Our previous articles discussed The Benefits of Business Intelligence and How to Become a Data-Driven Business: Dell Data Maturity Model. We decided to continue this theme for another week because we had a few people reach out to us and ask us the same question regarding becoming a data-driven business: Is the investment in time, equipment, and training really worth it?
It turns out that it is. According to a 2014 report by McKinsey, “Intensive users of customer analytics are 23 times more likely to clearly outperform their competitors in terms of new customer acquisition than non-intensive users, and nine times more likely to surpass them in customer loyalty. Our survey results also show that the likelihood of achieving above-average profitability is almost 19 times higher for customer-analytics champions as for laggards”.
Just in case that study isn’t enough to convince you, we’ve put together four inspiring success stories of companies who have made intelligent use of data in order to gain a competitive advantage.
1. Netflix
You’ve probably read numerous articles about Netflix’s clever use of data from user habits for their movie recommendation system. However, Netflix goes far beyond that in terms of harnessing the power of data.
Netflix executives have publicly stated that the success of their 2013 hit “House of Cards”, was a result of a series of critical decisions based on data analytics. Netflix algorithms showed that the series was likely to be popular with Netflix subscribers based on: the subject matter, the success of the original British television series among a similar demographic, and the appeal of Spacey and Fincher. According to New York Times, Netflix offered actor Kevin Spacey and director David Fincher contracts without even seeing a pilot.
To this day, Netflix continues to make use of data analytics when making programming decisions. This puts them at a tremendous advantage over competitors who relied on “gut feel”. Consequently, they are able to command the highest price and the largest market share in the streaming business.
2. Uber
Uber has made creative use of data analytics in solving perhaps their biggest problem– matching supply with demand. They have become largely successful because they simultaneously offer consumers the ability to quickly get an inexpensive ride while offering drivers the opportunity to make decent money and be their own boss. But this system will quickly break down if the app can’t efficiently match buyer and seller.
Consider a city divided into two parts connected by a bridge. At 5 pm, there are 10 Uber users on the east side needing a ride, but 10 Uber drivers are on the congested west side, unable to reach them due to traffic on the bridge. This situation leads to a poor experience. Drivers are unable to earn money and riders are frustrated by the unavailability of rides.
To address this issue, Uber has established an automated analytics system. The system gathers data on request volumes from different geographic locations and generates a “temperature map.” This map helps drivers identify areas where riders are more likely to be located. This will keep them from being on the wrong side of the bridge in the aforementioned example.
Additionally, Uber uses data to “secretly” keep tabs on their drivers. They can tell, for example, if their drivers are speeding or working for a competitor. This raises the question of whether data can and should be used for controversial purposes. However, that is a discussion for another time.
Despite its potential for somewhat nefarious purposes, it’s safe to say that Uber has made effective use of data that enables them to provide their drivers and riders with a positive experience.
3. Coca-Cola
Most people think that Coca-Cola is the world’s best selling soft drink because of their secret formula. But the reality is that the Coca-Cola company has become so successful because of several smart business practices. One of these practices is that they make very effective use of data.
They use data for a variety of decisions, including new product creation, supply chain management, and most importantly, marketing analytics.
Business leaders have always struggled with deciding where to spend their advertising dollars. Most famously, U.S. department store magnate John Wanamaker is alleged to have said “Half the money I spend on advertising is wasted, and the trouble is I don’t know which half.” This is quite scary for Coke, who spends around $4 Billion a year on advertising.
To maximize the effectiveness of their substantial budget, Coca-Cola utilizes a sophisticated AI system. This system analyzes consumer trends and behaviors across over 200 countries where they operate. According to a recent Harvard article, Coca-Cola monitors mentions or images of their products posted by consumers. They then tailor specific ads to these consumers based on their posts, significantly increasing the likelihood of engagement. Coca-Cola claims that ads targeted in this manner have a four times better likelihood of being clicked than non-targeted ads.
Furthermore, Coca-Cola has over 108 million Facebook fans, over 3.4 million Twitter followers, and over 2.8 million Instagram followers. They analyze data from these “fans” to gain insights into consumer trends and preferences. They then leverage this data for advertising and product development.
4. Google
Everyone knows that Google is perhaps the best example of successful data navigation in recent history. They can search through 50 billion web pages and pinpoint your desired subject in a fraction of a second. But they also apply a data-driven approach to other areas of their business, even Human Resources.
With data collection and analysis, Google can understand their workforce, manage people more effectively, and retain productive employees. For example, Google’s human analytics team recently conducted a study. They dug into performance reviews, feedback surveys, etc. to assess their employees’ feelings on Google’s what makes a good boss. The results were counterintuitive – for example, they discovered that technical expertise was the least important skill for engineering managers.
They also have applied data science to recruiting, performance reviews, and even employee well-being. Extending paid maternity leave from 12 to 18 weeks, for example, reduced their employees’ postpartum leave rates by 50%.
Conclusion
These four specific examples of how data-driven companies like Netflix, Uber, Coca-Cola, and Google have used their data to build a competitive edge should hopefully inspire you to revolutionize your own company. At CodeStringers, we have built up an expertise in AI, ML, and data science services in order to help our clients achieve this goal of becoming a data-driven business.