AI trends in retail industry

AI trends in retail industry

Digitalization has changed the way we search, discover and shop, and it is also changing the landscape of the retail sector. Although the physical store is still in the game, e-commerce brings fierce competition and new standards of customer expectations. To stay ahead of new entrants and keep up with the pace of full digital transformation, retailers are now adopting new technologies, especially artificial intelligence, to stay relevant in a crowded market.

Faced with many retail challenges, artificial intelligence is now used to personalize the shopping experience, optimize the supply chain, and increase conversion rates through massive customer data. Artificial intelligence also helps the traditional brands to stay competitive in the market and gives physical stores an edge. Today, we can see many popular applications of AI are visible in the retail industry. But, before moving into the trends that have impacted the retail industry entirely, let’s shed some light on the journey of AI in the retail sector.

AI scenario in the retail industry

We have arrived at the year 2020, and long before we entered the “year of the future”, Artificial Intelligence (AI) had already become a reality that is increasingly present in people's daily lives. With a focus on the consumer, this technology has helped companies from the most different segments to understand and anticipate the customer's behavior and desires. Cars are not yet flying, but technological innovation has completely changed many of our habits. After all, today, very few people can live without a smartphone by their side, right?

Mobile has been a key element in the relationship between brands and consumers. I can bet that after WhatsApp you started sending more text messages. This is a good example of how consumer behavior changes as technology evolve. Similarly, AI has also transformed the customer and retail buying journey, and these changes end up directly impacting sales.  Today, 95% of consumers research online before deciding from which physical store to buy; 87% of them check online if the physical store has the product they want to purchase; and 94% of the money is still spent on physical stores, according to Google data. That is why an online presence is so important for companies nowadays. Regardless of size, your business needs to appear in potential customer searches.

According to a new research report released by Global Market Insights Inc., the artificial intelligence market in this segment is expected to exceed $ 8 billion by 2024 as it is driven by increasing investments worldwide. This investment is attributed to the broad applications of technology in the industry, along with advanced analysis and machine learning.

Also, the survey says, artificial intelligence is ready for the next phase of the digital age in which we live, and all players in the market are preparing for this. Investment in technology is growing rapidly, dominated by giants like Google, Microsoft, IBM, AWS and Baidu. With the retail space becoming rich with more e-commerce platforms in the face of this scenario, as well as startups with great technology, the adoption of AI in the market is practically "forced" to increase.

Impact of AI trends in retail industry

Computer Vision – Computer vision already has many applications in different sectors. However, in retail, this technology is completely changing the customer experience, both in physical stores and online. Amazon, for example, surprised when it opened an Amazon Go store, where payment boxes did not exist. At these stores, customers can pick up items of their choice and leave the store without ever using their credit cards. Items are scanned and customers are billed through their Amazon account, using computer vision, deep learning, and sensor fusion. The technology is also reaching traditional retail stores more and more. Through in-store cameras and artificial intelligence, companies can monitor the performance of their products on the shelves and conduct analysis using machine learning to optimize product placement and promotion.

In addition, cameras can help a physical store better understand the customer experience. Is the store floor plan optimized? Do customers spend more time in one area of the store than others? Where do you spend most of your time? Do these patterns correlate with the sales conversion data we collect from our POS system? All of these questions can be answered with the use of a camera and AI that analyzes facial expressions and connects them to different human facial expressions and emotions.

Micro fulfillment Center – Considering that fast delivery is critical to any e-commerce strategy, micro fulfillment centers are proving effective. Micro fulfillment centers are small warehouses, usually located in urban areas close to the end consumers. Not only do these centers have more space than regular supermarkets, but they are also 94% smaller than traditional warehouses. At the center of these vertical stacks, artificial intelligence is implemented to suggest the best locations for items on the shelves. It is also used to prioritize tasks and guide ground robots to collect and organize cargo. Rami Levy in Israel, Wal-Mart in the United States, and Ocado in the United Kingdom are retailers that implement micro-fulfillment centers worldwide.

Image Recognition Application – AI is supporting search and discovery in a saturated retail environment. Retail stores are using image recognition to make it easier for customers to get what they are searching for. Neiman Marcus' Snap. The find shop application lets customers quickly browse stocks to search for the same or similar products. Similarly, Target used this approach in collaboration with Pinterest. Using Pinterest lenses, customers can upload images of any product and show them recommended products that are similar and available to Target. Both methods use machine learning to identify similarities in a project, whether it is the subject of an image or a visual pattern similar to other images. For Target, working with leading companies on visual search is a forward-looking initiative that not only saves a lot of time but also leverages the influence of social media in consumer decision-making.

Online Expert Advice – Despite the boom in e-commerce over the past decade, customers still value brick-and-mortar stores, and they can touch the product and try different sizes before buying. North Face attempts to bridge the gap between physical and online stores with its expert personal shoppers. The app mimics a retail expert and helps customers navigate e-commerce stores while getting recommendations similar to the in-store experience. For online shoppers, additional support and further guidance may be needed, as nearly 70% of shopping carts are abandoned before the purchase is complete.

Dynamic Pricing – Pricing in many industries such as airlines, car rental companies, hotels, etc, includes so many complications, as several factors affect it. Still, many companies are relying on an old formula involving only acquisition cost and a static profit margin. Dynamic pricing is possibly the best pricing model today because it is based on an analysis of factors that really influence prices, such as competitor prices, consumer behavior, buying periods such as long term or short term, customer information and customer price perception. In addition, with the help of machine learning, prices are systematically updated to reflect any change in conditions.

The main benefit of adopting dynamic pricing is the ability to offer the right price at the right time to the right customer, with the goal of maximizing sales conversion and margins. However, in order to obtain valuable results from dynamic pricing, it is important to take into account factors such as sufficient quality data and a customized algorithm that meets your specific business model.

Robots enhance in-store experience with AI – Ever walked into a department store and feel overwhelmed by the many products on display? Macy's calling app saves customers from the arduous shopping experience. After entering the store, the user opens the app and starts chatting with the AI bot. After, receiving instructions for specific store items is not a daily robotic experience. Robots can also check if items are in stock and alert employees when they feel frustrated by customers. Here, the robot reads the customer's emotions through the process of sentiment analysis, understanding, and classification of opinions expressed through language (text and speech). This tool is one of the most valuable branded AI solutions and is powerful enough to monitor people's thoughts or feelings in real-time.


Analyzing the new trends and the penetration of AI in the sector, it is undeniable that the traditional retail model is bound to end. The technology will reshape the entire inventory and operations management cycle of retail stores, thereby providing a renewed shopping experience for customers. Not only will the efficiency and sales of the retail space increase, but the proliferation of artificial intelligence will cause the world economy to grow massively, opening doors for several high-tech startups and a plethora of new job opportunities.

Comment here