Why Big Data Analytics is pertinent to ultimate business sucess
There are many tools available to help keep businesses ahead of their competition, but perhaps none are as valuable as those that provide data analysis. Analyzing public data can enable a business to preempt trends and understand customers’ needs and desires. This last can be particularly valuable to technology companies whose products are in high demand by consumers.
Auto insurance companies are particularly interested in using big data. Actuaries have always tried to store data on customers to understand their risk profile, but their data has been limited to driving histories. In the future, big data may help them keep track of other variables more easily, such as monitoring EZ pass records to see which areas drivers spend the most time.
Defining data analysis
Data analysis is a process that reviews information collected from users’ visits to websites, survey responses and many other types of information-gathering techniques to inform a wide variety of decision-making processes and for conclusions to be reached. With so much data available and with so much of it being hugely complex, so much so that it has been given its own name – Big Data, it is necessary that dedicated computer programs and online tools perform this process.
Different kinds of data
Just as there are different types of data, there are a wide variety of data tools and platforms available. Household names, such as Hewlett Packard and Microsoft, use Big Data analytic platforms developed by Apache Hadoop, while others use tools developed by Cloudera. Some use structured data, which is any data that has a home in a fixed field within a file and is often found in relational databases, such as CRMs, and spreadsheets. Others use unstructured data, which is data that defies such classification, such as graphics, photos, PDFs and blog posts. Then there is mobile data, which is data collected from mobile devices, and online data, information collected from Internet users.
How does data analysis help technology businesses?
Data capture and analysis using these tools can help a technology business in a number of ways. The primary use is for growth. Data analysis can indicate which parts of a business’s offerings are the most successful with consumers or users, and which the least, and therefore which demonstrate the most potential in terms of sales and those that are a drain on the company’s resources that may inhibit expansion. A good example of how data analysis can aid a company’s growth is provided by Keith J Krach, who as the Chairman and CEO of DocuSign, has made it possible for users to transact contract-based business wherever they are in the world and at any time. His involvement in this digital development enabled the company Ariba to double in size and thereby fulfill consumer demand for the service.
One of the major advantages to carrying out data analysis is how the conclusions reached can be used to develop marketing campaigns that will increase sales and help grow the business. Data analysis can be used to understand the needs and wants of a specific demographic that the technology business is trying to attract, so that they can tailor their marketing to appeal directly to this group by providing solutions to their specific problems. This approach makes a marketing campaign far more cost-effective by not attempting to appeal to people that do not intend to buy their product, and can influence future produce development.
Data analysis can also lead to greater personalization opportunities for technological items. For example, communications between company and consumer can be personalized, so that a marketing email is addressed to a named person rather than just a ‘Valued Customer’. This helps to deepen the relationship between the provider and the user, and ultimately engenders customer loyalty and retention.
Data analysis tools can be of huge benefit to technology companies in helping to tailor marketing campaigns to specific groups, develop new products and enhance relationships with consumers, providing, of course, that the data gathered is used in a legal, ethical manner.