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The Analytics of Things vs. Internet of Things – The Four Considerations That Matter

By James Gagliardi / June 8, 2015

I recently read an article in Direct Marketing News about the Internet of Things. It discussed how the attention shouldn’t be placed on just devices; but rather it should be placed on data, analytics and insights. Chief marketer at SAS, Jim Davis, suggested that this idea could be referred to as “the Analytics of Things.” He stressed the importance of looking past devices and delving deeper into the data, pulling the analytics, and gathering insights.

This caught my attention, especially since Digital River has been sharing its point of view on the Internet of Things and the role it will play in the future of ecommerce.  Jim Davis’ assumption is interesting, yet I can’t help but wonder is it really more about data and analytics than it is about the products consumers are connecting together?

While I do agree that analytics plays an incredibly important role, I continue to believe that it’s the Internet of Things that is the lead actor in this story. The Internet of Things is first and foremost the primary agent that is fundamentally disrupting how products have traditionally been sold, bought and consumed. The Internet of Things is about turning products into platforms, then turning those platforms into services – and ultimately adding consumer value to those services. In this evolution, analytics becomes a key supporting and informing factor, providing important inputs for not only merchants, but also consumers. To ensure that analytics provides value to the Internet of Things, keep these key considerations in mind:

  1. Collect data with purpose: What kind of data are businesses collecting? Is it meaningful? Are they collecting the right amount? Think about our smart phones. Smart phones transmit an incredible amount of data about our lives and everything we do. For instance, if our phones are set to allow location services within apps, there are apps that will actively collect our location data whether we’re using the app or not. This lack of control and purpose can be very frustrating. It’s important for businesses to offer consumers choices over when and how our data will be collected and then only collect information that will lead to better, more customized services for our needs.
  2. Use data to make personal customer connections: Once businesses have collected the data, it’s important to present the information back to consumers in a way that will resonate with them and ultimately add value to the product experience. For example, many Internet-enabled fitness bands will collect all sorts of data on our activity and sleep patterns. If the bands simply display our activity level, there’s only so much we can do with that information. But when a fitness band provides us with suggestions on ways to increase our activity level or ideas on improving our sleep – then it’s actually adding value for us and providing more customized information in a way that will improve our experience.
  3. Turn data into time-saving conveniences: Connected devices can be a catch-22. Just because a device is connected, doesn’t make it any more convenient. We want to use different devices that we believe will make our lives easier; but the more devices we have, the more siloed they become, and the more inconvenient they are. Manufacturers need to think about how they string these devices together in order to ensure a better experience. As we move forward, businesses should be thinking about how the data they are collecting can fuel the Commerce of Things – which is the next evolution of the Internet of Things and the ability for connected objects to make commercial transactions by themselves. For instance, data could be used to support replenishment programs. Right now, connected toothbrushes can report on how often and effective we brush, but it is still up to us to go and order replacement heads whenever we need them. But what if a new brush simply arrived in the mail every time you needed one? Businesses need to collect the data, analyze it, predict what services would be meaningful, then automate it for the ultimate convenience.
  4. Surround data collection with people. Predicting what consumers will need or want requires experts who are going to crunch the numbers and the data. Data and analytics on their own are only part of the story – they are dependent on people to analyze and interpret the data, looking for patterns and variations, and then taking action in a meaningful way to improve the end-consumer’s experience.

What are your thoughts on the “Analytics-of-Things” and “Internet-of-Things”? What role do you see analytics playing in the Internet of Things?

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