What is Big Data? By definition, Big Data is “the analysis of large amounts of data which can be analyzed via specialized software.” This definition does not leave much room for interpretation; therefore, it is extremely important for marketers to gain an understanding of what this new tool can do for marketing.
Big Data is basically the marketing strategy which focuses on using large sets of unstructured and structured data to fuel online marketing campaigns. These campaigns are made possible through real-time analysis of collected data. Companies who are already using big data tools and machine learning within their marketing plans generally make more profits, as opposed to companies who haven’t. With an entire business able to gather and analyze massive amounts of user data, any marketer can realize significant benefits.
To utilize Big Data effectively, a highly structured data collection process must take place. Without a well thought out plan for collecting this valuable data, you and your marketing team will likely miss some of the best opportunities available to you. Without an understanding of what is best for your market, you will spend your time doing what is not beneficial to you, instead of focusing on what is best for you and your company.
To effectively collect and analyze large amounts of user data, you must have access to the Internet at all times. Without access to the Internet, you will be limited to collecting information using offline methods such as mailing lists or advertisements in magazines. You will also miss out on one of the most effective ways to monitor your marketing campaigns; namely, with predictive analytics. Predictive analytics targets current trends, such as seasonal peaks and lulls, in order to provide a comprehensive analysis of what is currently working for your business. When used along with the proper data collection processes, predictive analytics provides a near perfect picture of what is working for your business. This allows you to adjust your marketing campaigns, if necessary, to better fit with what is currently working.
One of the primary benefits of using data analytics is that it is a highly effective method of identifying what is working for your business. By taking full advantage of the predictive capabilities of data analytics, a data scientist can take small samples of your marketing efforts and look for patterns and anomalies that may be hiding in the data. Once the anomalies are identified, a more detailed analysis can be performed. Once you have a better understanding of your marketing and your customers, you can fine tune your business model to better support your goals.
A large amount of the success of many marketing initiatives result from the integration of large amounts of user data. However, there is a limit to the usefulness of this approach and it is important for data science professionals to remain cognizant of the limitations inherent in this powerful marketing tool. The main problem is that users will typically only provide with response time information and this may not provide insight into the true user value. More specifically, a user data set can only accurately reveal the performance of a single user over a short period of time and if the user changes their behavior pattern, the usefulness of the data set decreases significantly.
Data mining is the process of extracting value from large consolidated databases. Unlike the traditional database mining, structured data enables marketers to drill down through large unstructured databases to provide the information needed to support strategic marketing decisions. It is important to make the right decision at the right time in order to gain maximum benefits and minimize potential losses. While the right time is relative, it is also relative to the amount of effort and resources that can be committed to the task. If the right time is chosen, structured databases can provide a valuable resource for future marketing initiatives and can even generate a return on investment for the company.
In short, the large amounts of information can often provide better insights than even the most detailed structured data analysis. This makes structured data analysis less necessary and more beneficial for many companies looking to improve their overall marketing efforts. This means companies can focus their efforts on gathering as much relevant data as possible, in the shortest amount of time while maximizing the amount of insights from the effort.