Industry Tech Boosters: IoT And Big Data In Retail

Mateusz Polakowski

Aug 17, 2021 • 11 min read
IoT and Big Data Usage in Retail Industry

Retail, one of the best-digitized industries, is advancing in technology-driven digital transformation.

IoT and big data in retail, the two industry-leading technologies, are having a huge impact on retail business.

They provide companies with a wealth of new opportunities to get to know their customers and offer them customized customer journeys with product suggestions and bespoke experiences based on their past choices.

According to a 2019 McKinsey study, implementing personalized recommendations and triggering communications using these technologies have brought retail organizations tangible benefits in customer engagement and spending. Some have realized 5%-15% revenue increases and 10%-30% increases in marketing spend efficiency.

McKinsey study on retail personalization Alexa AI

Source: McKinsey

With the big data analytics market set to reach $103 billion by 2023, the use of big data and IoT in retail is only expected to grow, due to the wide scope of applications of both of these technologies. Here’s why.

Big data - from ball and chain to retail business advantage

Let’s start with the data point of view of how IoT and big data work together. As a process of analyzing information, big data helps companies to gain insight into their business patterns.

Generated data streams obviously require an effective IT architecture, hence the challenge for system designers attempting to forecast the demand for the required computational power as the amount of data increases.

The vertical scaling of infrastructure is one way of expanding capacity. Although adding more resources such as memory and power to an existing machine is relatively simple, handling the growing volumes of information created by big data in retail is quite problematic for this method.

The amount of additional hardware is limited, not to mention the increased costs of performance and a potential loss of operational efficiency. But there’s another method of adjusting infrastructure to the increasing needs that is more effective.

Horizontal scaling describes forming a distributed network of servers. This can process tremendous volumes of data by dividing it between different machines, all handling smaller volumes of information.

The business advantage of big data in retail is unlimited capacity to grow. In theory, you can add as many machines as you like to fit your current demand. But that’s not the end of it.

Innovation driven by IoT and big data

IoT and big data are inseparably connected and the industry uses this connection to the full extent.

Internet of Things (IoT) describes the network of everyday items, devices, and objects that are all linked via the internet. As such, these connected devices provide an extensive volume of unstructured data sets in a retail setting that big data analysis helps to handle and structure.

IoT analytics have a huge potential when it comes to supporting business decision-making processes, as the combination of IoT and big data in retail provides more detailed information on customers: who they are, their location, what their preferences are and much, much more.

There are several IoT retail applications where this technology is used to build a complete customer profile. For example, an application where customer preferences are recorded. Sensors from IoT devices can track their habits and behavior, then big data can aggregate and review this information, evaluating the volume, speed, and frequency of different behavioral patterns.

Providing marketing teams with big data insights, companies can ensure they target their audience with more relevant offers. It’s a step towards a more personalised customer experience, leading to an uptick in sales and increased efficiency.

How are IoT and big data used in retail?

Considering the amount and diversity of unstructured data collected and analyzed with big data and IoT in the retail industry, both technologies stand as transformation drivers for retailers.

By exploring the volume, velocity, and variety of customer information, big data in retail can reveal how humans behave and interact when it comes to their consumer habits. This can identify different patterns in how their customers shop - information businesses can leverage to engage with this audience and grow it.

Other typical applications of big data and IoT in retail include data gathering and subsequent sharing through sensors. Real-time data collection is an effective way of monitoring supply chains or stock in warehouses alongside customer habits. IoT devices also act out commands from a distance, meaning processes are automated and enhanced.

These applications vary, but when you do utilise both IoT and big data in retail, these innovations speed up operations, reduce the strain on your human workforce, and dramatically lower costs.

Retail big data analytics

The main purpose of combining IoT and big data in the retail industry is to help companies get a better understanding of customers’ behavior to ensure they are meeting demand. It starts with unstructured data collection, however, many database frameworks aren’t able to process that amount of information.

Spreading it among many servers may be the solution. Imagine aggregating sales data from hundreds of locations from thousands of daily generated receipts and in-store IoT devices.

That kind of cumbersome task is easily solved when an additional layer is applied and a single server analyzes generated data only from its district or customer segment.

But information collection is only the tip of the iceberg, as raw data doesn’t improve the understanding of customer behavior and the reasons behind it. Using big data analytics gives it meaning and makes it possible to turn data into insights instead of just plain reporting.

For example, businesses can create more personalized shopping experiences based on reviews, previous purchases, and analyzing customers’ behavior in-store.

Other benefits include analyzing social media and online trends for more accurate forecasting around popular consumer products or enhancing the view of the customer journey to learn more about how purchases are made.

Streaming data in real-time

In the hyper-connected world of IoT and big data, it is crucial for companies to deploy real-time big data analytics to review information as it happens. Monthly reports are definitely informative, but rapidly responding to the latest data insights gives retailers leverage over their competition that cannot be overestimated.

IBM has recently underlined the importance of live data streaming when it comes to informing strategies and processes. According to their findings, 60% of all sensory information loses value in a few milliseconds if it is not acted on.

Many big data processing tools like Spark Streaming or AWS Kinesis have been implemented to target these issues and are very powerful when it comes to tapping into real-time online behaviors.

These frameworks provide a funnel for processing information that arrives from a variety of sources, like IoT devices. Then, data can be stored, transformed or analyzed using algorithms to extract meaningful insights.

Smart retail inventory management

As appetite for both online and in-store sales continues to grow thanks to big retail reopening in the wake of Covid-19 restrictions easing, refining supply chains, inventories, and the journey of stock from warehouse shelf to customer is a key concern.

With speed and efficiency as the greatest challenges, an automated retail inventory management system can be important for retailers, wholesalers, and distributors looking to track their inventories, enhance supply chains, and ultimately boost sales. The adoption of IoT and big data in retail can be very important in responding to these new demands. Here are some examples of this technology in action.

Smart shelf technology

Intelligent shelf software solutions are a great example of the relationship between IoT and big data. In the first instance, this technology can offer businesses a live view of the amount of goods available in their stores and warehouses, as well as their types and specifications. This can enable businesses to optimize and more accurately control their supply chains.

Smart shelves also have the ability to interact with apps on a customer's smartphone to enhance their shopping experience.

For example, IoT sensors installed in the shelves are capable of figuring out when a customer approaches and what they previously purchased. This means the app can then show shoppers deals on any items they’ve previously purchased or relevant discounts.

Temperature and humidity IoT sensors

Apart from monitoring stock levels, IoT and big data can use sensors also to measure in-store temperature and humidity levels. Analyzing these types of data enables retailers to offer clients the freshest products, guaranteeing that they have not expired. Food manufacturers can ensure a consistency of quality to their products while adhering to food safety standards.

Big data can help retailers review information such as the temperature of goods in transit or the performance of food manufacturing equipment. All of these benefits will hopefully lead to a better quality product reaching the customer.

Robotic warehouse systems

IoT can simplify processes, with warehouse fleet robotics representing a huge leap forward in terms of retail inventory management in distribution centers.

They can go beyond human capabilities, as they require little space, provide flexibility in managing varying demand requirements, and are able to work 24/7. This repetitive work can be carried out by these new systems quickly, with fewer errors and more cost-effectively than before.

Companies like SqUID create systems and robots that can autonomously handle parcel operations like fetching or distribution. Simple commands are enough to get a particular package moving and sent to the customer. This is possible due to the use of hundreds of IoT devices and big data processing real-time analysis.

Additionally, these robots are data sources themselves, generating tremendous amounts of information that can be processed further to deliver additional value (like real-time error management or process optimization).

Moreover, when IoT and big data are combined to manage robotic systems, live orders can be fulfilled within moments, without any human interruption.

The future of IoT and big data in retail

Big data and IoT in retail are clearly technologies and concepts that aren’t common and widely deployed yet. Nonetheless, these are not only academic or theoretical areas of interest, but great ideas that many businesses can benefit from in reality.

Moreover, as so-called “smart warehouses'' consist of up to 90% of space used only by robots, many retailers think about IoT as a part of their company’s strategy that enhances digitization and process automation.

Here, we’ve only skimmed the surface of what IoT and big data are capable of for the retail industry. Excitingly, it means that there’s a huge amount of white spaces to be explored and filled in the future.

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Mateusz Polakowski

AI Consulting