Post COVID-19, the retail world is seeing a massive change in consumers’ behavior and shopping dynamics. The retail industry is transforming as e-commerce, online retailing, in-store retail, and omnichannel retail are leveraging AI-ML-enabled digital tools & technologies for business outcomes. Varied challenges also have surfaced to balance online-offline eco-space based on changing consumer demands and priorities.

For retail businesses, varied key metrics are now focused around operational savings, enhanced customer experience, increased ROI, improved campaign revenues, demand forecasting, better pricing, etc.

Artificial Intelligence (AI), and Machine Learning (ML) are key technologies that help retailers in the above areas. AI/ML is also having an effective, lasting impact on varied areas of merchandising.

AI Technology

Let’s explore and see how AI is inspiring Smart Merchandising in the retail sector:

AI-Driven Merchandising

Smart Merchandising is also referred to as AI merchandising, where several aspects are taken care of by the very digital technology influencing business outcomes. Delivering excellent customer service by providing the exact merchandise they want at the exact time via a preferred channel (online/offline). Thanks to the AI-predictive analytics that predicts customers’ preferences and demands in advance.

Demand Forecast

Merchandizers across the globe are grappling with unforeseen demand & expectations of customers,& other related issues, especially in the post-pandemic era. The impact of demand shocks(internal & external) is finely taken care of by DF (demand forecasting). Which product is high in demand and other demographic details, AI-ML-predictive analytics greatly help.

Thus, you see, whether you belong to b2c or b2b framework, AI-ML-powered demand forecasting, and predictive analytical tools help in multiple ways.

AI in merchandizing predominantly helps to generate forecasts & determine demand signals for smooth decision making, merchandising planning, product replenishment as well as pricing forecasting.

Consumer Buying Pattern

AI-ML-NLP-powered predictive analytics help merchandisers in knowing the specific buying pattern of consumers in advance. Buyers and consumers get frequent product recommendations for purchasing them, through the smart merchandising tools powered by Artificial Intelligence.

AI-ML-NLP allow users and buyers to interact with digital chatbots, during their entire shopping journey using their specific languages. There’s no language barrier, no geography constraint, and no time zone barriers.

Online shopping behavior, recent purchases, reviews, preferences, buying patterns, the preferred mode of shopping channels/platforms, payment systems, etc. are the key points that retailers come to know in advance via AI-ML technology.

AI-ML-NLP does sentiment analysis based on consumers’ social media conversations. Thus, merchandizers are provided with prescriptive recommendations by AI that allow them to know the buying pattern and accordingly act upon it.

Financial Forecast

AI merchandising is helping the retail sector immensely. It is quite an uphill task for merchandizers to forecast buying or purchasing of materials for their shops/stores; they don’t know what quantity, amount of merchandise they need to buy, and stock to achieve their financial goals.

Smart merchandising allows retailers to segregate profiles, and demand preferences of varied consumers, based on brands, colors, sizes, and similar patterns in physical retail shops, and online retail stores/e-commerce shops.

Now, the planners/merchandisers can buy and allocate sizes, colors, and quantities accurately throughout their warehouses, stores, and inventory(in-store inventory as well as e-commerce) based on categorized input put forth by AI. This way, they can know in advance how much seasonal merchandise they need to buy/stock to achieve the financial outcome.

Price Optimization

Miscalculations and imperfections in pricing strategies are major challenges in the life of retailers/merchandisers. For instance, they miscalculate in the areas of promotional, Omnichannel, and markdown pricing adversely affecting the profit margins of those retailers.

Smart Merchandizing powered by AI helps them to reduce such miscalculations by optimizing their pricing strategies for selling products online or offline stores.


Segmentation is a big challenge for merchandisers and retailers across the world. There are varied factors that hugely affect the segmentation part. Demographics, consumers’ shopping behavior, and their purchasing history are a few of these factors.

These data cannot be segmented perfectly, accurately by humans. Smart merchandising, facilitated by AI-ML algorithms determine these factors and accordingly creates the segments.

Smart Approach

AI in merchandising is helping retailers in multiple ways. Demand forecasting, predicting consumer behavior, recommending future markdowns, and forecasting omnichannel returns are varied AI usages in merchandising.

However, one area in which AI needs human intervention is ‘creativity’! The man & machine hybrid model is the crux. Merchandizers will never be out of work but will have a definite competitive advantage using Smart Mercnadisng, inspired by AI.