too many different forms, and we need to understand how best to collect, collate and use these insights.

Major brands and retailers are turning to big data to revolutionize the way they understand and produce products, from apparel and footwear to luxury items and accessories. Increasingly connected and technology savvy, today’s consumer can make and break trends at incredible speed. From initial concepts through the product design and manufacturing process all the way to the consumer, real-time end-to-end collaboration is critical in order to deliver products people will value. To achieve this, it’s essential to collect the wealth of consumer data available and make sense of patterns in order to make the data actionable.

Taking advantage of technology enablers

Big data certainly provides strategic value, yet without the tools to access and analyze it, brands risk a trial-and-error process that can hurt their credibility and sales. Big data is also increasingly unstructured – from Twitter feeds and Pinterest to consumer shopping behavior. And it’s not just what they buy, but what they abandon in online shopping carts — even what they look at but don’t select.

Brands and retailers need to use a modern solution that directly captures the voice of the consumer, collects information from both structured and unstructured sources, organizes it into meaningful relationships, and displays the results in visually intuitive dashboards. This process provides companies with an intuitive way to communicate consumer insights and “wants” directly to the design and product development teams that are trying to anticipate them.  Brands and retailers can also bring the consumer directly into the validation process with social “test marketing” by using online solutions to replace old-style focus groups with real-time feedback.

One example of a company that has leveraged big data is TopShop. During the 2015 London Fashion Week, the retailer partnered with Twitter to analyze real-time data on the social network. Through the use of hashtags on a billboard, TopShop connected with consumers to identify the trends that stood out the most as they happened. Following the show, TopShop knew exactly which products consumers would want to buy.  

Hearing the customer  

Consumers are communicating with brands and retailers all the time. They speak loudly with what they purchase but also with what they abandon in their shopping carts. And when they talk about your products, competitors’ products or hot trends online they are really trying to shape what’s next. Too few retailers are taking advantage of this social stream for social ideation and social innovation.   

Opportunities to let the customer influence purchase options go beyond the design stage as well. Retailers can offer consumers an extended product assortment without increasing inventory or compromising the quality of store displays by replacing physical stock with realistic, 3D models. The implementation of 3D visualization solutions allows retailers to offer a curated collection of products in store and on their websites that customers can configure-to-order or even customize. I’m sure many of us have tried this with different brands of athletic footwear such as NIKEiD, miadidas and New Balance’s NB1 options.

Configured options allow consumers to share with their friends and order for direct delivery, without the retailer needing to produce inventory in advance.  This really lets the consumer feel like part of the design process and allows brands and retailers to address a true “market of one,” while still ensuring that the options offered are aligned to the brand identity. Feedback on what consumers configure – even if they don’t ultimately buy – provides great insights as well.

Focus on the consumer buying experience

With customization becoming more important than ever before, retailers are getting fewer returns from mass merchandising and instead are starting to think about how to serve individual customers. Macy’s, for example, uses customer data to personalize the customer buying experience. By collecting data ranging from sales to visit frequency to style preference, the company offers incentives at the point of sale with loyalty rewards and promotions. This data also enables it to send targeted direct mail to its customers to boost conversions.

Other retailers are using consumer navigation patterns and machine learning to improve the design of their website. Machines can aggregate information on how individual consumers browse, how long they look at an item, whether they navigate directly or hover over links trying to expose better information.  And from mouse clicks and mobile taps, machines can derive some insights on user preferences that allow the web designers to continuously improve the experience they deliver as well.  

Bringing big data to life

The value that big data brings to the retail industry has yet to be fully embraced. However, companies are gradually recognizing the opportunities that big data and other technologies bring to improving the way they design for and interact with their customers. As retailers continue to adopt these solutions, we continue to come closer to a world where the product and the customer experience are one.

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