08 Nov Examples of How Leading Brands Used Data Science in Their Marketing Mix

As we mentioned earlier in the article, many of the world’s leading corporations have already embraced the process of digital marketing with data science. As you will see from this list, they have all been huge successes. These are some excellent data science advertising examples that can assist businesses in making better decisions. Here are a few examples of businesses that have integrated data science online marketing into their business strategy:

• Facebook

In its marketing strategies, Facebook employs a multifaceted data science method. They have their own marketing strategies that they use across multiple platforms. However, they have also been providing insights and marketing tools to the many businesses that advertise on their platform. These clients are important to Facebook, which is why they have ML models that can measure how effective these business owners’ marketing campaigns are and how they can be improved. Their team creates new insights and tools to better serve their clients and bring in more revenue for the company.

• Spotify

Spotify is home to a massive amount of music from all over the world, which can be difficult to navigate when looking for new music to listen to. Finding good music by hand can be time-consuming. That is why Spotify has some really good algorithms in their app that recommend new music to the listener based on their listening habits and other people with similar music tastes. They have automatically generated playlists for songs and podcasts that people will find interesting. Listeners can even keep track of the week’s new releases and top charts.

• Netflix

Netflix, like Spotify, is a streaming platform for movies and web series. They are a hugely successful platform not only because of their content, but also because of how it is presented and marketed. They provide personalised recommendations based on each user’s viewing habits as well as those with similar tastes. This encourages millions of people to return to their platform for more.

• Google

Google is used as a marketing platform by many small, medium, and large businesses. Smaller businesses may be unable to hire a professional data scientist and must instead rely on Google to provide the services. Google ensures that data analytics is simple for their customers to understand. They give business owners tools to help them create captivating marketing campaigns. On the other hand, Google’s marketing team ensures that these clients’ ads reach the people who are most likely to buy from them.

Data-Driven Advertising According to Coca-Cola

Coca-Cola is the world’s largest beverage corporation, with over 500 soft drink brands distributed in more than 180 countries. Due to the scale of its operations, Coca-Cola generates a significant amount of data across its value chain, including sourcing, production, distribution, sales, and consumer feedback. Throughout the years, the corporation has used Big Data to drive corporate strategic decisions.

Coca-Cola has millions of social media followers and a variety of other methods for gathering customer data. Coca-Cola is known to have spent a significant amount of money on artificial intelligence (AI) research and development to ensure that it extracts every ounce of insight possible from the data it collects.

The data gathered reveals who is drinking their products, where their customers are, and what circumstances cause them to comment on their brand. When images of its products or those of competitors are posted on the internet, the corporation uses AI-driven image recognition technology to detect them and algorithms to determine the best way to display advertisements to them. According to the firm, ads targeted in this manner are four times more likely to be clicked on than those targeted in other ways.

EasyJet Advertising Campaign

EasyJet’s 20th anniversary celebrations began with a data-driven campaign. Based on each customer’s travel history, the company created personalised stories. Customers’ personal information, such as when they first flew with the airlines, was used to forecast where they would fly next. The campaign relied heavily on personalised emails, with content based on 28 key data points and other requirements. As a result, the open rates for this campaign were 100 percent higher than for their regular newsletters, with a 25 percent higher click-through rate.