Trying on Fast Data in Retail: How to Find the Perfect Fit

The retail industry has been quick to embrace Big Data. For years, Etsy has been looking at data and using it to help sellers become more successful while also optimizing shopping experiences. More recently, however, fashion houses and retailers of all sizes are taking a step further and taking on a Fast Data approach to their business. By analyzing their collected data in real time to deliver better and faster service, these businesses are able to tailor the shopping experience for each user and identify new fashion trends based on what’s most popular at the moment. Here’s a look at how Fast Data is impacting the retail space and driving results now.

The Backend Story

EDITD (pronounced edited) provides chain stores, retailers, and suppliers with real-time information that allows them to have the right products at the right price and the right time. If a retailer is stuck with a large inventory and is forced to put the product on sale, there is a disconnect between supply and demand—a retailer’s nightmare. How can retailers avoid this situation and beat their competition? The answer is Fast Data. EDITD, for example, analyzes 53 billion data points covering scores of retailers worldwide. Analyzing this data on the spot helps retailers anticipate demand and competition—once they understand it, then they can act on it by changing price points in real time to optimize inventory. A Fast Data approach eliminates the arbitrage of “comparative shopping” and makes the market more efficient.

An example: let’s say skinny jeans are in full stock at Molly the Merchandiser’s store, but through real-time analytics she can see that similar products at competing stores are falling in popularity. She is also notified that ‘70s-style fashion will be in vogue in the coming spring. With all of this information, Molly can instantly review her strategy regarding pricing and demand for her current stock of skinny jeans. She can then offer customers a more competitive price or promotion on skinny jeans and can begin to create inventory of bell-bottomed jeans for spring. In this scenario, Molly will more efficiently sell her remaining inventory of skinny jeans and ensure she’s stocked with the merchandise her ever-changing customers are now demanding.

With this Fast Data approach, she’s on top of the latest trends, ensuring she’s not stocked with dead merchandise, and can keep her store’s prices competitive. The store wins and the customer wins, all thanks to a Fast Data approach to retail.

Window Mirror Shopping

At the storefront side of the equation, Fast Data is incentivizing more customers to come inside and leave with a full bag of merchandise. While many retailers are turning their focus to the online retail space, brick-and-mortars aren’t dead. According to IDC Research, retailers will spend $100 billion this year on technology that will encourage more shopping, will engage with customers and will bring more shoppers to both online and brick-and-mortar stores.

The power of these technologies and the data they collect lies in how retailers proactively analyze the data. Look at the recent partnership between eBay and fashion brand Rebecca Minkoff. Together, they have created the first “connected store,” one ripe with new data-rich features such as mirrors that double as touch-screens that track which clothes you purchase, which you pass up, and which items you’ll potentially come back for at a later date.

Upon walking into the store, a customer uses her mobile phone to get notified when her fitting room is available. Once inside, she’ll use the mirror to choose another size if one of the items is too large or to choose another color, which the store attendant will bring to her. She can request the mirror to suggest trousers or a scarf to match her blouse. Upon choosing her items, the store will use expected buying behavior to offer her a promotion on an accessory to match her outfit, perhaps a necklace she brought into the fitting room. The next time she visits the store, she’ll get a promotion to update her wardrobe, perhaps with a jacket or pair of heels to match her outfit. While the online retail process has completely changed how consumers shop, its technological advances have trickled down into the old-school physical stores, where, surprisingly, the vast majority of purchases are still being made. And due to the ability to physically interact with customers, retailers have a unique opportunity in their stores to take advantage of Fast Data and real-time analytics.

Online or in-store, retailers are beginning to see the immense value in taking a Fast Data approach to their business. A multi-channel integration of real-time analytics boosts bottom lines for retailers and enhances the shopping experience for the customer. The result: a stronger relationship between both.