Retailers around the globe know that ordering the right mix of sizes is a critical component to a profitable organization and directly affects a customer’s ongoing loyalty. A customer who enters your store with the intent to buy and leaves empty-handed because you did not have his or her size stocked is not only a lost sale, but a potential lost customer. The same is true for a customer shopping on your e-commerce site who is unable to “add to cart” due to a particular size being unavailable.
While technologies that enable “endless aisle” and ship-from-store fulfillment are helping retailers to save the sale and deliver a better brand experience, the first and most profitable line of defense is to get sizes right in the first place – something that is easier said than done.
The majority of retailers today will attest to the sheer complexity of sizing. In a recent Apparel webinar we tackled this topic head on. I was joined by Debbie McCarthy, VP of Merchandise Systems Support at Destination XL and Greg Girard, Program Director, Merchandise Strategies at IDC.
During the webinar – now available on demand – we discussed several sizing challenges including inconsistencies in sizing, the sheer volume of data that must be analyzed to create size curves, and other inherent challenges in creating size curves that align to local demand.
What we looked to address during the webinar – and what many of you are working to address at your organizations is the answer to the question: How does a merchant capture true size demand to more accurately buy and allocate product?
During the webinar, we introduced two new analytic tools that can examine massive amounts of data, and convert that data into actionable intelligence, while capturing true demand to help retailers tackle the size curve and corresponding pre-packs.
Localized Demand that’s a Perfect Fit: The Aptos Size Curve Solution
Aptos’ best-in-class Size Curve application performs advanced size analytics to drive increase business, help create the best size curve locally, and increase efficiencies within the size analytics. With the Aptos solution retailers can more accurately capture demand to:
- Increase sales, gross margins and GMROI by size and inventory turn velocity
- Decrease inventory levels, stockouts and lost sales
- Increase customer service levels and enhance shopper loyalty
The Aptos Size Curve application thoroughly processes and cleans historical data, performs size analytics based on true customer demand, and optimizes the product mix to best meet customers’ needs. As well, the application offers an outlier detection process that gets rid of anomalies across stores.
Data Drives Downstream Optimization: The Aptos Size Pack Recommender
Once a retailer has an optimal localized size curve, the next critical step is to extend that data to the downstream system and begin building “eaches” or pre-packs, optimized for each retail store.
Some retailers choose to build pre-packs based on the following factors:
- Better efficiency in the supply chain of products to stores
- Less manual handling of the product
- More cost savings vs. buying “eaches” or single pieces of inventory
- Simplify the allocation of products
Most retail organizations typically use the size curve data to efficiently decide how to buy a pack and in what quantities. For example, is it better to buy pre-packs in quantities of 6, 12 or 18? For many retailers the question then becomes “how do I accurately calculate which pack to buy and why?”
The Size Pack Recommender application from Aptos allows retailers to create the optimal packs for their orders based on purchasing and allocation cycles in order to properly deliver to the stores a vast assortment of styles, colors and, of course, sizes. This ultimately minimizes the number of items a retailer has to sell at markdown prices while maximizing sales within regular price products. The tool makes it easier to derive optimal pre-packs locally, a decision that might otherwise be left to the vendor based on what has always been done historically. The Size Pack Recommender application allows pre-packs to be based on the customers’ needs.
Size Curves and Size Packs: Set Yourself Up for Customer Satisfaction
Better size curves and size packs – seemingly small decisions when compared to “larger” and more consumer-facing IT investments – can have an enormous impact on a retailer’s bottom line as well as other ripple effects throughout the retail organization. The failure to address localized sizing demand can have retailers run the risk of not seeing the true demand, ultimately ordering the wrong packs for the wrong stores and never being able to catch up from months and seasons of overstocks and markdowns.
The best response when a customer asks, “Do you have my size?” will always be YES. Set your retail organization up for success to ensure that customers’ sizes are available by putting the power of analytics to work for your business – and your shoppers!