Top retail tech trends in 2024

As 2024 unfolds, the retail industry is facing a spectrum of formidable challenges: a myriad of technologies, the complexities of omnichannel retailing, and the imperative of sustainability are all reshaping the landscape. Retailers are now focusing beyond just identifying trends; they are committed to providing analytics that demonstrate the tangible value added by their technology. Here is a list of the top retail tech trends that will shape the year ahead.

AI-Powered Solutions to make strides

In 2023, AI made huge waves in the retail sector, with retailers looking to use it to drive efficiency across several areas of their business. As per Statista, 73% of retailers are already using AI. Over the next 12 months, a further 15% of retailers plan to implement the technology. Amber Hovious, VP marketing and partnerships at Teamwork CommerceFrom marketing and financial forecasting to customer service and market analysis states that retail leaders will lean on AI to achieve more operational efficiency and deliver high-quality customer experiences in 2024.

Jessica Grisolia, industry solutions director (Retail) at Scandit also reveals that retailers across sectors are taking a deliberate approach to integrate generative AI into shopping – from redefining search, creating personalised, context-specific promotions to optimising internal processes to improve efficiency and drive out costs. Different sectors are likely to prioritise different opportunities for generative AI. For example, apparel retailers are experimenting with conversational shopping, breaking out of the linear Search and Browse experience. General merchandise retailers are seeing increased efficiencies from using generative AI in customer service, especially with returns optimisation. For speciality retailers, AI-powered virtual assistants will be used to elevate high-margin, specialty services across sectors, from home design consultations to makeup appointments to jewellery fittings. Whereas, department stores should look into generative AI’s ability to improve real-time price comparison and deal alerts, as well as overall online search results.

Generative AI plug-ins being implemented into platforms like ChatGPT, Google Bard, Amazon, or Apple could take shoppers all the way to checkout through a live link within the chat interface. Grocers, on the other hand, have a unique opportunity with shopping assistants, as customers can be directed to new brands, products, and ingredients that fit into their diet, budget, and lifestyle—with this channel boosting the power of their retail media networks. We will see more grocers experimenting with generative AI bots that would allow shoppers to create grocery lists based on their budget, dietary preferences, history, and tastes through knowing their preferences and purchase history.

Augmented Reality

Another technology becoming increasingly prevalent across multiple enterprises and in frontline environments such as the supply chain is augmented reality (AR), according to Grisolia. She states that for the store associate managing stock in-store, AR overlays can provide invaluable guidance as to inventory levels (whether in the same or another store, back of house or elsewhere), identification of products in similar-looking boxes and insights into stock expiry dates. As well as optimising inventory for the retailer, it can also significantly increase the efficiency of workers in their daily tasks and enable them to focus on higher-value tasks such as engaging with customers.


Leveraging AR aligns more closely with the needs of the large mainstream retail landscape, which often prioritises proven, reliable, and cost-effective solutions over ‘cool toys.’ In essence, while riding the AI wave might seem tempting, it’s the more incremental innovations like AR that could offer a more practical and immediately beneficial path for retailers, especially when considering the balance between innovation and proven reliability in business operations.

Nisa managed to capitalise on this kind of tech as a result of their desire to use technology to build an instant digital relationship with its customers. The solution implemented? A mobile app-based vouchering system called Scan and Save, integrated with a smart data capture platform presented customers with promotions they could redeem directly from their mobile device using AR overlay.

Martin Johansson, managing director of online florist Serenata Flowers also believes that as an online retailer, AR has the potential to revolutionise the consumer purchase journey by allowing customers to view products in their own homes before making a purchase. We anticipate this technology will become more prevalent in retail apps and websites to provide immersive and interactive experiences for shoppers.

Seamless Omnichannel Experience

In order to retain consumers on their e-commerce platforms and attract shoppers to their stores retailers have to work hard. However, an omnichannel strategy helps them unite these two fronts. When in-store and online experiences are integrated shoppers have more options. Brick-and-mortar retailers are keeping up with the times by offering customers more online pick up in store (BOPIS) alternatives. This blends the speed and customer service of in-store buying with the ease of shopping online.

Additionally, to enhance the experience of using smart shopping carts, retailers will start integrating “Omnichannel Customer Profiles”. The consumer and sales representatives can access these profiles at every touchpoint, and they are updated with each new encounter. Clients are able to create a “smart shopping basket” that they can use to make purchases at any time and from any channel of their choosing. For instance, a customer can save an outfit they like on their app and one week later they can go in-store to try on the outfit. They can finally check out their basket from your online shop a couple of days later.

Data utilisation and analytics

According to Stuart Higgins, partner at BearingPoint, advances in technology and cloud computing mean that it is now far easier to collect, store and analyse large volumes of data, bringing previously impossible analytics capability into the heart of retail decision making. He says that there has been an explosion of data generating devices, such as smartphones and wearable technology and each of us now leaves a digital fingerprint whenever we interact with technology. Retailers can use that data to better understand who we are, what our likes and dislikes are and ultimately, how better to service us in order to enhance our brand loyalty and secure our share of wallet.

He added that retailers can now leverage big data to understand their business and their customers in ways that were not thought possible only a few years ago. They can tailor store ranges and product assortments using local customer demographic data to enhance understanding of who is shopping in which stores and what they are likely to buy. They can use previous purchasing history to curate online ranges so the customer only sees products they are likely to buy based upon previous learning. They can use big data to train AI chatbots to be able to cater for the needs of any customer calling a customer service department. They can generate augmented reality images to allow customers to ‘try on’ clothes before they buy online to reduce the risk of returns. Or they can simply use more granular data to better understand the true cost drivers within the business in order to improve cost and efficiency like never before.

There is a consistent theme here around using the vast volume of data now available to improve business insight. However, one old adage remains; “garbage in / garbage out.” For retailers to truly leverage data and analytics to drive business performance, they need to ensure that the data they are using is clean, consistent, relevant, and accurate – and that requires the development of new data governance and data management strategies which, unfortunately, few retailers currently possess.

Chatbots and virtual shopping assistants

Over the past several years, consumer-focused chatbots in retail settings have helped streamline customer service interactions. With GPT-based models, consumers can receive 24/7 customer support, resolve issues with no waiting, track shipments and receive updates on order status. For instance, eBay introduced a chatbot for Facebook Messenger in Canada that makes it simple for users to buy, sell, and get other service requests fulfilled. Personalised recommendations, purchase tracking updates, and more are all available from the chatbot. Sephora, however, uses chatbots on a number of platforms that offer customised beauty advice and recommendations to its customers.

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