How to Make Sense of Big Data That Everyone Talks About
In recent years, the increasing importance of big data has led to big expectations. Particularly with the introduction of the concept of Internet of Things (IoT), each object is linked to the internet and with the continuous increase in mobile and digital applications and services, data has been gathered at a surprising rate from various sources. When used and evaluated correctly, data has become a crucial competitive weapon, so in the technology world, data is frequently expressed as new gold or new oil. So far, the most referred reference to big data and objectively one of the best definitions has been made by Duke University Professor Dan Ariely: “Big data is like teenage sex. Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”
Indeed, while each and every company continues to aggregate customer data, few of them can use such data to improve customer relationships and create customer satisfaction. The truth is that data does not represent a value by itself; value is formed as a result of processing data to solve a unique problem or fulfill a need.
Big data needs to be systematically developed...
Big data has not been used enough to differentiate businesses and offer new and innovative value propositions till now. Rapid analysis and interpretation of data has become more and more important every day to create value and gain valuable information. In order to obtain meaningful and useful insight from big data, businesses need to develop systematic processes based on their business processes. Although the methods and channels can be differentiated, it is quite critical to follow these three steps for big data processing:
1. Determine the channels through which the data will be collected and stored
2. Make sense of the data based on customer behaviors and create actionable insights via special algorithms and analyzes
3. Provide easy-to-understand and useful reporting for business needs
Big data is important for customer communication...
Appropriate use of data is also very important in order to find out strategies that will increase revenues by understanding and analyzing the customers or that will provide new customer acquisition methods. So, an additional step can be added to the above methodology: Interaction. Through interaction, companies can communicate with the customers by transmitting personalized messages in the right place, and at the right time.
Hello to predictive analysis...
In order to increase revenues, it is also necessary to be able to predict customer expectations, behaviors and reactions. To do this, data must be parsed, examined in a personalized manner, and processed as jeweler's rigor. By analyzing the past behavior of a customer, it is possible to understand how to react in similar processes, which is called predictive analysis. It is necessary to analyze the data as it is in the series of Fibonacci ((1, 2, 3, 5, 8, 13, 21, ...) each number is the sum of the two preceding numbers): analyzing previous steps to predict approximately exactly what the next step will be.
Big data improves customer experience...
The omni-channel strategy is becoming increasingly important, and companies are trying to move into multi-channel structures to communicate with customers and maintain a balance between the traditional and digital channels.This balance of big data is very useful in order to guide organizations in terms of reaching the customer with the preferred channel. It is also necessary to use more of the big data to improve the inter-channel customer experience, hence gain a competitive advantage.
More data is generated each year, and companies in almost all sectors struggle to ensure the reliability and quality of this data. The right use of data allows organizations to address their business challenges more effectively, while also providing invaluable guidance for managing and interacting with their customers.
Written by guest blogger, Ergi Sener