Traditional retail is facing constant pressure to outperform the competition. Retailers have to provide superior customer service and operational efficiency – all with a personalized touch – that has been difficult to achieve.
However, the power of AIoT can help brick-and-mortar retailers create enhanced, personally curated shopping experiences – both in store and online.
AI in the retail market is estimated to skyrocket from 9.65 billion USD in 2024 to 38.92 billion in 2029, representing a seismic shift in how retailers can leverage this technology to transform the shopping experience. in fact, some of the top brands, including Zara, H&M, and ASOS, are already leveraging AIoT for success.
How the Current Retail Landscape Has Evolved
The current retail landscape has undergone rapid change in recent years, fueled in part by shifting consumer behaviors and emerging technologies. Traditional retail environments are up against considerable challenges, including:
- Declining foot traffic: Traditional brick-and-mortar stores are experiencing a decrease in foot traffic as more consumers turn to online shopping. This trend has been accelerated by the COVID-19 pandemic and its limitations on in-person shopping.
- Competition with e-commerce: E-commerce has grown rapidly – especially during COVID-19 – offering consumers more convenient shopping options and wider inventory without geographic constraints. This has put increased pressure on traditional retailers to adapt and improve their online presence and stay relevant.
- Generic consumer experiences: Traditional retailers are struggling to provide personalized and engaging customer experiences. Consumers have become accustomed to retailers understanding their preferences and offering tailored recommendations and promotions.
To stay ahead, retailers need to focus on meeting consumers where they want to be with personalization, convenience, and innovation – all of which can be done with AIoT.
What Is AIoT and How Does It Work?
The artificial intelligence of things (AIoT) is the combination of artificial intelligence (AI) technologies with internet of things (IoT) infrastructure.
AI technologies like deep learning, machine learning, and natural language processing can enhance the functionality and performance of IoT devices to collect, analyze, and act on data in real time. Together, these technologies elevate each other’s capabilities for smarter and more efficient automated experiences and improved consumer experiences.
IoT devices collect data from their surroundings using sensors and other data collection mechanisms. These devices can range from simple sensors on household appliances to complex machines like semi-autonomous vehicles.
Once the data is collected, it’s transmitted to a centralized location like a cloud server for storage and processing. This can include consumer interactions or information about the environment and performance of the device itself.
This is where AI comes in. AI algorithms can make use of the data that IoT collects and identifies trends, patterns, and anomalies to offer valuable insights to improve efficiency and productivity.
How AIoT Is Creating New Opportunities for Retail Organizations
AIoT is transforming the retail industry by creating new opportunities for retailers to streamline operations and enhance customer experiences. Here are some examples:
Personalization at Scale
AIoT gives retailers the ability to collect real-time data from IoT devices about customer shopping patterns, interests, and behavior, giving them insights to personalize product recommendations and promotions.
For example, Thread, which has been acquired by the British retailer Marks & Spencer, used machine learning to scale personalization services with a platform that paired customers with personal stylists.
Tailored Product Recommendations
AIoT allows retailers to analyze customer data, including purchase history and browsing behavior, for tailored product recommendations. This personalized approach – which is what online shoppers are already used to – enhances their satisfaction and increases the likelihood of conversion.
Dynamic Pricing and Promotions
AIoT offers rapid-fire data insights to dynamically adjust pricing and promotions based on real-time information, including competitor pricing, inventory levels, and customer demand. This level of agility is difficult to achieve in traditional environments, giving retailers an edge to optimize pricing strategies and maximize revenue.
Enhancing Operational Efficiency
The capabilities of AIoT improve operational efficiency by optimizing supply chain processes. IoT devices track inventory levels, monitor product movement, and predict maintenance needs. This information can help retailers streamline operations and reduce costs.
Inventory Management
AioT enables retailers to track inventory in real-time using smart shelves and radio frequency identification (RFID) tags and readers. This up-to-the-minute visibility helps retailers maintain the ideal inventory levels, reduce stockouts, and improve overall inventory management for better profitability and less waste.
Zara took this approach by integrating AI into its supply chain management with the Just-in-Telligent supply chain system, which blends inventory management principles with AI and real-time data analytics.
Creating Immersive Experiences
Brick-and-mortar retailers struggle to create an immersive in-store experience, but AIoT can help. For example, retailers can use augmented reality (AR) to allow customers to visualize products in their own space before making a purchase, improving engagement and driving sales.
HY-LINE Group developed its interactive point-of-sale Smart Shelf Display solution using Lantronix. Combining the best of online and in-person retail shopping, the Smart Shelf engages customers, captures buying behaviors and delivers analytics to generate increased sales and revenue growth.
Overcoming Challenges with AIoT Implementation
While AioT holds a lot of promise for addressing the challenges for retailers, it comes with some challenges of its own.
Addressing Privacy Concerns
Vast amounts of personal data are collected and processed by AIoT systems, creating concerns around data ownership, consent, and privacy. To address these concerns, retailers must ensure data protection with robust security measures and consent for data collection and usage. In addition, there are privacy regulations retailers must comply with.
Overcoming Technical and Infrastructure Hurdles
Integrating AIoT with existing systems and ensuring scalability can be an obstacle. Retailers need to evaluate their current infrastructure and identify areas that should be upgraded or modified to better support AIoT implementation and scalability.
Cost Consideration
While AIoT can pay off in the long term, it’s a significant upfront investment. Retailers need to weigh the potential return on investment of AIoT implementation and adhere to a budget that balances both the upfront costs and long-term cost benefits. However, there are ways to minimize the costs while maximizing the benefits, such as leveraging cloud services.
AIoT for Retailers
One of AIoT’s most exciting applications is in retail, creating a retail environment that’s more efficient, personalized, and responsive for both profitability and customer satisfaction. As more and more retail brands leverage AI for success, there’s likely to be more innovation within the industry.
Author
Guido Voigt is the Director of Engineering, at Lantronix, a global provider of turnkey solutions and engineering services for the internet of things (IoT). Guido’s and Lantronix’s goal is to enable their customers to provide intelligent, reliable, and secure IoT and OOBM solutions while accelerating time to market.