Smart shelves, sensors, and self-checkouts have become usual tools in shops around the corner. IoT in retail is not a future anymore; it’s a self-sufficient economy that grows by 25.9% annually.
Yet, IoT implementation in retail stumbles into barriers—siloed systems, a lack of orchestration, adoption friction, and poor analytics keep retailers from implementing IoT at a larger scale. At this point, you understand that having some IoT in-house is not enough; implementing and managing this technology wisely is what really matters.
In this article, you will learn how to overcome the IoT implementation frictions and maximize the benefits. If you are a retailer, you’ll learn how businesses deal with fragmented visibility between stores, manage to turn real-time data into actionable insights, and implement innovations smoothly on real-life examples.
Suppose you develop SaaS tools for IoT in retail. In that case, you can expect insights into how retail chains implement tech and include solutions for real-world IoT challenges in your software offering.
Rustam Irzaev is a MobiDev .Net Team Leader with expertise in cloud solutions, retail, ERP, AI, and SaaS development. He helps MobiDev’s clients create scalable, complex, maintainable, high-performance systems, searching for the optimal way to combine tech and business needs. In this article, based on his extensive hands-on experience in the domain, Rustam shares practical insights on implementing IoT in retail.
The Role of IoT in Modern Retail
IoT refers to devices that connect the physical and digital worlds. IoT applications in retail include smart sensors in appliances like shelves, fridges, cameras, robots, and automated POS systems. They perform tasks like movement tracking, condition monitoring, and inventory management, giving store owners unprecedented visibility into inner operations.
Therefore, it is no wonder that the business world readily invests in IoT. According to Fortune Business Insights, the IoT in retail sector will reach $350.85B in 2032, a considerable increase from $57.30B in 2025.
This is part of a larger IoT trend: the general IoT market is also growing—the number of IoT devices worldwide is predicted to increase to 30 billion items by 2030.
An interesting part of this trend is the rising adoption of IoT analytics. Since retailers and manufacturers collect a lot of data that needs processing, they also invest in the means to analyze this data more readily. The IoT analytics market is projected to grow 20% yearly and reach $130B by 2032.
At the same time, the sphere of IoT applications in retail expands. Industry leaders like Walmart and Kroger monitor shop inventory in real time and implement tech to help customers better navigate to products they love. These are just some of the wide spectrum of examples.
Below, we discuss the key applications of IoT in Retail in more detail.
6 Key IoT Applications in Retail
The application of IoT in retail can be extended to several categories, such as inventory management, supply chain visibility, in-store behavior analysis, automated checkout, and energy saving.
- Inventory management. Smart sensors, RFID readers, computer vision, and depth-sensing cameras allow businesses to easily track every item’s location in the warehouse and collect granular information on stock quantities.
- Supply chain visibility. Sensors and cameras with computer vision and OCR scan delivery items at every step of the delivery route and report the precise location of goods. Sensors on shipping containers ensure conditions like temperature are sustained.
- Customer behavior analytics. In-store motion tracking appliances provide a picture of customer movement, helping stores optimize product placement.
- Customer experience and personalization. Customer in-store tracking, digital price tags, and shopping history analysis help retailers create more personalized shopping experiences. For example, a US retailer, Kroger, navigates shoppers to the items they need or want through an app.
- Smart checkout & Payments. Self-checkout systems combined with mobile payment streamline payment and reduce queue times.
- Energy management. IoT-connected HVAC, lighting, and refrigeration systems can automatically optimize for energy efficiency, saving money and reducing environmental impact.
Overall, in the future, we’ll see more ways to use IoT in retail. It’s an exciting journey of innovation, and we’re thrilled to be part of it. Meanwhile, for retailers, deciding which technologies are needed in the first place is essential to create an implementation roadmap.
For SaaS owners, understanding which technologies are most sought by their consumers will help them adjust their products to become more competitive. Below, you can learn about the most common IoT in retail examples, their benefits and technologies to use.
7 IoT Use Cases that Deliver Real Value in Retail
There are different types of IoT technology, some of which deliver value in the first place. Based on MobiDev’s experience and industry-wide research, we hand-picked 7 IoT use cases in retail that offer business-critical results when implemented.
A number of systems we describe in this section are developed as custom-made products for individual retailers.
They provide great examples of features to be implemented as part of a SaaS offering or built in-house by retailers wishing to have full control over their IoT.
1. Smart Shelving & Inventory Sensors
The primary function of smart shelves is inventory tracking. Weight sensors in smart shelves send signals when a product is out of stock so workers can replace it.
In connection with RFID (Radio Frequency Identification), smart shelves show the exact location of every product, reducing errors.
Yet, the functionality of smart shelves may be expanded. 3D depth-sensing cameras detect spills and product damage and alert users to initiate fast replacement. Still, this functionality may be expanded even more. For example, the American retail chain Kroger integrated data from smart shelves into its shopping app. Based on shopping lists, the app navigates visitors through the aisles to simplify finding products.
The key features retailers get are:
- Real-time shelf-level visibility
- Automated planogram compliance
- Shrinkage alerts.
Technology Used: RFID, weight sensors, computer vision with edge devices.
2. Electronic Shelf Labels (ESLs)
Digital labels make offline campaigns as fast and flexible as online campaigns. Walmart, a retail chain that recently implemented digital labels, reports that changing prices for a whole category or products takes up to ten seconds.
In Europe, the adoption of the ESL technology is wide-spread. For example, SPAR Austria uses the four-color ESLs providing their customers with information on product, prices, and available discounts. The company’s CEO, Hans K. Reisch believes the technology automates many routines, allowing staff to dedicate more time to customer care.
Besides reducing staff walking time, ESL streamlines restocking. Changing the name and specs of products on one shelf takes several clicks.
Also, electronic shelf labels can provide additional information about each product when equipped with barcodes.
The key features retailers get are:
- Instant price update chain-wide
- Dynamic pricing for demand-driven promos
- Automation of manual routines
Technology Used: E-ink ESLs with BLE/Zigbee connectivity and centralized pricing system.
3. Autonomous Mobile Robots (AMRs) in Warehousing
Autonomous mobile robots take the burden off human workers by performing many routine tasks. Equipped with cameras, RFID scanners, LiDAR, and navigating sensors, robots patrol store areas, detect displaced products and pricing errors, and even help customers with the checkout.
For example, the American retailer BJ’s Wholesale Club uses a proprietary robot called “Tally,” which roams the aisles daily, tracking inventory. IKEA uses a whole fleet of camera-equipped drones for the same purpose.
The key features retailers get are:
- Automating routine tasks like picking and sorting
- Improving warehouse safety with smart navigation
- Integration with WMS for real-time order fulfillment
Technology Used: IoT-connected AMRs with LIDAR and navigation sensors.
4. Cold Chain Monitoring
Cold chain monitoring is a system of temperature sensors that sends data on goods to a centralized software platform. This way, a retailer is alerted when a refrigerator or a batch of products falls outside the set temperatures.
The key features retailers get are:
- Real-time alerts
- Historical compliance reporting
- Reduced reliance on manual temperature logs
Technology Used: Wireless temperature and humidity sensors with NB-IoT connectivity.
Check a success story of the IoT solution for bars, breweries, and restaurants, which helps to get real-time insights into the business’s draft system, inventory levels, and operational efficiencies.
5. Smart Energy Management in Stores
The energy monitoring system analyzes electricity, water, and gas usage through sensors and data acquisition devices.
In retail stores, energy monitoring helps identify energy waste and develop more energy-effective strategies.
Examples of energy monitoring systems in stores include smart lighting systems that allow users to control the lighting intensity, motion-activated lights, automatic doors, and smart HVAC systems.
The key features retailers get are:
- Real-time tracking
- Optimization of energy use
- Predictive maintenance for heating and cooling systems
- Automated energy use adjustments based on occupancy hours
Technology Used: IoT-connected HVAC, lighting, and smart meters with occupancy detection.
6. Real-Time Fleet Tracking and Telematics
Real-time fleet tracking makes every aspect of fleet operations and logistics visible to store management. It works thanks to the smart device system with cameras and scanners, GPS tracking, and accelerometers integrated with logistic management software.
Although delivery companies, like DHL, usually employ this technology, custom fleet tracking solutions offer numerous benefits to retailers.
The key features retailers get are:
- Tracking fleet performance, which allows for managing delays
- Enhancing driving efficiency
- Receiving geofencing alerts for store deliveries
Technology Used: GPS, accelerometers, fuel and engine sensors, CAN bus integration.
7. In-Store Customer Behavior Analytics
In-store customer behavior analytics helps retailers see when customers visit their stores, how they behave, and how their behavior influences the business overall.
Current technology allows us to go even further by unifying customer online and offline activities into integrated data sets. This allows us to track patterns or implement the personalized brand experience via mobile apps.
The key features retailers get are:
- Heatmaps for better store layout planning
- Offering personalized offers to customers via app notifications
- Monitoring and managing checkout wait times.
Technology Used: Footfall sensors, Wi-Fi analytics, BLE beacons
These are just some examples of IoT in retail that can be implemented in the first run. Yet, the success of implementation will depend on your readiness to implement IoT technology into the retail chain in practice, or prepare IoT integrations into your SaaS products.
How to Implement IoT Technology across the Retail Supply Chain
The journey toward IoT transformation depends on your clear vision of the steps to take and scenarios to follow. Below, we describe the key milestones of IoT implementation, such as designing the IoT strategy, integrating the IoT solutions into your platform, and becoming an IoT-mature retailer.
Designing an IoT Strategy: Key Principles
It is essential to align IoT implementation with key business goals, whether eliminating product shrinkage, speeding up operations, decreasing costs spent on routine operations, or increasing customer satisfaction.
Therefore, it is recommended to start with devices and software that fulfill the named goals in the first turn. For example, smart shelves will help combat shrinkage, electronic labels will address the speed of reorganizing and rolling out campaigns, etc.
It is also essential to decide whether your business will start with isolated solutions, like implementing an integrated POS, or building an ecosystem of IoT devices and integrating it with the software you use.
The common issue for IoT devices in retail is the poor integration with ERPs and CRMs. It is possible that the current CRM you use will not accept integration with IoT devices, or even if it does, it won’t be able to handle the flow of data collected.
Several years ago, businesses reported the loss of up to 70% of data from IoT because of the lack of software. The rise of ML and AI changed the rules of the game, and now you can use the IoT benefits to the fullest, but if you use an outdated legacy system, it may require modernization.
Cloud integration is the first step in flawless IoT deployment. The cloud architecture allows for unnoticed transformation. Yet, IoT will also require investment in connectivity and edge computing to make the system work fast.
Integrating It All: The Role of a Unified IoT Platform
As you have planned which devices to implement, decided on the architecture (whether you need single devices or an ecosystem of devices) and system modernization (whether your ERP and CRM needs that or not), your next step will be connecting it all into a centralized hub.
Connecting your devices may require custom software or a ready-made integration platform like AWS IoT, ThingsBoard, or IBM Watson IoT.
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IoT Consulting ServicesAnother essential consideration is architecture. IoT in retail often uses edge computing: smart devices that perform computing tasks themselves.
For example, a security camera in the store processes all of the video and only sends clips with suspicious behavior to the central server. A conventional camera would send the 24/7 footage to the central computer for analysis.
Although edge computing requires extra investment, it helps avoid network overload and helps process important data faster.
You should also consider what you will do with the data once it is collected. Conventional analytic tools use statistical methods to make predictions or send alerts.
Yet, processing your data with machine learning will give you more insights and a basis for decisions. This method allows for considering granular data details, giving a deeper picture of your business’s operations.
Learn Deeper:
How to Build Tech Stack for Omnichannel RetailBecoming an IoT-Mature Retailer
The implementation of IoT in your retail business will mark a shift to a higher league: you will benefit from automating routines, less manual work, and reduced firefighting, as you will be alerted about issues or stockouts in time.
Advanced analytics will help make decisions proactively.
The successful implementation of IoT requires training, staff preparation, and an overall cultural shift. Running the necessary staff training alongside software development and device integration is essential.
Yet, despite the clear vision and thorough preparation, the IoT implementation path may come with challenges. Below, we’ll describe the key challenges of implementing IoT in retail and how to solve them with examples from our experience.
Challenges of implementing IoT
The MobiDev team has developed multiple solutions for dealing with challenges when implementing IoT across various use cases. The key challenges and solutions are as follows:
1. Interoperability Across Devices and Platforms
When building an IoT ecosystem, you must acquire devices from different manufacturers. Despite industry standards of compatibility, these devices often speak different “languages” or use incompatible protocols.
Often, integrating sensors, data gateways, and the software platform for managing them is far from plug-and-play. This creates additional challenges if the business uses the SaaS platform for store management and must hire external specialists to handle all the integrations. Making a SaaS product ready for a wide range of integrations would be a great advantage over the competition.
How to solve it:
An efficient way to fix this issue is to develop software for the electronic sales labels based on Zigbee. The energy systems in the same IoT ecosystem should depend on Modbus. To connect them all, build custom middleware and robust API strategies.
2. Data Overload Without Clear ROI
It is a common problem when sensors generate IoT more data than systems can analyze. Therefore, figuring out how to use that data and tie it to real business needs often becomes an issue.
It creates an excellent opportunity for SaaS developers targeting retail. Equipping their
SaaS with built-in machine learning tools for making data-based insights will solve the data overload issue that retailers may have in the future.
How to solve it:
Collect detailed sensor logs from AMRs, but lacked the analytics tools to identify productivity insights. Introduce ML models to detect the fulfillment KPI patterns and receive the full picture of the system’s functionality.
Learn Deeper
How to Implement IoT Data Analytics3. Security and Privacy Risks
IoT devices are often attack magnets because of insufficient security protocols. The risk of attack multiplies with thousands of edge devices implemented across retail chains, from unsecured smart cameras to employee-tracked devices.
How to solve it:
Enhance IoT security in three steps. First, isolate the IoT network. Second, enforce device authentication, and lastly, roll out the firmware management protocols for all the edge nodes.
4. Scaling from Pilot to Production
Small pilot projects work well in controlled environments. Yet, things change when it comes to scaling, and you have to implement the same system across different stores in the chain.
How to solve it:
A retailer successfully implemented the original footfall sensor in the flagship shop. Yet, when it came to rolling out to 300+ layouts, unexpected implementation challenges showed up. The situation was solved with infrastructure tweaks, local calibration, and localized support.
5. Organizational Buy-In and Change Management
IoT success is much about people. The skills in setting up and managing IoT devices across the store are as crucial as tech support. Quite often, despite the real benefits of IoT in retail,
Therefore, we recommend implementing solid change management strategies, including staff training, right as the device integration is rolled out.
How to solve it:
Following ESL implementation, run in-store trials side-by-side with paper labels. This will allow store workers to learn more about ESL management and compare the process with conventional label management, which was considerably more time-consuming.
We hope this section is helpful for store owners seeking solutions for IoT implementation challenges. SaaS developers will get an idea of how to make their product more implementation-ready. This will help them proactively provide their users with the means to troubleshoot challenges and enhance their IoT systems in the future.
The Future of IoT in Retail
IoT in the retail industry combines convenience for employees and a strategic advantage over competitors. The future of IoT in retail promises that these systems will mature and get more sophisticated. Here are several trends to expect:
- AI-powered automation. Combining IoT sensors with AI enables predictive restocking, innovative promotions, and adaptive store layouts.
- Hyper-personalization. The integration with mobile apps on customers’ phones will offer more personalization. Apps that navigate customers through the store aisles based on their shopping list already exist. We expect that there will be more personalized offers, loyalty rewards, or individual discounts in the future.
- Sustainable operations. IoT enables smarter energy usage, less paper, fewer deliveries, smaller energy bills, and greener business operations.
- Scalable infrastructures. Implementing central dashboards to manage thousands of devices across hundreds of stores will make scaling up or down more flawless, giving retailers space for flexibility.
Build Your IoT-Enabled Retail Software Product with MobiDev
MobiDev has extensive experience in IoT Consulting & Development in retail. Our experts can guide you through the whole IoT implementation process to maximize positive outputs and reach the set goals.
FOR RETAILERS
With our Retail Software Development Services, you can modernize your legacy software, develop an architecture for IoT implementation, and solve multiple issues if you have already started using IoT in retail stores. MobiDev’s AI and ML expertise will help you maximize the use of IoT data collected from devices while turning it into predictive insights and a data-backed basis for decision-making.
FOR RETAIL SAAS PROVIDERS
With our Software Product Development Services, you can enhance your SaaS to meet retailers’ growing need for AI/ML solutions. You can supply your products with improved AI-driven analytics and equip your systems with the integration needed for various edge devices running in one system. Such enhancements can make your product more attractive to many retailers planning to increase their IoT efforts.
