The biggest trends in retail, like rainstorms, can be fairly easy to predict. You look at the current conditions on the radar screen, consider their proximity and can pretty much nail where and when the rain will fall.
This goes for retail events as well as the weather. Consumers increasingly use their mobile devices in the shopping process. They expect more personalized, relevant shopping experiences. They research online and purchase in-store. These practices and preferences have been steadily advancing, so it is easy to predict and prepare for the continuing trends.
However, there are some trends that might not get the press coverage they deserve. In this article, we will uncover these important, emerging patterns, technologies, and preferences of the future:
Men Outspending Women
We will continue to see men take the lead in spending. Already, for the first time ever, men are outspending women by 13% and early indicators predict that the menswear market will expand 8.3% next year. That’s 1.5 times more than women’s. Expect more struggling retailers to bring menswear front and center.
The savviest retailers are taking advantage of advancements in machine learning, deep analytics and artificial intelligence (AI) for a more targeted and personalized shopping experience. Customers now have longer digital footprints (shopping histories, social media profiles and interests), giving retailers easy access to offer a tailored selection of products. Brands such as The North Face and 1-800-Flowers.Com are already using AI to provide personalized recommendations.
Major brands and retailers continue to struggle with big box stores, but succeed with small footprint devices such as custom vending machines. Calling them “vending machines” really does not do them justice, as many models are technologically advanced, with features that include touchscreen consumer interfaces, credit card payment systems, integration with social media, smart phone apps (order and pay from your phone), and remote management so owners can see inventory from any computer. Companies like Alps Innovations (www.alpskiosks.com), is a custom kiosk manufacturer. One of their customers, Chatty Cupcakes, is using an advanced, custom automated retailing system as their only “store” location. This significantly reduces overhead costs over a traditional brick and mortar store.
New “automated” stores are popping up around the country, selling everything from batteries to books, fresh salads to frozen foods, all of which make shopping more convenient and quicker for the consumer, and inexpensive for the retailer or brand owner to deploy.
We will see more brands actively engaging in crowdsourced products. Digital and social media have provided countless opportunities to engage with so many people at once about subjects, products and ingredients that are interesting or culturally significant. This has helped to level the playing field by democratizing access to people so now any brand, regardless of marketing or research budget, can effectively and efficiently have direct and real dialogue with its communities on a broad scale.
More retailers will apply data to every part of the retail process, from the supply chain all the way to the post-purchase stage of the buyer’s journey.
Retailers who make data-backed decisions will outperform those who don’t. More and more merchants will recognize this — which is why we think companies will double-down on data collection and analysis.
JustFab is one example of a company that puts its customer data to good use. The fashion retailer uses style quizzes to learn more about its members and then makes recommendations based on each member’s preferences. JustFab also closely tracks the products each member browses, rejects, and buys — and then uses data to curate selections for each member.
Using data to personalize customer experiences is just the beginning. Data analysis also plays a major role behind the scenes, especially when it comes to inventory management and merchandising. Retailers rely on data to forecast demand and to make important stock-control decisions.
Have a look at what clothing company Patagonia is doing. Patagonia factors in current trends and historical data (among other things) to figure out which products to purchase and distribute in its stores. In doing so, the retailer’s able to accurately predict demand, keep stores stocked with the right merchandise, and minimize waste throughout the supply chain.