MTV Katsomo is a Finnish, totally web-based concept, offering for example sports broadcasts to its customers, and connected articles on the MTV website. With the help of Big Data, MTV Katsomo is seeking added value to its customers.
Understanding the customer behavior online is one of the cornerstones of a digital business, in order to improve customer care and develop the business. Regarding the Total Sports package the challenge of using this information has been the lack of a Big Data environment, and thus the slow processing of large data masses.
Online success depends on the right offering, just like in traditional stores. The variety of sports is broad in the MTV Total Sport package. However, from a customer loyalty perspective, it is vital to understand both the needs of different sport fans and they cross watch broadcasts, especially regarding seasonal sports in order to avoid churn after the season.
Therefore, one of the main objectives of the MTV Total Sport’s big data project was to grow customer loyalty using the right content and an optimal offering of different sports.
Customer analysis and predictive models
A better customer understanding was gained using different customer models, which revealed key aspects, such as the length of the customer relationships, customer retention, sports interests, seasonal variations and user activity. After the basic analysis a more challenging and more interesting phase was entered; building the predictive models.
The models are used to predict probabilities in, for example, viewers’ activity per sport, orders placed by existing customers, and customer retention. The results can be used for building more customer-serving content and thus longer customer relationships.
The Big Data project of the MTV Total Sports package also resulted in an extra benefit, as the data storage structure was rationalized: all data, which did not include significant information for building better customer relationships, was eliminated, and 80 fields turned into only 10 fields. As a result, the heavy data collection phase was significantly simplified.
Why should leaders be interested in Big Data?
"The exercise was an eye opener. It helped understand and identify dependencies between the sports content when our customers are choosing the Total Sports package. Based on the results we now know what kinds of customers we need to target with a sharper message, regarding content as well as timing”.
Ilkka Pornan, Head of online analytics at MTV3 Internetanalytics
Big data – or unstructured data – changes business models and opens up many opportunities to improve customer service. Even very scattered database structures, comprising dozens of exabytes, can be systematized and analyzed to serve the needs of the business.
Big Data means collecting, warehousing and analyzing almost unthinkably large and unstructured data masses with the help of technology. The term encompasses, except for large data masses, also fast-cycled data and its complexity. The fast development of technology and analytics has also made it possible to use Big Data where it was not possible earlier, due to technical limitations or the huge price tag of the process.
The information drawn from data is becoming a necessity for competitive advantage. Organizations led by information and companies using information to add value to the customer interface are the winners in the digital business.
In retail, for example, the Big Data collected from online stores can be used to develop the physical store, and vice versa. This means that the customer relationship can be crystallized in an omni-channel store concept:
- What information is the customer seeking online?
- Which products are the customer looking at online but for some reason not purchasing?
- How does the customer’s online behavior differ from the purchases in a traditional store in terms of product groups?
- How has the customer been using social media and interacted with our call center?
With the help of Big Data it is possible to achieve a significant 360-degree customer view and use it as a foundation for developing the business.
Ville Laitinen is an experienced analyst in the retail business. In his current role as CIO for Houston Analytics [P1] he is helping organizations utilize big data for building better predictive models.
Houston Analytics is an analytics company started by experts on data-driven leadership. By linking data to business decision-making Houston Analytics is guiding its customers to market leaderships in their industries.