It has become a truism that data is the oil of the 21st century. In the course of advancing digitization, more and more data are being generated: on the one hand by the online behavior of consumers, on the other by products increasingly equipped with sensors (Internet of Things). But what exactly is meant by Big Data and how can the vast amount of data be used in marketing?
Data has arrived in marketing, but is not yet part of everyday practice in the marketing departments of all companies. Most of them already have access to a great variety of data, including their own customer data, data generated via various communication channels such as websites or social media channels, second- and third-party data, and product usage data (Internet of Things).
Many companies already use marketing automation software to analyze customer behavior in real-time and deliver relevant content to (potential) customers on the basis of their analyzes. Customers who have registered for a brand's newsletter, for example, and whose online behavior (clicks) indicates that they are interested in a particular product category automatically receive corresponding offers via newsletters or display advertising.
The benefit speaks for itself: the incoming data enable a 360° view of the customer. This enables more precise segmentation and predictions of future customer behavior. Marketing hence becomes much more targeted and sales will increase.
The use of data is now a matter of course in marketing. Many companies, however, only scratch the surface of what Big Data can really do for their marketing. Big Data does not just mean data amounts as such. There are other aspects that make Data really "big".
What is Big Data?
The consumer has become an incessant data generator through the use of digital technologies. This includes structured (master data, transaction data etc.) as well as increasingly unstructured data (content in social media, forums, pictures, videos, etc.). There are three dimensions that make data Big Data, the so-called three Vs: volume, velocity, and variety. Big Data is therefore an enormous amount of data collected and analyzed in real time. This data comes from a large number of sources and has different formats (structured vs. unstructured).
In addition, two other factors play a significant role when it comes to using Big Data profitably: validity and value. This applies to the quality of the data records and whether these can create a value for the company and its marketing activities.
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A successful Big Data strategy requires more than technology
"Traditional" software is not able to analyze Big Data. Therefore, companies must create a platform that allows them to store and analyze data coming from different sources (variety) in large quantities (volume) in real-time (velocity).
In addition to this technological solution, which is provided by various suppliers, the organizational structure is also important. Big Data needs employees who know how to mine valuable information and ultimately translate it into appropriate strategies. Moreover, an agile organizational structure that makes it possible to implement new data-based strategies is required as well. It is ultimately useless to know where an increased demand for a product or service is to be expected if a business lacks the ability to act on this insight.
The Benefits of Big Data
According to the Big Data Report of the University of Reutlingen, businesses pursue a wide range of interests with Big Data, including the analysis of customer needs, improving customer satisfaction, improving customer loyalty or developing new services. It is therefore clear that Big Data can be used to address customer needs in a targeted manner, while at the same time developing new products and services based on data-based insights. Put simply, it is about gaining competitive advantages.
Never have there been more opportunities to gain new insights. Sooner or later, Big Data Consumer Analytics will replace methods of traditional market research, such as customer surveys, as they are both time-consuming and time-delayed and hence deliver less comprehensive insights.
For a long time, only large companies had the means to profit from the flood of data of the 21st century. An early example of the successful use of Big Data Consumer Analytics came in 2012: using comprehensive data analysis, Target knew whether a consumer is pregnant – oftentimes before they had the chance to tell their family. Using their insights, the company send out highly targeted offers to the pregnant women. This example caused quite the stir back then, but has now almost been forgotten. One of the reasons for this is the fact that such examples of forward-looking marketing are now becoming more commonplace.
The already mentioned Big Data Report shows that a rising number of companies have started to look into Big Data and have launched the first projects. The time to act is now.
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