January 18, 2019 6 min read

Opinions expressed by Entrepreneur contributors are their own.

Modern-day marketing has changed drastically over the past decade. Back in the day, when companies wanted to tweak their advertising, they would have to sift through their sales data, click-throughs and general behavior of their audience.

Related: Here’s How Big Data is Changing The World

But big data has changed all that. It’s changed the way that businesses market to their customers, which in turn, helps companies increase their profits. According to a BARC research report, businesses surveyed that use big data saw a profit increase of 8 percent, and a 10 percent reduction in overall cost.

There are numerous ways you can use big data to adjust your business model for the better, especially as it pertains to advertising. Here are examples of how companies are using big data today, and how you yourself can use it to boost your sales.

Predict products that customers may want to purchase.

How often have you looked at your Amazon recommendations and thought, “Wow, I could really use that!” Chances are, that reaction happens fairly often considering that Amazon uses big data to figure out exactly the type of products you’ll want to buy in the future.

The retail giant — which hit a net worth of 1 trillion dollars late in 2018 — gives its customers insight as to what factors go into determining those recommended products. In this context, Amazon cites a variety of data points to figure out what its customers want. Those factors include:

• When customers make purchases
• How customers rate their purchases
• What customers with similar buying habits are purchasing

Obviously, the last factor is the most important one as pertains to big data. Amazon is able to correctly determine what kind of products you want to buy based on customers with buying habits similar to yours.

Similarly, you can use this kind of data to make predictions for your own customers. When you see a sales increase, you’ll start to notice trends. For example, Amazon noticed that people who buy TVs tend to also purchase a TV mount — which the retailer began to upsell in the hope that customers would buy them together.

Amazon “frequently bought together” example

Image credit: Amazon

Related: Big Data Combined With Machine Learning Helps Businesses Make Much Smarter Decisions

Get an edge against operational risks.

Back before the world was connected via technology, issues of fraud were few and far between. But now that so many of us are connected in one way or another, sometimes an entire business can be compromised in just a couple of keystrokes.

Operational risk is particularly high in financial institutes. Scammers are constantly trying to evolve schemes to take advantage of both people and companies. As big data has evolved, however, financial institutes have realized that they can use this information to stop scam artists in their tracks.

Banks, for instance, are now using big data to monitor their transactions on a “front-to-back” business line to help eliminate fraud at all levels. They look at information about who is sending/receiving money, how often those people engage in this behavior, where they live and how much money they are sending.

This type of technology can be helpful for any business, not just banks. As data is collected, trends emerge and anything that deviates from “business as usual” triggers a digital sticky note on that transaction. This makes it easy for companies to identify fraud when it occurs and to keep their operational risks at a minimum.

Use key data to influence the customer’s behavior.

Big data is absolutely vital for figuring out how to get customers to make important decisions when they land on your page. Companies are using this data to learn their customers’ behavioral patterns, and to help point them toward a sale or conversion.

Specifically, the data analyzes every single action a customer takes upon landing on your page. It can see the customer’s keystrokes and how he or she moves the mouse; it can predict the actions that will be taken next.

As a business owner, you can use this data to give your customers what they want when they want it. For instance, if you manage a marketing website and a customer comes to your website to read an article, big data can predict when this viewer is going to go up to the “X” to close out of the window. You can use this as an opportunity to make a curated pop-up appear, offering the customer more information by entering a personal email and joining your mailing list.

Here is how a sample exit pop-up looks to customers. Who doesn’t want 25 percent off their first purchase? Enticing, right?

Exit pop-up example 

Image credit: Banana Republic

It’s possible to combine this marketing technique with other strategies like the offer of a free ebook, gift or discount as the customer goes to leave. The benefits don’t stop there, though. You can use big data to predict when customers might leave empty carts on your storefront. If they already left the page but entered an email address, you can program the system to automatically send them reminders that they left a vacant shopping cart.

As more customers come to your website, you’ll start to learn their most common behaviors and plan ahead. Your marketing plan will flourish as you gather more data on what those customers want and need.

Over to you

These are three of the most common ways that companies are using big data every single day. Because technology is continuing to grow, big data is obviously here to stay. Statista predicts that the big data business world is going to be worth $77 billion by 2023.

Related: How Can Small Business Benefit From Big Data

Most people used to think that big data was only for big business. But, as time goes on, it is clear that this technology is for everyone. If you’re interested in pursuing big data in your small business, a little research can get you started, and before long you’ll be able to increase your revenue, boost your email lead list and expand your business in ways you never thought possible.