Data is good but insights are better. Precise new analytics tools on the market are finding willing customers in apparel clients looking for ways to win in retail in this day and age.
Fashion companies today face myriad pressures compelling them to seek a competitive edge with analytics. Speed to market is perhaps the top factor influencing decisions to invest in analytics, said Elizabeth Shobert, CMO for StyleSage, an analytics platform designed for the needs of apparel brands and retailers.
“I think the biggest thing that leads apparel retailers to analytics is the recognition of the speed at which the market is moving—consumers’ changing preferences, new market entrants/increasing competition, and how and where trends emerge,” she explained. “Some are trying to get ahead of these changes, and others find themselves falling behind. Either way, they realize that in order to be more responsive, they need the data that can help them move more quickly and efficiently.”
Andrea Morgan-Vandome, CMO for inventory analytics firm Celect, echoed the pressure that new competitors with new business models like rentals and subscriptions put on entrenched apparel firms. “Most of the new entrants are incredibly driven by data insights so fashion retailers need to take on the same approach in order to stay relevant,” she added.
Besides speed and the digitally native challengers springing up everywhere, Morgan-Vandome cited demanding consumers—and their changing expectations—as another thorn in fashion’s side. “They expect to be able to shop 24/7 anywhere, receive the merchandise anywhere quickly and return anywhere,” she explained. “This makes it harder for retailers to manage the inventory so they need solutions to help them.”
Apparel sellers can leverage analytics in many places within their business but Celect, used by companies like Lucky Brand, finds that they often want to start with a focus on optimizing inventory. “Retailers are looking to optimize the use of inventory—they are going beyond what and how much, to also consider where to place the inventory and where to fulfill online orders from,” Morgan-Vandome noted.
Many clients are very “tactical initially” with what they hope to get out of a new analytics deployment, said Karin Bursa, EVP of marketing for supply chain and retail analytics firm Logility.
At StyleSage, many clients are looking for a more scalable and streamlined process for collecting external, competitive data, Shobert noted. “A key element of this is an acknowledgement that having an external, not just internal point-of-view is important,” she continued. “You’d be surprised to know that many fashion organizations still are largely internally focused.”
Some organizations task employees with checking retailers’ websites, ask them to subscribe to and monitor competitors’ newsletters, and dispatch workers to conduct store visits. “But they quickly realize that is not a very efficient process, at which point they’ll come to us,” Shobert said.
As with any technology initiative, fashion companies want to see results and a return on their investment sooner rather than later. With their focus on inventory, apparel clients that work with Celect want to optimize allocation and enhance fulfillment operations to support e-commerce order fulfillment from stores.
“Retailers ready to take advantage of the AI-driven inventory optimization Celect provides are looking for more than incremental wins—they want margin improvements, reduced out of stocks, reduced markdowns and increased full-price sell through,” Morgan-Vandome explained.
Companies often unlock unexpected insights after deploying analytics within the business. Hunkemöller, a European lingerie retailer that’s focused on expansion into Asia, began working with Logility in the fourth quarter of 2017 and has since shifted from shipping standardized pre-packs to its store fleet to tailoring those assortments to local geographies, Bursa noted. The brand realized that women in Spain and the Netherlands are more likely to sport surgically enhanced bustlines, widening the variety of the band-to-cup sizes they require.
After deploying Logility analytics, Hunkemöller gained a “more precise indication” of the sizes selling at the store level, Bursa added. At the outset they were looking for faster product distribution and somehow stumbled into even more valuable insights.
StyleSage customers, on the other hand, have their gaze on profits and margins. “Where our clients see the quickest ROI is when they are able to make in-market, real-time decisions around discounting and pricing,” Shobert said. Most want to get away from offering discounts too early in the markdown cadence or to eliminate discounts that are unnecessary because they were informed by historical data versus “what’s actually happening in the competitive market,” she added.
“This way they’re able to preserve margins and sell more products at full price,” Shobert continued. “In addition to that, they’re able to be more responsive to trends in the market with real-time intel in what their competitors are bringing to market.”
Before they incorporate analytics into their business, there are a few steps a brand or retailer should take for maximum effect and outcome. According to Morgan-Vandome, apparel clients are wise to prioritize the problem they want to solve and “encourage a culture of trial” to do so.
“AI often recommends insights that are not obvious but will drive significant value if executed,” she continued. For example, a customer that had never sold cold-weather puffer vests in hot and humid Florida found that the garment became a best-seller there after Celect’s AI solutions recommended offering the product in the southern state, Morgan-Vandome noted.
Shobert agreed that apparel firms should be clear about their pain points and how to address them. “Are you trying to get products to market faster, make sure all your merchandising and planning teams are on the same page, price more competitively, or avoid unnecessary markdowns? Cross-organizational alignment and clarity on this is really important,” she explained.
What’s more, identifying the workflows and decisions this data will flow into is equally important, Shobert noted. “A critical part of our process at StyleSage is making sure there’s a key team in place that represents different areas of the business, so that they are all on the same page, sharing information, and ultimately maximizing their ROI,” she added. “Spending the time up front to get clarity on these things ensures that analytics gets truly embedded in the decision-making processes of the organization.”
Apparel retailers should get their data house in order before trying to force an analytics platform to work, according to Bursa. “The biggest challenge for any business is tapping into the data and getting the insights,” she said, adding that companies can leverage machine learning tools to identify the data that’s meaningful to drive those insights.
Though retailers can develop in-house analytics, they stand to benefit from working with an experienced third-party vendor. For one, apparel clients quickly discover that building a proprietary platform that effectively captures all the right data points is seriously complicated. “In fashion, for example, there are so many item-level details (we call them attributes) that impact customer decisions,” Shobert explained, “and those details will also vary a lot by the category you’re looking at.
“Our goal is to help businesses do what they do the best they possibly can by freeing up their resources to really focus on that strategic business of creating great product,” she added.
Today many apparel companies are interested in gaining an “external lens and point-of-view on their business,” Shobert concluded. “Working with a third-party vendor not only provides deep industry expertise, but it also injects a much-needed external perspective that can help optimize an organizations’ existing process.”