Zainab Hussain is not just an observer of the retail industry; she is an architect of the modern shopping experience. As an e-commerce strategist with years of hands-on experience in customer engagement and operations, Zainab has seen the industry move from rigid, store-centric models to the fluid, boundary-less world we navigate today. Her expertise lies in bridging the gap between digital convenience and physical presence, ensuring that retailers don’t just survive the shift but thrive within it. Today, she joins us to discuss why the old “siloed” approach to inventory is a relic of the past and how a unified view of stock is the secret to protecting margins in a highly competitive market.
We delve into the evolution of demand, exploring how the path from browsing to buying has become a seamless loop across channels. We’ll discuss the release valve effect of omnichannel fulfillment, the critical shift from calendar-based markdowns to data-driven pricing, and how AI-powered allocation is preventing the inventory gluts that used to plague retail backrooms.
Shoppers are increasingly researching products online and visiting stores to try them on, only to complete the purchase digitally later; how does this fluid behavior redefine our understanding of demand?
This shift in behavior has completely upended the traditional definition of a successful store. In the past, if a sweater sat on a shelf for three weeks without a sale, we would label it a failure and start eyeing the markdown stickers. But in today’s world, that same sweater might have been tried on by fifty different people who loved the fit but preferred a different color available only online, or perhaps they simply wanted it delivered to their doorstep the next morning. The demand is still there; it just isn’t showing up in the local cash register. We have to stop looking at store inventory as being trapped within four walls and start seeing it as a flexible asset for the entire network. When we recognize that a product in a quiet suburban store is actually a vital fulfillment unit for a digital order across the country, we stop guessing and start knowing where our value truly lies.
You’ve mentioned the concept of online demand acting as a “release valve” for physical store inventory. Could you explain how that mechanism actually protects a retailer’s bottom line?
For years, moving excess inventory between locations was a logistical nightmare that rarely justified the cost, so items were often marked down locally just to get them out the door. Now, omnichannel fulfillment acts as a release valve by allowing that local stock to satisfy digital orders from anywhere, which takes the immediate pressure off the store to slash prices. When a retailer has visibility into how often online orders are filled from specific stores, they can see the real trends of the business rather than just a flat sales report. It’s an incredibly satisfying feeling for a manager to see a shelf clear out at full price because those units were shipped to customers in a different market where the item is trending. This flexibility allows planners to hold their ground on pricing, avoiding the unnecessary discounts that the data simply doesn’t support if you look at the bigger picture.
How does having a single, connected pool of inventory change the way a company approaches the traditional end-of-season markdown cycle?
The old way of pricing was essentially following a rigid calendar—once you hit a certain date, everything dropped by twenty percent, then forty, and so on. We are moving away from that “peanut butter spreading” approach where every store gets the same discount regardless of local needs. With a unified system like Zebra Workcloud Lifecycle Pricing, we can be much more surgical, looking at specific sell-through goals like hitting 70% before the first markdown and then pushing for 80% to clear the floor. If a cold snap suddenly extends the demand for heavy coats, or if a specific color becomes a viral sensation online, the data tells us to hold the price even if the calendar says it’s time for clearance. By catching these shifts early, we can promote items when they still have momentum, which means we take far less pain at the back end of the season when margins are most vulnerable.
What role does AI-driven allocation play in ensuring that retailers aren’t forced into aggressive pricing actions in the first place?
Allocation is really where the battle for margin is won or lost at the very start of the season. Traditional allocation often relied on broad rules, like sending full-size runs to every location, which ignores the fact that products are bought by individual people with unique local tastes. By using AI, we can account for the fulfillment strategy of each specific shop—some might be designated as regional hubs staffed specifically for high-volume ship-from-store tasks, while others are boutique showrooms. When we get the right product to the right spot from day one, we significantly reduce the buildup of “stuck” inventory that eventually requires a deep markdown. The goal is to make more frequent, smaller decisions that reflect real-time demand, rather than one giant, imprecise guess that leaves money on the table.
What is your forecast for the future of retail inventory management?
I believe we are entering an era where the distinction between “online stock” and “store stock” will disappear entirely from the corporate vocabulary. In the coming years, the most successful retailers will be those who can pivot their entire inventory in real-time, responding to a trend on social media or a shift in the weather within hours rather than weeks. We will see a massive move toward hyper-local allocation, where AI predicts not just what will sell, but which store is the most cost-effective “hub” for a specific customer cluster. Ultimately, the retailers who treat their inventory as one living, breathing pool will be the ones who maintain the highest margins and the happiest customers, because they will always have the right product available, regardless of where the shopper decides to click “buy.”
