The retail sector is experiencing ongoing transformations due to the growing demands of customers and the rapid advancement of new technologies. However, it’s important to discern between trends in retail technology that hold practical value for optimizing business operations and those that may seem more like fiction. Let’s take a look at the retail tech trends that can bring tangible benefits for your business and learn what you need to get started using them.
Trend #1 – Artificial Intelligence is Changing How We Shop
Over the past year, artificial intelligence has taken markets by storm. With generative AI, nearly every industry has been disrupted, and retail is no exception. Artificial Intelligence implementation helps retailers automate their operations, leading to increased profits and optimized business processes.
Inventory Management
AI is a powerful tool for analyzing consumer spending trends. Some items move around on the sales floor more than others at different times of the year. To ensure that quantities are kept up to date, you need to audit items regularly. Combined with demand forecasting models, you can use AI algorithms to plan inventory reductions and increases according to forecasted changes in demand.
By analyzing the demand patterns for specific products on different days/seasons, and leveraging inventory data and actual information on sold products typically stored in POS systems, machine learning algorithms can be applied to accurately predict the timing for replenishing certain products. This enables you to optimize inventory levels by reducing excess stock and ensuring timely restocking.
Generative AI in Retail
Chat-GPT and various other large language models have captured the attention of millions. Although having AI generate marketing copy is useful, there are other ways that generative AI can help retailers advance their goals.
For example, chatbots are typically associated with business-to-consumer interactions, but Wal-Mart has taken a different approach. The major retailer uses a generative AI chatbot to negotiate prices and terms with product suppliers.
Another promising approach to improve retail operations is to use generative AI for store layout and planogram creation. Using rich data from customer analytics, demand forecasting, and available space and shelving options in a particular store, layouts and planograms could be generated automatically.
Personalizing User Experiences with Data Analytics
Retail businesses keeping track of customer behaviors in-store and online are reaping the benefits of AI-driven data analysis to better personalize experiences for shoppers.
Eagle Eye Communications and Propositions Director Sarah Jarvis writes that the future of retail personalization will be about generating unique messages and offers for customers on an individual basis. AI can base these messages and offers on the customer’s historical, current, and predicted behaviors. Some approaches to personalization that can be used are upselling, suggested items, and bundling through smart product recommendations.
AI recommendation systems can be built using different approaches. Collaborative filtering analyzes the behavior of similar customers to make recommendations, while content-based filtering focuses on the similar attributes of the products themselves. Hybrid approaches combine multiple techniques for improved accuracy. The recommendations can be delivered to customers through various channels, such as personalized emails, on-site product suggestions, mobile app notifications, or targeted advertisements.
Waning Focus on Self-Checkout Technologies
One subject of artificial intelligence in retail applications is self-checkout technology. Although self-checkout POS devices have been popular for over a decade, more advanced solutions are often a topic of fascination by retail technology professionals. During the pandemic, 87% of shoppers preferred to shop in stores with touchless or robust self-checkout options.
However, some of the most ambitious and futuristic innovations in self-checkout technologies are starting to wane. Amazon is scaling back on their Amazon Go Grocery stores which have championed the “just walk out” model for customers. Powered by a sophisticated array of cameras, sensors, and AI systems, Go Grocery provides a convenient shopping experience for consumers.
One reason why this model may not be as effective as originally hoped may be a hyperfixation on technology instead of customers. Longbow Asset Management CEO Jake Dollarhide suggested that Amazon Go Grocery was “an expensive hobby” rather than an effective business model.
Although the “just walk out” model may be ahead of its time, machine vision-based self-checkout applications may work better on a smaller scale. For example, smart vending machines can be a cheaper alternative for such solutions.
How to Start With This Trend:
- Build or hire a remote team of AI engineers who will be responsible for implementing AI innovations in your company.
- Understand what data you have that can become the basis of AI solutions.
- Turn to AI product consulting to create a clear AI implementation strategy based on the best match between your business goals, market needs, and technology capabilities.
Trend #2 – Omnichannel Retail Experiences
Competition is fierce on every front of the battle to win the hearts and minds of consumers. Retailers not only have to fight hard to get customers into their brick-and-mortar stores but also to keep shoppers on their ecommerce websites.
The primary approach to unify these two fronts is an omnichannel strategy, sometimes called a “phygital” approach. By integrating in-store and online experiences, consumers will find their shopping sessions more consistent. They will also have more options to choose from when they shop.
Buy Online and Pick Up in Store
Brick-and-mortar stores are continuing to utilize and expand buy online pick up in store (BOPIS) shopping options for consumers. This combines the convenience of online shopping with the swiftness and service of in-store shopping.
BOPIS infrastructure is about more than just accounting for inventory. Most order pickup solutions require a lot of manpower to maintain. Finding items scattered about the store can take time, especially if those items are in the wrong locations.
One particular problem that order pickup workers face is “double tappers”. Coined by Target Drive Up workers, this term describes a customer who parks at the store, then taps “I’m on my way” and then immediately taps “I’m here”. This gives the store zero time to prepare their order, delaying delivery to the customer. Perhaps with unique innovations in UI and fulfillment processing, retail businesses will be able to set realistic expectations for their customers while continuing to build trust and loyalty.
Innovative Point of Sales Systems
One of the major challenges software engineers face when developing POS systems is real-time data synchronization and instant UI for core business operations across all in-person locations and online stores. Innovative POS must provide retailers with a centralized view of their stock. This enables accurate inventory tracking and ensures that customers have access to real-time product availability information, whether they are shopping online or in-store.
One critical component of bridging the gap between online and offline shopping experiences is payment. Being able to accept various digital payment methods adds convenience and consistency to the customer experience. Accepting “buy now, pay later”, QR code payments, virtual payments like Google Pay and Apple Pay, and even cryptocurrency, can provide better accessibility for online and offline shoppers. This helps reduce friction at the point of sale and enhances the overall shopping experience.
How to Start With This Trend:
- Identify the channels you want to integrate as part of your omnichannel strategy.
- Invest in a robust, unified commerce platform that can integrate all your sales channels, inventory management systems, customer databases, and other relevant systems.
- Partner with software experts to analyze your existing infrastructure and update it in line with your new strategy. This may include upgrading your POS systems, implementing mobile apps, and adopting new software solutions.
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Contact usTrend #3 – Indoor Positioning Systems for Stores
I’ve always found indoor positioning systems (IPS) to be fascinating. When I worked at my retail job, I always imagined that AR-based directions would someday guide workers to parts of a store or warehouse to pick items for customers ordering online.
Although that future may be on the horizon, we do need to be realistic. IPS systems can help retail businesses today, but the future I imagined may not be here quite yet.
At this stage of indoor positioning technology development, it can’t lead customers directly to a certain product on a shelf. Here we’d need centimeter accuracy, and that’s just not possible yet. However, indoor navigation can direct shoppers to the right store department. This can make navigation much easier for guests of large supermarkets and shopping centers.
Implementing in-store navigation solutions for your business can be challenging. The first step is hardware. Having the right infrastructure in place is essential, whether it be Visual Markers, Bluetooth beacons, Wi-Fi RTT, or Ultra-wideband (UWB). For example, Target chose to implement Bluetooth IoT lighting systems at many of its locations. When guests shop with the Target app on their phones in stores, they can get access to a map that helps them find their position in the store and find the items that they need.
This particular solution placed Bluetooth beacons in the lighting systems above the sales floors. However, other solutions may be possible based on the layout and size of the store, since the use of beacons can be prohibitively expensive and provide insufficiently accurate navigation. After the infrastructure is set up, all that’s left is to develop the software that can take advantage of it.
How to Start With This Trend:
- First of all, accurately map the environment you want to navigate.
- Consult with app developers to choose the best positioning approach for your business case, as well as identify potential challenges and opportunities for implementing indoor navigation.
- Build a team to develop your indoor navigation solution.
Trend #4 – Augmented Reality Shopping Experiences
Augmented reality has been a big part of retail for years now. Thanks to the development of tools like ARKit, augmented reality is becoming the basis of more complex and multifunctional solutions for retail businesses than before.
Try-On Solutions
Bridging the gap between digital and physical shopping experiences is perhaps the holy grail of retail marketing. “Try before you buy” solutions powered by augmented reality help achieve this goal.
Often referred to as virtual fitting room technology, shoppers can see how they look when trying out various products, particularly apparel and accessories. At home, it’s also possible to visualize how furniture or wallpaper will look. With AR experiences, it’s as simple as placing a virtual sofa on your living room floor with your smartphone camera.
In fact, IKEA’s version of this lets you do much more than just see the size and shape of furniture. IKEA Studio can use the unique LiDAR technology on iPhones to display rooms, measurements, windows, doorways, and more to visualize interior design like never before.
In-store, augmented reality holds great potential for delivering enhanced product experiences to customers. By scanning a barcode or activating a pop-up display, AR can showcase the product’s features and benefits. This not only adds a competitive edge to the product but also serves as a compelling incentive for shoppers to visit the store and personally witness the unique AR experience.
Assisting Planogram Setup
Making sure shelves match their planograms is a critical task for the quality of merchandising. Augmented reality could be used to help merchandisers see a 3D model of a completed planogram overlaid onto a shelf or fixture in front of them. This can help them set up shelves and zoning devices, and to place products in their appropriate locations. These experiences could be powered by widely used ARCore-capable devices like the Zebra TC-51 and its successors.
Although this may be a useful feature, it’s worth noting that it’s not uncommon for retailers to have to improvise and deviate from a planogram due to space in a store, available shelves, and tools, as well as available products. As a result, AR-planogram tools may not be beneficial in some situations.
How to Start With This Trend:
- Determine your objectives for implementing AR in the store. Identify specific use cases, such as product visualization, virtual try-on, interactive product information, or gamified experiences, that can enhance the customer journey and drive sales.
- Enlist the support of experienced AR developers to select the best technology solutions and create an AR application that easily integrates with your existing infrastructure.
- Educate store staff about the AR technology and experiences offered in the store.
Trend #5 – Demand Forecasting
One of the most prominent topics of innovation in retail is demand forecasting. Predicting demand for products has a number of important advantages that can benefit your business:
- Inventory optimization: prepare inventory for high product demand periods and keep your stock on track
- Cost savings: know exactly how much your business needs to buy to meet demand in a given period
- Revenue: by forecasting periods with low revenue, retailers can strengthen marketing efforts to increase sales during this time
- Sustainability: reducing overstock is better for the planet, as less products go unsold and sent to the landfill
- Competitive advantage: being able to better predict customer trends than your competitors can give you an advantage in the market
It can take between 1.5 to 2 months to create a proof of concept for a demand forecasting project. One of the greatest advantages of building demand forecasting models is that they can be trained on production data and usually should not be additionally labeled; businesses can use predictions for live operations while development is still in progress.
The most successful demand forecasting approaches are handled by AI. Machine learning can pour through the massive datasets needed to accurately predict demand and sales. From the AI’s analysis, a program can offer suggestions and if allowed, make decisions automatically to make sure stores are stocked with the right items for that period.
How to Start With This Trend:
- Collect existing sales data for your products. Usually, a three-month period of historical data for one item is enough to kick-start forecasting with ML.
- Identify factors that affect demand for your products such as seasonality, geography, holidays, etc.
- Start working with Data Science engineers to get the most out of your data and turn it into an effective demand forecasting solution for your retail business.
Trend #6 – 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, it’s now easier than ever to create engaging, conversational experiences between customers and chatbots.
For example, eBay launched a chatbot in Canada for Facebook Messenger that allows customers to buy, sell, and get other service requests met with ease. The chatbot can provide personalized recommendations, order tracking updates, and more. Meanwhile, Sephora utilizes chatbots across several channels. Customers can receive personalized beauty advice and recommendations from Sephora’s chatbot.
It’s important to keep in mind that off-the-shelf services can address common tasks with a moderate level of quality. However, if AI is the core feature of your chatbot product, relying solely on ready-made solutions may not be sufficient. The more complex and innovative your idea is, and the more advanced tasks you intend to entrust to AI, the higher the likelihood that existing models will fall short of meeting your specific requirements.
AI chatbots for stores can provide customer support by handling inquiries, offering product information, and addressing frequently asked questions. They can also assist customers with placing orders, tracking shipments, and providing updates on order status.
How to Start With This Trend:
- Determine what functionality you want to include in your chatbot solution and what business goals it will help you achieve.
- Establish a team that will be responsible for analyzing existing solutions on the market and whether they meet your needs.
- Work with experienced software engineers to create the best technology solution based on your strategy.
Trend #7 – Voice Commerce
Although home voice assistants have yet to fully incorporate advanced conversational artificial intelligence, their ability to serve customers in the retail space has improved tremendously. Ordering products from home with your voice, with or without a screen, leaves a lot of nuances to be explored.
Walmart’s Voice Ordering is a notable example of this technology in action. By asking smart speakers to add products to a cart, they can place orders entirely by voice. Walmart workers then make these items available for pickup.
There may also be some promise in integrating this technology in-store with AR-capable smart mirrors. By simply speaking commands to a smart mirror, a virtual fitting room experience could be generated based on the prompt.
How to Start With This Trend:
- Determine the specific use cases where voice commerce can add value to your store. This may include voice-activated product searches, voice-based ordering, personalized recommendations, or voice-enabled customer support.
- Hire a team that can evaluate and select a voice assistant platform to integrate into your store’s ecosystem.
- Build voice-enabled applications tailored to your store’s use cases and integrate them with your existing software ecosystem.
What Comes Next for Innovation in Retail Stores
The most important innovation that will transform retail businesses this year will be generative AI. This may impact ecommerce platforms more than in-store experiences at first glance. However, savvy brands will find ways to integrate their online shopping experiences with in-store.
More important will be the benefits that AI has on backend processes such as inventory management, supply chain negotiations, and other processes. Brands need to find ways to integrate new technologies like AI to improve existing workflows. With bankruptcy an ever-present threat, anything that can put the customer first and enhance business practices to make and save money is worth exploring.
Stores online, brick-and-mortar locations, and combined business types are working to use technologies in new ways and find unique solutions to problems that will put them on top. If you’re ready to be a forerunner in the industry and stand out against the competition, it’s time to work with experts to transform your vision into reality.
Reach out to learn more about MobiDev’s retail software development services today.
