Understanding Customer Behavior With Big Data Analysis: An Overview
It is a common understanding that big data analysis is one of the hottest topics for researchers and industries today. Big data refers to the large volumes of data, which can be both structured and unstructured. Likewise, they are most commonly characterized by the 5 Vs.
Understanding the volume of big data is crucial for anyone who wants to take advantage of big data analysis. Big data systems deal with terabytes(TB) units and above and are out of the range of most personal computers.
Understanding the rate at which the data is being generated is also a crucial part of big data analysis. Sometimes, a low volume of data with perfect timing can provide a greater advantage over a large volume.
Anyone who has a basic understanding of big data analysis knows that not all data are the same. Today, smart sensors and processors can be embedded in any type of application. This is due to the fact that they have exponentially grown powerful while simultaneously lowering their size. Businesses have to find out which type of data can provide the most fruitful insights.
Veracity is one of the key factors that big data analysis sits upon. It refers to the quality and accuracy of the data obtained and whether or not they can provide value.
The value that the obtained data offers is the final piece of the puzzle. If your data cannot provide valuable information for your business, it is not worth employing such complex systems at their high cost.
Why is Data Getting Big?
In less than two decades, the Internet has become one of the most important human inventions. Similarly, it has been an inseparable part of human lives, and the convenience it has caused is immeasurable. Therefore, it is only common that there will be unfathomable amounts of data on this platform.
Some of the reasons why such enormous amounts of data are being generated every day are:
- Most of the communication and interaction between people happens on the Internet today.
- The number of people who use e-commerce has grown massively in the last decade.
- The use of the Internet of Things (IoT) in many industries and applications has given an enormous volume of sensor-generated data.
- Social media sites, streaming sites like Netflix and Amazon Prime, and e-commerce sites can record the finest details involving customer interactions.
- Many technologies and applications that remained inside labs and private spaces have been released for open-source research.
Due to the above-mentioned reasons, systems that store and process such data volumes have become crucial for businesses and governments.
Big Data in Customer Behavior Analysis
Customer behaviour refers to the process of understanding your customers through data and using this information to make business decisions. You can understand and segment your market, predict future customer needs, develop new products, and improve existing products. Today, there are millions of analytics tools and platforms that you can embed into your websites and IT infrastructure.
Similarly, customer experience can be a point of difference between you and your fierce competitors. The nature of the new buying population prefers brand relationships and experience over price and products. Therefore, this is vital for customer acquisition as well as retainment.
The following are some of the ways how big data analytics could grow your business and your profits by understanding customer behaviour.
Customer Acquisition and Retention
Customer acquisition and retention are some of the toughest jobs for businesses today. Since products and prices do not have as much differentiation power as they used to, companies have to search for new ways. Likewise, it is very easy for customers to switch from one brand to another because of the available options. Therefore, it is up to the brands to provide quality products and services and maintain meaningful relationships. The prospect of big data analysis, in this case, is massive. Understanding customer behaviour will help you design products and services that best suit their needs. Furthermore, you can design loyalty programs, discounts, and giveaways to support your goal of retainment. Moreover, you can capture your future customers before they reach buying capacity. For example, Airlines can identify frequent-flying future customers like students in business schools and reward them with loyalty programs.
Prediction of Customer Needs
Prediction of customer needs is one of the most important applications of big data analysis for businesses. Since buying and selling over the internet has exponentially increased all over the world, failing to capitalize on this means you will get behind. E-commerce sites have analytics tools that can record customer buying behaviour and predict their future needs. We have already seen product recommendations that pop up almost instantly after product viewing or buying. Furthermore, you can also use predictive analysis to provide a tailored experience for your customers.
Understanding Reviews and Feedbacks
Collecting reviews and feedbacks for your products and services has never been easier. You can get them through your websites or different social media handles. Since reviews are public and can be seen by anyone, it is important that you address your shortcomings instantly. Furthermore, you must understand that reviews affect buying decisions. If your product has bad reviews, there is a high chance that new viewers will instantly avoid it. The use of big data analysis is vital to understand what people are saying and writing. For example, text analysis systems can derive sentiments of the people from what they have written. Similarly, you can understand the keywords in the bad reviews which will tell you what to improve upon.
Understanding Your Competitors
For any business, staying ahead in the competition requires an understanding of competitors. Due to the rise of e-commerce, it is very easy to understand your competitors’ pricing and programs. Likewise, you can also look for reviews and feedback on their products and services. This will help you understand what you are lacking and what you should avoid. Furthermore, you can develop your own new strategies and programs to attract customers from your competitors.
Improve Indicators Measurement
Big data will improve upon the inaccuracies and biases in traditional marketing and indicators measurement. For example, the Net Promoter Score (NPS) is a measure of how likely customers are to recommend your products and services in their circles. However, this is error-prone as not all customers will provide real answers. In contrast, big data analysis will take into account real interactions and purchases, which will derive more accurate indicators.
In this blog, we have learned how big data analysis is key to understanding customer behaviour. Similarly, we have also discussed how you can use the power of data to acquire customers, improve their experience, design new products, and understand your competitors. Furthermore, employing such systems has been very easy as there are a number of cloud-based providers. You need not invest huge amounts of money in sophisticated hardware.
Technology news must be a top priority if you want to learn about the market’s current state and its possible evolution. As a highly reputed source of technology-related news, we at Top World Business make sure that you stay updated on the latest trends and receive the correct information. In this fast-changing world, we make sure that you won’t miss a high potential investment.