Merchandising manager interview questions and expert answers

Answer example: I run monthly category diagnostics across sell-through, mix, AUR, and full-price rate, then rebalance depth into top-decile performers while pruning low-velocity styles. I protect pricing integrity and favor private, client-first activations over public promos. In handbags, trimming entry-price over-assortment and reallocating into signature silhouettes improved margin +4 pts and sales +10% without discounting.

Answer example: I analyze each location by sales volume, customer profile, space constraints, and market characteristics. I allocate inventory to maximize overall productivity while ensuring each location has appropriate assortment for its customers. I consider both quantitative factors like historical sales and qualitative factors like local preferences. I also maintain flexibility to reallocate based on performance. I use systems to automate routine decisions while applying judgment to strategic items. When optimizing allocation, I created a tiered approach based on store profiles, improved allocation algorithms using sales velocity data, and established clear transfer protocols. This reduced stock-outs in high-performers by 30% while improving overall inventory turn.

Answer example: I approach markdowns strategically, viewing them as inventory management tools rather than sales drivers. I analyze aged inventory to determine optimal timing and depth of reductions. I implement markdowns in ways that minimize brand impact: private sales for clients rather than public promotions, transfers to outlet channels when appropriate, or donations for tax benefit. I also work with buying to prevent future overstock through better planning. When faced with excess seasonal inventory, I organized exclusive client events offering early access at modest reductions, transferred slower items to locations where they had better sell-through, and took strategic markdowns on remaining aged stock. This cleared inventory while maintaining brand prestige.

Answer example: I map sales by attribute cluster and price band to spot cannibalization and gaps. I shrink the long tail, deepen proven winners, and fill white space where clients signal unmet needs. In accessories, cutting overlapping styles 20% and adding two missing price ladders increased sales productivity while improving perceived choice.

Answer example: I work closely with VM to ensure product is presented in ways that tell compelling stories and drive sales. I share insights on what products deserve prominence based on performance and margin. I also provide feedback on what presentation approaches are working from a sales perspective. I ensure VM has the inventory they need for impactful displays. I view this as a true partnership where commercial goals and aesthetic excellence must align. When launching a new collection, I collaborated with VM on floor sets that highlighted key hero pieces, ensured adequate depth in featured styles, analyzed early sales response by location, and refined the presentation approach. This collaboration resulted in 25% higher attachment rates for complementary products.

Answer example: I set category stock-to-sales targets, concentrate depth on signatures, and cap exposure on novelty. Exception reports trigger actions on underperformers by week 4. This improved inventory turn 20% while keeping in-stock above 90% on key items.

Answer example: I approach pricing strategically, considering brand positioning, competitive landscape, cost structure, and customer value perception. I analyze price elasticity to identify opportunities where we can adjust pricing without affecting demand. I also ensure our pricing architecture creates logical ladders that guide customers through the assortment. I protect pricing integrity by avoiding discounting that trains customers to wait for sales. When reviewing our pricing strategy, I identified several styles where we had room to increase price based on quality, exclusivity, and customer willingness to pay. I implemented strategic price increases averaging 8% on selected items, which improved margin with no impact on sell-through because pricing still reflected appropriate value.

Answer example: I use historical sales data as a foundation but adjust for trend shifts, market changes, and brand initiatives. I monitor early indicators like pre-order response, website engagement, and sell-through of similar items. I also stay connected to market intelligence from stores, competitors, and industry sources. I build flexibility into plans so we can react to stronger or weaker than expected demand. I forecast conservatively for unproven items while betting bigger on proven performers. When forecasting a new category launch, I analyzed analogous category performance, tested customer interest through previews, started with conservative initial buys with reorder capability, and monitored early sales daily to adjust quickly. This approach achieved strong sell-through while avoiding significant overstock.

Answer example: I diagnose with a waterfall: mix vs plan, price architecture, depth vs velocity, and regional skew. Actions span assortment refocus, pricing, inventory cleanup, and VM/storytelling. In one category down 15%, these moves restored growth within two seasons.

Answer example: I believe luxury requires both sufficient choice to feel curated and edited, and appropriate depth in key items to ensure availability. I concentrate depth in proven bestsellers and brand signatures while offering breadth to provide discovery and newness. I also consider that some categories benefit from breadth, while others need depth. I use sales data to guide these decisions while respecting brand and customer expectations. When optimizing our core category, I identified that we had too many marginal styles with insufficient depth in winners. I worked with buying to rationalize the assortment by 20%, reallocating inventory dollars into deeper positions on bestsellers. This improved in-stock rates, reduced complexity, and actually increased sales through better availability of what customers wanted.