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Grow Your Business Technology

How Businesses Are Collecting Your Data (And What They're Doing With It)

Customer data pie chart
Credit: Arthimedes/Shutterstock

The modern business environment is awash in data. As technologies like the internet of things and artificial intelligence continue to develop, companies have begun capturing and analyzing more and more data.

Few things are immune to the explosive demand for more information. This includes the consumer. Companies capture, store, analyze and react to massive amounts of data on their consumer base every day. Everything from consumer behavior to predictive analytics comes into play, and some companies have even turned their customers' digital footprint into a revenue stream.

Here's a look at some of the ways companies capture their customers' data, what exactly they do with that information, and how you can use the same techniques to improve your business.

Companies capture data in many ways from many sources. Some processes are highly technical in nature, while others are more deductive (although these methods often employ sophisticated software).

The bottom line, though, is that companies are using a cornucopia of sources to capture and process customer data on metrics, from demographic data to behavioral data, said Liam Hanham, director of data science at Elicit.

"In short, customer data can be collected in three ways," Hanham said. "By directly asking customers, by indirectly tracking customers, and by appending other sources of customer data to your own. A robust business strategy needs all three."

Businesses are adept at pulling in data from nearly every nook and cranny. The most obvious places are from consumer activity on their websites and social media pages, but there are some more interesting methods at work as well. Here are just a few of the ways businesses vacuum up consumer data for analysis.

One example is location-based advertising, which utilizes an internet-connected device's IP address (and the other devices it interacts with) to build a personalized data profile. This information is then used to target users' devices with hyperpersonalized, relevant advertising.

Companies will also dig deep into their own customer service records to see how customers have interacted with their sales and support departments in the past. Here, they are incorporating direct feedback about what worked and what didn't, what a customer liked and disliked, except on a grand scale.

Of course, these are just a couple ways companies collect data. They can also purchase data from or sell it to third-party sources, so once captured, this information is regularly changing hands in a data marketplace of its own.

Of course, capturing large amounts of data creates the problem of how to sort through and analyze all that data. No human can reasonably sit down and read through line after line of customer data all day long, and even if they could, they probably wouldn't make much of a dent. Luckily, computers are much better at this type of work than humans, and they can operate 24/7/365 without taking a break.

As machine learning algorithms and other forms of AI proliferate and improve, data analytics becomes an even more powerful field for breaking down the sea of data into manageable tidbits of actionable insights. Some AI programs will flag anomalies or offer recommendations to decision-makers within an organization based on the contextualized data.

Without programs like these, all the data capture in the world would be utterly useless.

There are several ways companies use the consumer data they collect and the insights they draw from that data. Chief among these uses are improving the customer experience, boosting the effectiveness of marketing campaigns and selling that consumer data to third parties as an additional revenue stream.

For many companies, consumer data offers a way to better understand and meet their customers' demands. By analyzing customer behavior, as well as vast troves of reviews and feedback, companies can nimbly modify their digital presence, goods or services to better suit the current marketplace.

And not only do companies use consumer data to improve consumer experiences as a whole, but they also use data to make decisions on an individualized level, said Brandon Chopp, digital manager for iHeartRaves.

"Our most important source of marketing intelligence comes from understanding customer data and using it to improve our website functionality," Chopp said. "Our team has improved the customer experience by creating customized promotions and special offers based on customer data. Since each customer is going to have their own individual preferences, personalization is key."

Contextualized data can help companies understand how consumers are engaging with and responding to their marketing campaigns, and adjust accordingly. This use case for consumer data is highly predictive, building an idea on what consumers will want from what they have already done. Like other aspects of consumer data analysis, marketing is becoming more about personalization as a result, said Brett Downes, SEO manager at Traffic Jam Media.

"Mapping users' journeys and personalizing their journey, not just through your website but further onto platforms like YouTube, LinkedIn, Facebook or on to any other website is now essential," Downes said. "Segmenting data effectively allows you to market to only the people you know are most likely to engage. These have opened up new opportunities in industries previously very hard to market to."

Companies that capture data also stand to profit from it. Data brokers, or companies that buy and sell information on customers, have risen as a new industry alongside big data. For businesses that are capturing large amounts of data, this represents an opportunity for a new stream of revenue.

For advertisers, having this information available for purchase is immensely valuable, so the demand for more and more data is ever increasing. That means the more disparate data sources data brokers can pull from to package more thorough data profiles, the more money they can make by selling this information to one another and advertisers.

Some businesses even use consumer data as a means of securing more sensitive information. For example, banking institutions will sometimes use voice recognition data to authorize a user to access their financial information or protect them for fraudulent attempts to steal their information.

These systems work by marrying data from a customer's interaction with a call center and machine learning algorithms that can identify and flag potentially fraudulent attempts to access a customer's account. This takes some of the guesswork and human error out of catching a con.

As data capture and analytics technologies become more sophisticated, companies will find new and more effective ways to collect and contextualize data on everything, including consumers. For businesses, doing so is essential to remaining competitive well into the future; failing to do so, on the other hand, is like running a race with your legs tied together. Insight is king, and insight in the modern business environment is gleaned from contextualized data.

Adam C. Uzialko

Adam received his Bachelor's degree in Political Science and Journalism & Media Studies at Rutgers University. He worked for a local newspaper and freelanced for several publications after graduating college. He can be reached by email, or follow him on Twitter.