The Internet of Things (IoT) may sound like a futuristic term, but it’s already here and increasingly woven into our everyday lives. The concept is simpler than you may think: If you have a smart TV, fridge, doorbell, or any other connected device, that’s part of the IoT. If you’ve used an app on your phone to navigate through your day-to-day tasks, then that’s also part of the IoT. With the IoT, the future is now, but how does this connected world really work? More importantly, how can businesses get on board so they’re not left behind the competition?
The answer to both questions is big data. Big data powers the IoT, and as data connectivity evolves into 5G networks, Wi-Fi capabilities expand, and smartphone users grow even larger in population, the “big” in big data grows even bigger. Let’s take a look at two examples of how businesses can be part of the IoT despite not being in the tech industry.
These examples show how the combination of IoT connectivity and big data continuous transmission can make things better for businesses and their customers. IoT enables an improved experience for everyone involved, but how does it actually work? Let’s take a closer look.
To understand exactly how big data and the IoT work together, we need to examine several pieces in the overall workflow:
Big data and IoT devices have a symbiotic relationship, and if there’s an AI system responsible for processing that data and making decisions, then that adds another variable to the equation. As big data storage is both the repository and source of data, the more IoT devices that get connected or the more complex the AI model, the greater the spotlight on big data hardware. Performance and processing depend on the capacity of the big data hardware to pull what is necessary, which highlights the importance of investing smartly in efficient hardware and optimized infrastructure design.
Let’s go back to the two examples above, the theme park and the retailer. Their uses of big data and connectivity directly impact the possibility of people converting into customers.
Theme park example: One of the biggest reasons why people avoid theme parks is the lines. But real-time data showing the status of lines—and in turn, aggregate data that can show average wait times at specific points of the day, similar to the way Google Maps projects drive times for certain hours—makes the whole venue more accessible. It allows people to maximize their time and plan around their needs, be it small children or just sheer patience, and that in turn converts customers and builds relationships.
Retailer example: The best-rated retailer apps are the ones that provide both savings and convenience. To achieve this, combining unstructured data (like social media mentions or demographic data) with structured data (a user’s browsing history on the app) can generate smart recommendations, even entice with algorithm-generated coupons. For example, if a city is having a heat wave, backend analysis can show a spike in regional fan searches, cross-reference that with a user’s browsing history, generate a coupon for a specific product in-app, and notify that it’s available for in-store pickup. Data and connectivity thus work to bring the user back into the store for purchasing more items at lower prices.
Note that in both of these cases, investing in big data collection and device interconnectivity pays off by building upon the expected customer experience to offer the industry standard while evolving with current capabilities. From a technology perspective, this means establishing the avenues for identifying the data, collecting it, and then processing it and outputting it in a format that benefits the business and the consumer.
For businesses looking at exploring the opportunities made possible by an IoT paradigm, there are two major areas to consider. First, ask how your business can use interconnectivity and metrics to better your customer experience. This might even be an indirect benefit, such as creating a system that optimizes your inter-departmental communication to ultimately streamline processes for waiting customers. Second, consider the current state of your IT infrastructure. Adapting to the needs of IoT and big data involves elements such as scalability and processing speed beyond traditional hardware capabilities.
Thus, such a decision may feel like it solely belongs to the IT department, but it really is a business decision. These opportunities create ways to deliver immediate dividends, while also establishing a company as forward-thinking and technology savvy, enhancing its reputation and customer loyalty while building the technological foundation for future improvements. Though it requires up-front resources to create an IoT experience, such an investment is almost a necessity these days. Given how much connectivity has become part of our daily lives, not supporting big data and IoT is a sure way to fall behind the competition in today’s dynamic and connected business landscape.
To learn more about big data, IoT, and analytics, check out the following links: