Use E-Commerce Data to Boost In-Store Sales as Retail Reopens
Best-selling or trending products are often displayed on a retailer’s homepage. It’s time for retailers to take e-commerce sales data and improve in-store visual merchandising. After all, aren’t window displays essentially a retailer’s homepage come to life? Since the COVID-19 pandemic struck, apparel brands have seen casual and athleisure sales soar. Savvy apparel brands with brick-and-mortar locations will act on this data to increase in-store conversions.
In short, analyzing and testing omnichannel data can help retailers bounce back stronger.
Pandemic Shopping Looks Different
Recently, PepsiCo’s chief marketing officer held nothing back when he said launching the company’s two direct-to-consumer websites was done to collect customer data. With screen time increasing by more than 50 percent during quarantine and e-commerce sales jumping by 49 percent in April, brands acquired significant amounts of data that can be utilized to increase in-store sales and enhance shopping experiences. Online brands that own data own the future of their sales and are able to make faster decisions that impact multiple revenue channels.
As stores reopen with limited capacities and socially distanced lines, retailers must capture every customer they can when shoppers enter their doors.
Bridging the Online-to-Offline Merchandising Gap
When visual merchandisers map out product placement, they usually go by gut feeling or follow a planogram. Planograms and strategic product placement would perform much better if they incorporated e-commerce data.
If the end goal of a store is to sell products, enhancing the positioning of products based in part on what online shoppers are buying (or not buying) is a wise move. And another bonus: it removes opinion or gut feel. A healthy reminder that data should determine decisions.
Online Product Categories Are Physical Aisles
At surefoot, we like to think of a brand’s website homepage, category pages, and even social media accounts as digital store windows. That's where retailers get real-time, rich insights into the imagery and products resonating with their customers. When retailers view their stores this way, it’s easier for them to see the benefit of adjusting in-store visual merchandising strategies. Even store layouts can be upgraded for better flow based on the shopping journeys of online customers.
One reason some department stores have suffered in recent years is due to a disconnect between in-store, supply chain, and e-commerce teams. For example, if online sales data indicates customers in a particular geographic area are buying a sunscreen brand that’s unavailable in their local store, that information must be communicated to regional teams and warehouses in order to stock in-demand products. Data sharing should go both ways. For example, in-store sales trends from different regions could trigger an e-commerce team to personalize online merchandising based on that regional data.
Got the Goods, How About the Data?
Today’s online shoppers are sharing data that brands like PepsiCo have wanted to get their hands on for years. Collecting Instagram usernames, favorite seasons or body types isn't only doable, it’s happening. Most retailers have databases where that information lives, such as customer relationship management (CRMs) platforms and customer data platforms (CDPs).
Companies that invest the time and resources into stitching their data together and using it cross-channel and cross-team will win at the digital and physical cash register.
Laura Stude is co-founder of surefoot, a boutique experimentation and personalization agency helping e-commerce brands and SaaS companies better understand customers and boost revenue through strategic experimentation programs.
Laura Stude is co-founder of surefoot, a boutique experimentation and personalization agency helping ecommerce brands and SaaS companies better understand customers and boost revenue through strategic experimentation programs.
Laura gives a damn about helping ecommerce brands grow. She cut her A/B testing teeth as a developer and strategist for clients like Keurig, Adidas and Patagonia before packing her bags to run optimization at Hillary Clinton’s campaign in 2016.