More data than ever before is available about everyone.

Every website you visit can be tracked. Every purchase you make online goes into a database of one kind or another. Every post you like on social media is added to your profile. Every form you fill out, every survey you take, and every online quiz you complete adds more information to the cloud about you.

All that data can be used to create a more complete picture of who you are for advertisers and marketers.

In the coming year, marketers will find new ways to collect even more of that data and more ways to use it. Here are a few trends in store for 2017 big data:

 Focus on Variety Not Quantity

Right now, big data is just BIG.

The focus is on collecting as much data as possible to create audience profiles. But not all that data is useful. Much of it is repetitive and irrelevant information. It either doesn’t expand your understanding of the user, or it doesn’t expand your understanding in a meaningful way.

In 2017, the focus will be on getting as much variety in your data as you can. That will mean looking for data in disparate places and through unique strategies. The idea is to get users to share more information about the various aspects of their lives and their beliefs, as well as to uncover more of the motivation behind their decisions.

Machine Learning to Do More with Data

Technology is becoming smarter than ever (perhaps frighteningly so?), and it can do much more with the data we collect.

In particular, artificial intelligence and advanced algorithms are being used to interpret the data and make smarter decisions for reaching audiences.

For example, In-Feed from CodeFuel is an advertising solution that looks at user intent signals to determine the placement of native ads. Using CodeFuel’s proprietary technology, it evaluates the data to deliver the right ad for that particular user at that particular time.

In-Feed looks at a large wealth of data to understand just what the user really wants and needs.

The goal is to get beyond simple queries and to make more intuitive decisions about what the user wants. By matching more relevant content with users, advertisers will get more bang for their buck in terms of both exposure and sales.

More Individuated Frameworks

Brands are rejecting a one-size-fits-all approach to big data, including in the software architecture and tools that they use.

The rise of tools like In-Feed illustrates this well. Advertisers are more focused on how to use big data to reach individual customers, rather than audiences as a whole. They want tools that will help them interpret the data on an individual level.

Advertisers also want flexibility in their data frameworks. They want tools that will fit all their needs, whether they are creating intent based ad campaigns or are trying to assess the market landscape as a whole.

Continued Internet of Things

The Internet of Things is driving big data right now, and it will continue to grow in 2017 and contribute to our enhanced knowledge of the marketplace and its individual users.

We are seeing the rise in popularity of more personal products such as Google Home, virtual reality headsets, and fitness trackers. Each of these can collect different information about users, and each has the ability to connect to other devices and sync data in different ways.

Eventually, marketers predict the convergence of all this data in a central location for the convenience of users and the exploitation by brands. Not only will people be able to log into a single cloud application to access everything from their health profile to their shopping history, but brands will (potentially) be able to access the same information to learn more about these users and what they want and need.

We won’t reach that goal in 2017, but we will see the continued Internet of Things to move toward that goal.

What big data shows marketers is that they need to think beyond traditional strategies for learning about consumers and connecting with them. The sea of data that we now have available makes it both easier and harder to learn about consumers. There is much more information to get a clearer picture of our consumers, but it is harder to know what to do with that information.

Take advantage of the advanced technology now available to interpret and apply the data, such as In-Feed from CodeFuel. Adopt marketing strategies that are focused on the individual, rather than your larger audience profile. You’ll get better results, and you’ll improve your marketing team’s efficiency.

Marketing Trends for 2017 Big Data