1. Retailers who rely solely on internal and historical data are limiting their growth potential.
  2. Retailers need the right tools to identify profitable products and react quickly to capitalize on them.
  3. AI-powered analytics is becoming essential for assortment optimization in the retail industry.
  4. Retail assortment optimization applications (RAOA) and retail assortment management applications (RAMA) provide powerful planning and inventory management capabilities.
  5. Leveraging data at every stage of the retail lifecycle is key to creating and maintaining high-performing assortments.



Introduction: The Challenge of Assortment Optimization

Increased market share is a key performance indicator for most retailers, but basing your next assortment structure only on internal and historical data from inside your business is restricting your growth. You can see top performers and worst performers, but without easy access to the most profitable or greatest potential products in your business, you are unable to maximize opportunities for assortment optimization. 

This is the challenge that many retailers face. Spotting trends as they’re developing, finding the most profitable products or categories and reacting quick enough to capitalize on them commercially. Optimized supply chains mean retailers can get top- performing products in front of customers quicker than ever. But as trends become transeasonal and product drops more frequently, knowing which products to push in your assortment when looking across multiple categories, at hundreds of competitors and over several channels only becomes harder.
That’s where the power of assortment intelligence data lies. Manual comp shops can’t gather or process that volume and detail of information. Retailers need to be armed with the right tools to identify the right products, then plan, price and promote them effectively. The sheer quantity of new products combined with speed to market, means that AI-powered analytics is becoming essential to support retail growth.

Bringing AI-Driven Assortment Intelligence into Your Business

To solve the question of how best to find and use data to optimize your assortment, retailers are looking to integrate high quality, AI tools in their daily workflows more than ever before. According to Gartner, retail assortment optimization applications (RAOA) provide powerful planning and inventory management capabilities that can minimize excessive inventory and grow margins to enable dramatic improvement of cash flow. This helps retailers implement and manage winning assortments to satisfy consumer demand.

Retail assortment management applications (RAMA) also support business processes that are critical to fulfil customer needs through advanced assortment planning (Gartner). Whether it’s product ranging and replenishment planning or allocation support and optimizing open-to-buy, having a platform that helps you get the full picture both inside and outside of your business is a game changer for the retail industry.  

“Retail assortment management applications (RAMA) are foundational for modernizing merchandising processes as part of a digital business transformation strategy in unified commerce.” – Robert Hetu, Gartner Analyst

Leveraging Data at Every Stage of the Retail Lifecycle

However categorized, using a platform to leverage data and focus on a customer centric approach is key to creating and maintaining high-performing assortments and a positive merchandising experience. Wherever used in the retail lifecycle, this type of data can be integrated with workflows at any stage across pre-season, in season and end of season actions.

No matter the objective, data poses a solution. To offer the best assortment optimization in the market, you’ll need to compare your assortment to competitors at regional, brand, category, color and SKU level. To identify and potentialize outperforming categories, you’ll need to uncover the best performing categories in the market and understand how the best performing products are priced. To identify and monitor trends in the market, you’ll need to leverage market analysis and reporting, along with new in product tracking, SKU availability and sell-through data. 

Offering the right product, optimizing successful categories, identifying white space, and potentializing existing stock and the best price points all lead to improved planned sales, increased incremental sales, new revenue opportunities and reduced inventory levels.


The Perfect Mix: Assortment Planning and EDITED

So how can you achieve all of this and satisfy consumer demand using data? This is where retail transformation truly starts, and it starts with EDITED. In uncertain retail environments and with new challenges daily, the right information matters now more than ever. With multiple data sources available, teams can plan their assortments more effectively, optimize price points, time product launches effectively and quickly identify relevant trends to apply.

Basing your next assortment structure only on limited internal and historical data from inside your business is only half the story. By understanding shifts in your competitors’ assortment structures and sizes while being able to react in real-time so you can structure your assortment optimally is key to driving revenue and increasing market share. Get an efficient read on your business with daily trading insights, new arrivals performance and seasonal hindsighting. 

EDITED’s suite of planning tools gives your team unrivaled visibility: past, present, and future. You’ll instantly gain a 360-degree view of your own business and competitive marketplace. Learn which actions had the most significant impact on profits and understand why. Grow your market share by easily identifying under-penetrated and under-served categories across every market relevant to your brand. Determine the forecasted impact of actions taken on price, merchandising or inventory before they happen. No matter the objective, we have a solution. Leverage the data you need to create the perfect assortment. Get started here today.