The Most Successful Companies Today Are Data-Driven

Enterprise Data Science

As a data nerd and product marketer, I never cease to be amazed by what data science can reveal about people’s preferences, moods, and behavior. These applications can range from the amusing to potentially life-saving. From its analysis of online interactions between couples, Facebook Data Science can predict with astounding accuracy the likelihood of budding relationships and break ups. Using Twitter data, researchers at Northeastern University developed a model to accurately predict flu outbreaks up to six weeks in advance.

Data analytics is being used by more and more companies to allow them to make better decisions, develop new products and services, and verify or refute existing theories or models. According to McKinsey research, “organizations that leverage customer behavioral insights outperform peers by 85 percent in sales growth and more than 25 percent in gross margin.” Perhaps then it is no surprise that some of the most innovative products, services, processes, and solutions were developed by companies that successfully leveraged and applied the customer insights that came from big data. The names of companies who have outperformed their peers through data are now household names.

With its unrivaled database containing the shopping and purchasing behavior of 244 million customers, Amazon used predictive analytics to build personalized recommender systems, book recommendations, one-click ordering, and anticipatory shipping models to increase customer satisfaction and loyalty. Guided by its mission statement to become “Earth’s Most Customer-Centric Company,” Amazon is currently one of today’s most admired companies (in addition to enjoying an impressive $7.4 billion free cash flow as of December 2017).

Most people go about their day using Google’s search engine, email, and its Android operating system on their smartphones without a second thought. But as the saying goes, “if the service is free, you are the product.” All information that goes into those free services are eventually integrated into Google AdWords, Google’s online advertising service that has an ingenious business model using keywords, targeted advertising, a unique bidding model, and paid-per-click. Google AdWords is ultimately responsible for over 90% of Google’s staggering $89.5 billion revenue.

Netflix became the biggest streaming service in the United States using data analytics that combed through subscribers’ viewing habits, gathered valuable insights, and produced heavily personalized content. One successful hit that emerged was the political thriller House of Cards. To this day, 75% of Netflix’s viewer activity is still driven by its recommendation algorithm, which is estimated to save the company over $1 billion every year.

Amazon, Google, and Netflix may all have different business models but all three of these tech titans built their vast empires with a core focus on customer behavior data and analytics. Clayton Christensen, author of the best-selling classic The Innovator’s Dilemma, has taken pains to point out that customers aren’t really interested in products or services themselves but in what they do, specifically “jobs to be done.” Christensen further elaborates:

Identifying and understanding the job to be done are only the first steps in creating products that customers want—especially ones they will pay premium prices for. It’s also essential to create the right set of experiences for the purchase and use of the product and then integrate those experiences into a company’s processes.

For example, when someone buys Netflix subscription, he or she is not just buying TV shows and movies. That person is “hiring” Netflix to provide affordable and convenient entertainment. Examined in this context, Netflix is not competing not only with other streaming services like Hulu or Amazon Prime Instant Video, it is competing with “everything you do to relax” from listening to music or reading a book.

Successful companies such as Netflix know that they have go beyond knowing “who” their customers are. Specifically, they rely on data analytics as revealed through their customers’ behaviors to obtain a more accurate picture of what they really want and need, and how and when to best deliver it to them. The key takeaway for marketers is that they should not be segmenting their customers by demographics or personas, but instead be focusing on motivations, context, and triggers.

Data-driven companies like Amazon, Google, and Netflix are laying the groundwork for the future and various industries are feeling their disruptive effects. Industries unable or too slow to apply customer-centric, behavioral data-driven strategies in their business models will be at greater risk of obsolescence.

In today’s economy, companies are constantly reinventing themselves through customer-centricity, personalization, and customer experience. Data-driven analytics and quantitative insights are the must-have tools.

Another version of this article was originally published on the Abraxas Technology company blog. Read the original article here.


Aaron Tao is a graduate of the MSTC Class of 2017. He is currently a Product Manager with Abraxas Technology, a data analytics startup devoted to serving the out-of-home (OOH) advertising industry.

Follow him on Twitter here.

Leave a Reply

Your email address will not be published. Required fields are marked *