Best Match Demand and Maximize Profit
Drive Value at the Most Granular Level
7thonline's proprietary optimization algorithms and services are at the forefront of optimization technology for the apparel, footwear, and accessories industries. We help you identify profit opportunities and advise optimization strategies at a granular level that is often difficult to achieve.
Your assortment needs to speak directly to the customers you are targeting. However, localizing assortments down to the door level can be a daunting task due to the volume and complexity of available data: historical and in-season sales and inventory, product attributes, financial objectives and local demand patterns are only examples of critical factors that need to be analyzed and considered.
Our Assortment Optimization solution and service can lend you a fresh pair of eyes going through all of your important product and location data to generate the optimal category, class, SKU breadth and depth down to door level. Through proprietary algorithms and deep domain knowledge, we help you identify sales opportunities and recommend the right assortments at your lowest planning level.
- Identify top selling styles and recommend the quantity needed to maximize margin contribution
- Identify and account for lost sales on styles with under-purchased units
- Identify and account for an under-purchased breadth of styles
- Consider the potential price erosion as more units are added to styles
- Determine the optimal balance of adding units to the top selling styles or adding additional styles
- Increased SKU productivity (identify and reduce under-performing products and invest more in top sellers)
- Increased full-price sell-thru and reduced markdowns and stock-outs
- Improved customer satisfaction and loyalty through localization of assortments
- Reduced administrative costs and errors
Every retailer loses a significant portion of sales and gross margin due to a mismatch between store size distribution and local demand. The amount of data and quantitative analysis involved in determining the optimal size allocation by style by store is prohibitive. Furthermore, the calculations of the size distribution are often oversimplified, not taking into account the price, revenue, and margin impact of missed opportunities, stockouts and overstocks in particular sizes. Without correcting for past mistakes, history is repeated rather than improved upon. These shortcomings in retail sizing result in lower profits and disappointed customers.
Retailers can avoid these unnecessary sales and margin losses with our size analytics and optimization services. Through historical POS analysis and proprietary optimization algorithms, we help determine the optimal size distribution by store that will minimize lost sales due to early size breaks without increasing inventory. For case pack styles, the algorithm determines the optimal size mix for each pre-pack and the optimal distribution of available pre-packs to each store.
- Account for missed sales potential from sizes that were out of stock early as well as margin losses from overstocked sizes that were sold at discounted prices
- Optimize size profiles and distribution by store for open stock
- Optimize pack size configurations and distribution of pre-packs to stores
- Automatically apply size profile to purchase order
- Clients can mirror the size profile of local demand at the style attribute and door level
- Reduced size breaks (up to 15 percentage points) and increased full price sell-thru (up to 14 percentage points) deliver higher revenue and gross margin contribution