SKU Assortment Optimization
Increase sales by putting the right products on every shelf across your business
Neal Analytics offers an open, integrated solution that provides machine learning insights through a scalable platform for advanced analytics.
Optimize your inventory and delight customers
Increase sales for your organization by stocking the right products on every shelf, ensuring high market penetration for all top performing SKUs, increasing the ease and frequency of the portfolio management process, and equipping your business leaders, analysts, and field operators with data-driven insights.
Identify the best products for each market
Receive personalized product assortment recommendations for each outlet by with our SKU Optimization models. Our solution is capable of processing millions of SKUs and buyers by segmenting sales data into peer groups for fair and detailed comparisons that also account factors like local preferences, demographics, and purchasing habits.
This solution will help you identify the best products for each market segment. You’ll be able to compare similar segment portfolios, distribute SKUs to the locations they’ll perform best, and optimizing operations by cutting cannibal products.
Identify top and bottom performing SKUs across your sales channels to increase market penetration and replace underperforming SKUs with your “diamonds in the rough” products in need of wider distribution. This level of detail offers deeper insights so that you can dynamically tailor your inventory and keep up with customer demands.
A customized and integrated solution
Our solutions can be customized to fit your unique business needs – optimizing on the metrics important to your business (i.e. sales volume, product margin, returns/wastage, etc.).
SKU Optimization can also be integrated with additional data sources to provide demand forecasting, sales decomposition and other Neal Analytics solutions.
SKU Optimization requires a minimum of two years of historical transaction level sales data, a product description table (product names family/group, brand, package size, etc.) and a customer description table (customer name, location, trade channel, etc.). Additional datasets may be required based on customization options.