Big Data and the applications of its techniques and tools to businesses are a necessity for many companies. In this article, we will learn about the main applications of Big Data to digital marketing and how they can help us to better understand our clients and offer personalized strategies.
The real applications of Big Data
When we talk about Big Data and the applications that it can have to the business, we are referring to the set of technologies, processes, techniques, and tools for processing large amounts of data that we produce and manage in our company. The objective is to take advantage of the knowledge provided by the analysis of this data to improve the efficiency of processes and make decisions based on data.
Among the multiple fields of Big Data applications in the company, perhaps the most significant is marketing. In the new digital age, customers demand a highly personalized experience. In this case, Big Data represents the link between the need for companies to get to know their customers better and the large amount of data generated by the latter in their digital transactions, including:
• Interactions with marketing, sales, or customer service departments that are generally recorded in the company's CRM systems.
• Purchase transactions both online and offline.
• Interactions with the different digital interfaces of the company: website, social networks, mobile applications, chatbots, etc.
• Unstructured information generated in social networks, forums, search engines, about your person, interests, relationships, etc.
• Geolocation data, generated by mobile devices.
5 applications of big data in digital marketing
All this great set of information can be used by digital marketing with the aim of getting to know our potential customers better and reaching them in an easier, more efficient, and less costly way.
Next, we will see the five main applications of Big Data to digital marketing:
• Segment our clients: with Big Data, we can analyze large amounts of data in real-time and generate personalized profiles of our clients. This helps us to better understand our interactions with our company and purchase intentions.
• Implement personalized strategies: this knowledge allows us to reach a large number of potential customers interested in our products and services, with highly personalized marketing and communication strategies.
• Detect loss of clients: it also allows us to detect and prevent possible disinterest or abandonment in time.
• Improve decision-making: thanks to the profiles we have been able to build, we can make personalized strategic decisions in real-time.
• Planning and predicting: perhaps the greatest potential Big Data offers us is to be able to extract knowledge from the data to anticipate and plan future actions.
Big Data's successful applications in real companies
Every day, thousands of companies of all kinds implement Big Data with applications to their marketing strategies. In fact, some of the most relevant success stories come from companies in non-technology sectors.
• Amazon is one of the pioneers in using the purchase and navigation information of its users, in addition to interactions with its new voice assistant Alexa. Thanks to the collected data, Amazon is able to build a highly detailed user profile to provide personalized recommendations to its customers.
• In the same way, Spotify uses information about the consumption patterns of its users to offer personalized music recommendations. For this, a few years ago, it acquired the musical search engine The Echo Nest.
• Nike uses the data it collects from its customers to improve the design of its products. A year ago, it closed the purchase of data analysis company Zodiac; It also opened Nike by Melrose, its first store in which the products sold are decided based on the data generated by customers in the Nike, Nike Training, Nike + Run Club apps.
The challenges of Big Data and its applications to marketing
Although Big Data applications to marketing have innumerable advantages, it is still difficult for many companies to access them. The main challenges stem from the difficulty of choosing the correct information from the large amount available. In addition, the challenge of implementing data analytics that knows how to extract valuable and actionable information is added. Finally, the biggest challenge has to do with people and is that all levels of the company, including senior management, assume a culture based on data analysis. Companies should not just collect data; they should consult any top data science company to help them with their big data analytics.