The Pew Research Center released its report, “The Internet of Things Will Thrive by 2025,” last month. The report provides insight and predictions from a range of Internet and digital experts on how the “Internet of Things” will impact society by 2025.

It’s a must-read if you’re just starting to hear about the IOT, or already following it.

The report covers a range of opinions, and data plays a huge role. The summary notes that:

To a notable extent, the experts agree on the technology change that lies ahead, even as they disagree about its ramifications. Most believe there will be:

  • A global, immersive, invisible, ambient networked computing environment built through the continued proliferation of smart sensors, cameras, software, databases, and massive data centers in a world-spanning information fabric known as the Internet of Things.

  • “Augmented Reality” enhancements to the real-world input that people perceive through the use of portable/wearable/implantable technologies.

  • Disruption of business models established in the 20th century (most notably impacting finance, entertainment, publishers of all sorts, and education).

  • Tagging, databasing, and intelligent analytical mapping of the physical and social realms.

Here’s what they mean to you:

  • The first bullet translates into loads of data and context provided by the aggregate of networked objects. Think data is “big” now? The scale will increase by magnitudes, as noted in Mark Challinor’s recent post on this blog.

  • Augmented Reality: Data overlaid on the world as viewed through wearables or smartphone cameras, i.e. look at a shop, see a coupon; look at a restaurant, see a menu; overlaid directions.

  • Disruption: Data and content delivered in novel ways, and from new competitors.

  • Tagging, databasing, etc.: Information on the data and structure of the world (natural and made), as well as the social ecosystem, to analyse and navigate it.

See the trend? The last three topics exist now in lesser forms, and media are trying to find ways to leverage them – but they’re going to blow up and disrupt again in unknown ways once the Internet of Things begins to grow.

How can we position ourselves to adapt? The report offers some insight from Jeff Jarvis:

… Because I use Google’s maps and its newly acquired traffic app, Waze, to navigate every day, Google has intuited (accurately) where I live and where I work, allowing it to serve more relevant content and advertising and commerce with less noise and waste.

My own local newspaper doesn’t know any of that. So, my newspaper continues to give me the same 300 pieces of content it gives everyone else, treating me still as a mass. Google treats me as an individual because it knows me as an individual.

Therein lie the most important factors in new user interactions with machines and the companies behind them: identity and signals. (Emphasis mine.)

The concepts of identity and signals are at the core of topics we’ve previously discussed, most notably with predictive services and the “ambient” user experience. With smartphones and tablets, these services are competitive advantages and sources of user data.

In the Internet of Things, such services are necessities. Not only because they serve the consumer, but because they provide us valuable information – more than just knowing  that “Steve likes sports.”

Even the Google maps example cited by Jarvis is a broad use of user data. With data collected from when a consumer is doing something, where, for how long, and how often, we learn much.

We begin by watching a user read his replica app in the morning , then view the Web site on his phone, and then read the tablet app at night. All the while, we can track the various times, content, and how he interacted within the app.

Along the way, data informs what advertisements, content, and services to push to the user and when.  

Jarvis notes user interactions are as much with the business as with the application. We can build apps that provide this customisation, but without feeding back that information to the business and reacting to it, we aren’t learning.

We’re starting the relationship from scratch with every new app, and building different relationships with each app instead of creating a durable relationship between the consumer and the business itself that transcends the individual apps.

User data should inform the range of relevant business systems. It’s through this information we can see trends that roll up from the individual to the mass. This allows us to better serve our readers individually and as tribes, to discover and fill gaps, and to improve the services and content we provide.

Having a team dedicated to defining and understanding your data structure, meta data, and their relationships across systems and customers is ever more critical.  

The expectations of digital users continue to grow. It’s only through solid back-end planning and data management that we will be able to provide the level of services demanded in the future, much less compete against new competitors and publication channels.