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Making Money From Internet of Things Data

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Making Money From Internet of Things Data

IoT's most useful component is the data it generates. Businesses need to be ready to switch up their models and make use of IoT analytics to benefit.

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The Internet of Things (IoT) has arrived, and the promise of a connected-device world is taking shape as innovative companies bring improvements to market in the form of automated water meters, connected industrial machinery, and useful consumer products, to name just a few categories. With the current estimated number of connected IoT devices reaching well into the billions, there is still tremendous room for growth to the projected 50 billion devices expected to be connected to the IoT by around 2020. That is a big number, and there is a lot of opportunity for innovation at every layer of what is going to be a very large and very complex industry.

It is that large number of devices that has many industry observers suggesting that the greatest value of the Internet of Things may not be the Things themselves at all. Rather, the argument is that the data generated by all those connected devices is the most valuable aspect of the IoT, and the analytics of all that data is the most direct path to the increased utilization, productization, and monetization of the IoT. It makes sense on many levels; after all, devices do not connect directly to each other, but through the data they generate.

The conversations between billions of connected machines may yield insights that have never been possible. Yet a clear explanation of why IoT data matters is elusive to most. The following is my humble attempt to explain.

IoT Business Models Go Beyond the Obvious

First, you should know that IoT Analytics is already a multi-billion dollar segment of the IoT industry. Mainly, device data is being collected and visualized by humans who use the data to make better business decisions. That is a great start, but IoT Analytics can be applied to monetize IoT data directly.

Here is an example: Connected parking meters are a small example of how the IoT is making our cities more user-friendly. Wireless parking meters can accept credit cards, which is more convenient for consumers, which increases revenue for cities. That is the direct IoT business model.

IoT Analytics can identify the indirect IoT business model. Parking meters know when parking spaces are vacant. That data can be sold to app developers who want to make a parking spot finder app. Parking meters also know what kind of credit card you used, which indicates demographics. A good IoT Analytics firm can use that data to create a heat map overlay on a city map indicating what kind of consumers are where and when. That data can be sold to advertisers to improve their billboard placement. It can even be used in real time to deliver the right message to the right demographic at the right time using next-generation connected (IoT) advertisements.

Connected parking meters are a very small slice of the overall Internet of Things. Imagine how billions of other devices may be generating data that can be turned into revenue, and you start to understand why people think IoT business models are all about the data and why the IoT Analytics segment is expected to grow significantly.

It should be noted that turning data into revenue from otherwise unmonetizable products is nothing new. An example that most people can identify with is Google. Google built a search engine. It didn’t make any money, but it did generate a lot of data. Then Google added Analytics to analyze all the data about whatever we were all searching for. Once the value of that data was understood, Google was able to turn that data into a product that could be monetized. You know that product as AdWords. AdWords is what it looks like when you turn Internet search data into a sellable product. What does it look like when you turn IoT data into a sellable product?

Well, IoT data is obviously very different from web search data, requiring an entirely new and different set of algorithms to parse, understand, and package all of that data into entirely different products for entirely different customers, and that is exactly what the IoT Analytics segment of the larger Internet of Things is hard at work doing right now.

With billions of devices generating trillions of data streams, it isn’t difficult to imagine that in all that data there is some useful insight that is of value to companies, consumers, and even other devices that can use that IoT data to make improvements and increase value. That is the ultimate promise of the Internet of Things, after all, and that is why IoT data is so important. 

Cisco is a software company. Surprised? Don’t be. Join DevNet to explore APIs, tools, and techniques that developers are using to add collaboration, IoT, security, network priority, and more!

Topics:
iot analytics ,iot data ,iot ,industrial iot

Published at DZone with permission of Shawn Conahan, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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