Assortment planning in retail: optimization and automation


One of the key elements in every store, both physical and virtual, is assortment planning. In this article, we will discuss how to optimize and automate it taking into account seasonality, store localization, store clustering and other relevant factors.


What is retail assortment planning?

When you enter a store or visit an online shop, the assortment of goods that you see, where they are, how prominently they are placed, and how much merchandise is purchased, is the result of a detailed planning process.

All of these aspects are vital to increase sales and are what make assortment planning important.

The practice of placing the assortment of a store’s products in the optimum place to show their best features and potential benefits is called “visual merchandising.” This can include everything from where the products are placed to how much shelf space is regularly allocated to products. This is a central part of any effective assortment plan and is therefore key to any retail strategy.

There are other key factors belonging to the assortment planning process, as well as other terms we will have to define in order to talk about the challenges posed in creating a sound assortment planning strategy and then how to overcome them.

Assortment: Starting from the basics, when we talk about “assortment” in assortment planning, this refers to which range of products retailers are currently offering at any specific time.

Seasonality: This is an extremely important consideration. In addition to considering market trends, retailers must also include specific periods in their assortment plan. Good strategic assortment planning identifies which products should be purchased by the store, and then marketed and placed appropriately according to that retailer’s visual merchandising strategy—no swimwear on prompt display in winter, and no woolly jackets in summer.

Localization: Different areas require different products. Good assortment plans take into account store locations, as different stores will often vary the merchandise available according to customer purchasing history. This is an important consideration for online stores also, which are able to use geolocation to determine consumer demand by area.

Store clustering: Customer demographics and consumer demand determine the visual merchandising in terms of store layout, and also which inventory is ordered and in what quantity. Stores that are geographically close, or webshops that target a specific area, will have similar store characteristics. The assortment plan can therefore be applied to stores as a cluster, rather than requiring a specific plan for each store.

The base range: These are products that continue to sell and remain popular, regardless of local differences. These will therefore be prioritized items that will have the same store location regardless of the retail environment. In-store shoppers will consistently seek out these products and expect to find them in a specific place, regardless of store location.

Cross-merchandising: The location of inventory items in a store is key, and this is especially true with cross-merchandising. Here, complementary displays show mutually beneficial items to be purchased together, so as to encourage impulse buying from the individual shopper. Therefore, the retailer will create assortments of complementary products.

In addition to the above key factors, product assortment planning must include an analysis of the features of each project that influence its demand. This includes aspects such as the style (and whether this represents a current trend), the color, the size, and what the product is used for. This will inform both next season’s assortment and how to group similar stores as to where inventory is sold.

All of these things appeal or do not appeal to customers and will therefore determine decisions as to what is placed where and how much shelf space they will inhabit. Other metrics such as shelf life and assortment (i.e. range of products offered) are also key here. In terms of the online store, these attributes influence how items are ordered on different pages, and which items are prominently displayed on landing pages.


Optimizing the assortment planning process

There are affiliated areas in IT that can help retailers build a highly effective assortment planning strategy, and so optimize the assortment plan overall.

These are:

  • Big data: Retailers must have a strong grasp of the past data that relates to the factors that led to previous successful sales, such as local demand, customer demographic, and how the store layout contributed to converting customer behavior into purchased units. This data is useless unless it can be represented in a way that offers insights and a plan of action. Data analytics can streamline this process and offer data that is clean, without superfluous or extraneous details.
  • Stock and assortment tracking: The ability to manage inventory is important: if too much stock is purchased, then this can lead to waste. If too little stock is purchased, then this can lead to empty shelves and the inability to satisfy customer demand. A live database can show how much stock remains and when it should be replenished, based on an analysis of previous customer behavior and current trends.
  • Live analytics: Current trends inform and complement aggregated historical data. IT experts can use analytics tools—such as Google, Adobe, or Heap—to show contemporary market trends and pair this with past performance. This is the sort of service that could highlight serious errors in the planning process of a retail business that only bases its decisions on what has worked before.


It is clear that if all of this is completed manually with only human labor, then the process is time consuming and also prone to error.

Retailers must not only collate all of the data relating to past sales, store locations, store size, product ranges, and customer demand, but must also use this data to anticipate future marketing trends and identify which base ranges are going to stay constant. This is an enormous undertaking and requires large teams, which can eat into costs and resources.

When it comes to retail assortment planning in retail, therefore, many retailers in this area opt to turn to IT experts who are able to advise on the above considerations, as well as to how to use such expertise in automating the retail planning process. This frees up more time, which can then be used to allocate staff resources to creating a better business strategy.


Artificial intelligence and process automation in assortment planning

After the pandemic, shoppers now expect online stores to offer merchandise in a process that is thoroughly integrated with seamless payment and transport organization. The same goes for the product assortment planning of physical stores, with increased customer traffic having pronounced consequences for inventory management and how long items stay on shelves.

It is, of course, inevitable that retailers are adopting AI and automation tools in greater numbers and increasing their reliance on them, so as to take the edge off the human factor in labor requirements. Given the advantages these solutions confer, there is no doubt that their use will continue.

AI is sought after because it simplifies intimidating amounts of data, from inventory costs and sales to customer demographics, for both individual and group stores. AI-based platforms can sift through this data to present well-calibrated hypothetical situations, which if taken into account in the planning process, will increase sales and so contribute toward retail success.

Setting up and calibrating an AI system to perform the relevant tasks of assortment planning, from analysis of historical data to accurate forecasting, is not simple. Fortunately, AI is often synonymous with automation or hyperautomation, which professionals are ready to assist with.

It is possible, then, for automated systems to predict emerging trends and future retail contexts with a higher degree of accuracy than even the most experienced retail worker, and at a greater speed. This is vital for financial objectives to be met, especially if staff can be reallocated to roles other than analyzing product data themselves.

Next season’s product assortments and an accompanying effective brand strategy can then be summoned by the retailer instantaneously, resulting in highly effective assortment plans that take into account product categories, store clustering, and also individual stores.

This streamlines the overall process and allows for an effective assortment plan pertaining to product ranges and the most appropriate brand strategy to be devised and applied to multiple stores in hours rather than days or weeks.


IT, automated solutions, and the profit margin

Financial performance is always a key consideration, and profit margins are currently under increased tension. Wages are rising due to inflation, and the raft of new e-commerce apps that are increasingly adopted by the industry are expensive. These growing costs eat into profit margins.

Retail is becoming more global due to the emergence of online as well as international department stores. This results in an increased market, but also increased competition—something that’s especially problematic when multiple companies are attempting to target similar demographics.

In this case, the business benefits of automating and having IT professionals assist in retail data and analytics for assortment planning are clear.


Business benefits of assortment planning automation and optimization.

  • Automation used well can lower these costs as it reduces the need for human labor in some respects and also reduces the need for purchasing licenses for multiple apps.
  • Analyzed data can yield actionable insights for assortment plans that when implemented lead to increasing sales. It is the assortment decisions, the identification of top sellers, and the right mix of stock and where to locate this in the floor space at the right time that is the main strength here.
  • Customer data informs these decisions and allows for a more customer-centric approach, which in turn allows for greater customer satisfaction. As retailers are aware, increased customer satisfaction translates directly into being able to meet more ambitious sales targets, so keeping the profit margin healthy.
  • AI and automation can produce a hypothetical forecast and assortment plan based on solid historical data involving stock and customer behavior to be able to produce a highly effective assortment plan that allows retailers to maximize profitability and customer return.
  • Personalization: Different businesses have different assortment planning needs, as seen in the numbers of stores, customers, and areas of operation. Some businesses may only be online. Whatever the needs involved for assortment planning, the necessary variables can be entered into the software, so producing thoroughly optimized assortment plans that are unique to each retailer.


Final summary and takeaways

The assortment planning process is a complex and delicate one, depending on both historical and contemporary trends.

A sound assortment planning business strategy for both department stores and online stores depends on the ability of retailers to analyze their sales and product data. This should cover all of the relevant assortment planning factors and result in an effective retail plan to enable the realization of that period’s given financial objectives.

Good financial performance is directly linked to the retailer’s ability to plan inventory purchases according to the main product, assortment, and store data points as outlined above. Excel spreadsheets are not as helpful here to retailers as IT services such as automation, which can remove human error in assortment planning, and significantly save on costs and time.

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