Balancing act: Finding the optimal mix with assortment intelligence

assortment intelligence


  • Assortment intelligence involves understanding and optimizing the mix of products and services in retail, impacting sales, profitability, and customer satisfaction.
  • Retailers must balance factors like customer demand, profitability, competition, and seasonality to find the optimal mix of products and services.
  • Assortment intelligence in e-commerce involves using data analytics, category management, and assortment planning software to navigate decision-making complexities.
  • Amazon's use of assortment intelligence has made it a global e-commerce leader, increasing sales, profitability, and customer satisfaction.

Assortment intelligence is the ability to understand and optimize the mix of products and services offered to customers. It is a critical part of any successful retail business, as it can have a major impact on sales, profitability, and customer satisfaction.

Finding the optimal mix of products and services requires pitting one factor against another. In that way, it can be a balancing act. Retailers need to consider a wide range of factors, including:

  • Customer demand: What products and services are customers most likely to buy?
  • Profitability: Which products and services are the most profitable for the retailer?
  • Competition: What products and services are competitors offering?
  • Seasonality: Which products are in high demand at certain times of the year?

For e-commerce businesses, assortment intelligence is often a dynamic orchestration of data, strategy, and foresight. As the digital marketplace evolves, assortment intelligence becomes increasingly indispensable, additionally fostering a symbiotic relationship between customer satisfaction, profitability, and the enduring success of e-commerce enterprises.

How does technology fit into assortment intelligence?

Therefore, a mere one-size-fits-all assortment model may not be the way to go. Online retailers can wield an arsenal of tools and techniques to finesse their assortment strategies. 

  • Data analytics: Harnessing the power of historical sales data, customer surveys, and comprehensive datasets to unveil trends and patterns in customer demand, paving the way for informed decision-making.
  • Category management: Entrusting the responsibility to category managers, experts adept at developing and optimizing assortments within specific categories such as groceries or electronics.
  • Assortment planning software: Leveraging cutting-edge assortment planning software to navigate the complexities of decision-making. This serves as a guiding compass, considering factors like customer demand, profitability, and available shelf space to pinpoint the optimal mix of products and services.

A real-life success story 

Amazon’s case can be taken as a real-life success story for the apt use of assortment intelligence as a sales strategy. Amazon uses a sophisticated algorithm to personalize the shopping experience for each customer. This algorithm takes into account a variety of factors, including customer purchase history, browsing behavior, and product reviews. Amazon recommends products to customers based on their likely interest in buying them.

amazon recommended
Source: Mageplaza

Some of their key strategies include “Recommended for You” and “Frequently Bought Together” recommendations. Amazon’s successful use of assortment intelligence has helped it to become one of the most successful e-commerce businesses in the world. By offering customers the right products, Amazon has increased sales, profitability, and customer satisfaction.

Related reading: The power of data: how pricing and assortment intelligence drives business success

Benefits of assortment intelligence

It is clear that assortment intelligence is a strategic tool that can help retailers achieve their business goals. This is done by enabling data-driven decisions about their product mix. It also offers a number of significant benefits, including:

Tailoring product mix for target audience

Assortment intelligence can help retailers tailor their product mix to their target audience by providing insights into customer demand, preferences, and behavior. 

For example, a retailer that targets young adults might use assortment intelligence to identify the latest fashion trends. It can also be done to ensure that they have a wide selection of products that appeal to this trend-conscious demographic. The retailer could also use assortment intelligence to understand the target audience’s budget constraints and to offer a range of products at different price points.

Planning seasonal and trend-based assortment

Assortment intelligence can also help retailers plan their assortments for different seasons and trends. By analyzing historical sales data and tracking industry trends, retailers can identify which products are likely to be in high demand during different times of the year and during specific trends. 

Maximizing profitability through smart assortment

A retailer can use assortment intelligence to identify the products that have the highest customer margin. The retailer could then focus their marketing and promotional efforts on these products to increase sales and profitability. Thus, assortment intelligence can help retailers maximize profitability by providing insights into product profitability and customer margin. 

Personalizing and applying customer segmentation

Through personalized recommendations, retailers can seamlessly assist customers in finding and purchasing their preferred products.

Assortment intelligence can also be used to segment customers and tailor the product selection to each segment. By analyzing customer demographics, purchase behavior, and other data points retailers can offer a more relevant and engaging shopping experience.

Ensuring availability of high-demand products

Tracking sales data and customer demand patterns helps retailers ensure that high-demand products are always in stock, reduce the risk of stockouts, and improve customer satisfaction.

Reducing product returns and improving satisfaction

Analyzing product return data and identifying the products that are most likely to be returned and why helps retailers make changes to their product mix and/or return policy to reduce the number of returns.

How to implement assortment intelligence?

As retailers delve into the intricate process of implementing assortment intelligence, they set the stage for a profound transformation beyond mere data analysis. It’s a paradigm shift in how businesses curate and present their offerings to the world. Here’s how retailers can implement assortment intelligence successfully:

  • Collect data: Retailers need to collect data on customer demand, profitability, shelf space, competition, and seasonality. To gather this data, retailers can explore various sources, including historical sales data, customer surveys, and market research.
  • Analyze the data: Once the data has been collected, retailers analyze it to identify trends and patterns. This analysis can be done using a variety of tools and techniques, such as data mining and statistical analysis.
  • Develop an assortment plan: Based on the data, retailers can develop an assortment plan that identifies the optimal mix of products and services to offer. The assortment plan should take into account all of the factors that are relevant to the retailer, such as customer demand, profitability, shelf space, competition, and seasonality.
  • Implement the assortment plan: Once the assortment plan has been developed, implement it. This may involve making changes to the products and services that are offered, as well as to the way that they are displayed.
  • Monitor and adjust the assortment plan: Finally, monitor and adjust the assortment plan on a regular basis. That way you can ensure that it is still meeting the needs of the business and its customers.

Best practices in assortment intelligence

To get the most out of assortment intelligence, it is important to adhere to a few best practices:

  • Use a variety of data sources: Retailers should use a variety of data sources to get a complete picture of customer demand, profitability, shelf space, competition, and seasonality.
  • Use data analytics to identify trends and patterns: Retailers should use data analytics to identify trends and patterns in the data. This will help them to make better decisions about their assortment.
  • Involve category managers in the assortment planning process: Category managers have a deep understanding of the products and services in their category. They can play a valuable role in developing and optimizing the assortment.
  • Use assortment planning software: Assortment planning software can help retailers identify the optimal mix of products and services to offer.

Looking ahead: The future of e-commerce

In a bigger sense, assortment intelligence is the linchpin of e-commerce. Its impact, from tailoring products to maximizing profitability, underscores its pivotal role. Encouraging widespread adoption for long-term growth, exemplified by industry giants like Amazon, it aligns businesses with evolving customer needs.

The future of assortment intelligence promises AI-powered solutions, predictive analytics, and AR integration. As retailers implement strategies, assortment intelligence becomes a dynamic force propelling innovation, and anticipating customer expectations in the e-commerce landscape.

Create the optimal mix of products for your online customers with our e-commerce analytics solutions.

Connect with us
  • I agree to receive updates on the latest industry trends, products and services from Netscribes.
  • We respect your right to data privacy and security. You may unsubscribe from our communications at any time. For more information, check out our Privacy Policy.