Addressing Challenges with Retail Assortment Management

Addressing Challenges with Retail Assortment Management

Retail Tech Insights | Thursday, January 04, 2024

Technology integration is transforming the landscape of retail assortment planning for CPG companies and retailers.

FREMONT, CA: The landscape for consumer packaged goods (CPG) companies and retailers has been marked by significant volatility in recent years. These businesses have faced numerous challenges, from grappling with supply chain disruptions to surging inflation and unpredictable market conditions. Amidst this uncertainty, there are opportunities for growth and profitability.

Despite the impact of inflation on customer purchasing power, consumer spending remains robust. Technological advancements have transformed consumer behavior, making them more demanding than ever. Consumers now expect the best products at competitive prices, delivered conveniently. This shift in consumer expectations underscores the need for CPG companies and retailers to adapt and evolve.

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One critical aspect of meeting these demands is accurate demand forecasting. Traditional forecasting methods and reliance on past performance analysis are inadequate in a rapidly changing market. AI-driven forecasting engines, backed by a wealth of data sources, including macroeconomic factors like inflation rates and consumer confidence, provide a more accurate picture of demand. These advanced models can adapt to changing trends quickly, which is crucial in a fast-evolving industry.

Store clustering plays a pivotal role in retail assortment planning. Retailers can create clusters that reflect evolving demographics and preferences by assessing historical sales, store size, gross margins, and more. Traditional tools like spreadsheets are ill-suited to this task, whereas AI-based clustering tools utilize sophisticated algorithms to select optimal variables and evaluate multiple algorithms for the best results. This flexibility empowers retailers to customize their clustering approach, ensuring the validity of their results.

Regarding assortment planning, sizing is critical, especially in the fashion industry. Ensuring the availability of products in the right size is essential to providing a positive customer experience. AI-based tools simplify the process of identifying size ranges and building optimal size curves for planning, helping retailers avoid the frustration of customers not finding their preferred size.

Operating a network of stores across various regions and countries presents additional complexities. Store size, shelf space, and local consumer preferences all vary, impacting product performance. AI-driven analytics help retailers find the right mix of products and store attributes to categorize stores effectively. These tools also consider the interdependencies between complementary products often purchased together, optimizing not just shelf space but also the customer experience.

In contrast to time-consuming, error-prone traditional methods, modern retail assortment planning powered by AI is an iterative, data-driven process that adapts to changing market dynamics. AI tools empower retailers and suppliers to continuously refine their assortment plans. By running thousands of simulations, they can identify adjustments likely to affect forecasts and evaluate the impact on sales, margins, and other factors. This level of optimization is simply unattainable using traditional methods.

With these advancements, they are able to not only meet but also exceed consumer expectations. Retailers can offer a better shopping experience, drive sales, and boost profitability in an ever-evolving market by accurately forecasting demand, optimizing store clustering, considering sizing, and accounting for interdependencies between products.

 

 

 

 

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