How Brands Are Using Big Data to Grow Sales

Using Big Data to Grow Sales

In the last 2 years, 90% of the world’s data has been created, according to IBM. Over 2.5 quintillion bytes of data are created every day, according to the “Global Big Data Analytics Market Size, Market Share, Application Analysis, Regional Outlook, Growth Trends, Key Players, Competitive Strategies and Forecasts, 2019 to 2027” report. 500 terabytes of data are generated every day on Facebook alone and over 300 hours of video are shared every minute on YouTube. Data is generated by every click, swipe, search, share, and stream. Businesses are taking notice of the massive amounts of data that are available and are putting their money behind using it with more than $180 billion spent on big data analytics every year.

To compete in today’s global market and to generate more sales, you need to be able to tap into this data. Doing so can provide you with powerful insights about your customers. A BARC research report shows that businesses that use big data realized a profit increase of 8% and a 10% reduction in their overall costs. Thanks to the latest advancements in technology, even smaller companies can use big data to grow their sales. Here are a number of ways you can do just that, along with how some companies have been able to effective use these strategies.

Most Popular Ways to Effectively Use Big Data

With easy access to public records, analytical tools, and customer behavior, some of the most popular ways that brands are using big data include to:

Influence the Customers’ Behavior

Many companies use big data to attract customers and to get them to buy something. Brands can use big data to pinpoint customers’ behavioral patterns, which they can then use to help them through the sales funnel.

Some of the data that is collected for this purpose include:

  • Keystrokes
  • How long a customer stays on your page
  • What a customer clicks on
  • What led the customer to your page
  • How your customer moves the mouse

This information helps predict the customer’s behavior with greater accuracy. Companies can take advantage of this information by delivering what the customer wants. For example, a company can predict when a potential customer is about to close a window but make a curated pop-up appear, such as a discounted offer to entice them to complete the sale.

Predict Products that Customers Will Like

One of the most effective methods of using big data is to predict products and services that the customer will like, based on their behavior and past buying history. Some of the world’s biggest brands use this strategy to provide a better customer experience and to boost sales.

Google has based its entire business model around this concept. By using big data, including previous selections and the sites you visited and combining this information with special algorithms, the site generates the most relevant results to match your queries.

This process works through machine learning, in which computers learn behavior patterns based off of data and then apply this knowledge to predict a customer’s action, such as subscribing for a service.

Amazon has also successfully integrated this strategy into its sales model. The company gathers data about:

  • When customers make purchases
  • Customers’ rating for their purchases
  • What customers who share similar buying habits are purchasing

The retail giant then uses this information to provide recommendations of certain products to the customer. These sometimes appear in the “frequently bought together” feature on Amazon, such as showing customers who bought tvs available tv mounts. This simple maneuver can boost sales tremendously.

Another prime example of using big data to predict behavior is through Netflix’s recommendations that appear on the app’s home screen. The company collects data such as the shows watched, when they were watched, whether they were binge watched, and what shows that people with similar interests enjoyed to make recommendations. Netflix estimates that its unique algorithms produce $1 billion a year in value from customer retention, which is approximately 93% of its customer base.

Starbucks also uses this strategy by having customers download an app and make purchases through it. This allows the coffee mega giant to learn about the buying habits of its customers and make recommendations to customers about products and to adapt its marketing campaign to customers.

You can use this same type of system to make predictions for your customers, deliver curated recommendations, and increase sales. Algorithms are often the foundation of this predictive strategy.

Optimize Pricing Strategy

Another way that you can use big data is to change your pricing structure based on customer behavior. The best example of this practice is how airlines change the prices of plane tickets based on customer behavior. For example, if a person checks plane tickets multiple times, this is usually an indicator that they want the ticket and will be willing to pay more money for them. Amazon uses a similar strategy, changing their prices up to 2.5 million times each day.

Price strategy optimization may take various factors into consideration such as:

  • Shopping patterns
  • The relative rarity of the product
  • The prices offered by competitors
  • Local and global economic situations
  • Weather
  • Reservation behavior
  • Cancellation patterns

Some brands, such as Starwood hotels even consider whether a nearby show at the Madison Square Garden is playing to adapt its price.

Improve Products Based on Customer Feedback

Big data can also help brands obtain information to help them innovate their products. Big brands listen to their customer feedback and redevelop their products to meet the desires of their existing customers. Companies can do this by carefully tracking their products, customer feedback, and competitor behaviors.

Companies can use big data to then create a targeted action plan. For example, the Amazon Fresh and Whole Foods initiative harnessed big data, allowing Amazon to move into the large grocery retail market. It used the massive amount of data it culled over the years to develop the necessary expertise to create and achieve greater value. Amazon used its existing supply chain to offer this new option to their existing customers.


As you can see, big data has a big impact on the marketing world and is here to stay. Thanks to the massive amounts of data that are readily available through public records, apps, website analytics, and data you can personally cull from your customers, even small businesses can tap into this data to learn more about their customer and create a more personalized experience.

About the Author


Ben Hartwig is a Web Operations Executive at InfoTracer who takes a wide view from the whole system. He authors guides on entire security posture, both physical and cyber. Enjoys sharing the best practices and does it the right way!

The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of The World Financial Review.