Data Analytics for Business: Why Is It Important?

Data analytics is gaining tremendous traction—not just for business, but any field that aims to extract valuable insights from various metrics. With markets growing at alarming rates, it can be difficult to make sense of all the noise. Data analytics consists of storing, analyzing, and interpreting raw data. These tools empower businesses to make informed decisions and readjust their strategies in accordance with the numbers. The ability to understand and digest various performance metrics allows a business to enhance its operations and boost its returns.

Data-driven business models are the future. When using data to make substantiated decisions, businesses are able to proceed more efficiently and effectively. For instance, according to an article by Harvard Business School, Uber was able to verify significant improvements to its ticket resolution system through A/B testing, which is a process of comparing the performances of two or more versions of a variable. Aside from the optimization benefits, Uber was able to save “millions of dollars.” By taking note of their performance metrics, companies are able to save money and time—​​arguably a business’s most important resources.

When making substantial changes to a business, analyzing data to predict future trends, or predictive analytics, can inform a company of whether those changes will prove to be beneficial. That way, businesses are able to constantly recalibrate and avoid taking large hits in regard to profit. Predictive analytics also enables companies to foresee operational concerns and address them before they become exacerbated. In this way, businesses are able to streamline their operations without unanticipated hiccups and subsequent resource drains.

Moreover, a business’s customers and stakeholders are integral to its success. Analyzing customer data can help an organization highlight pain points, understand who engages with its product, and ultimately pivot so that customer retention and acquisition are achieved. Looking at engagement metrics allows a company to measure its success with various strategies, and coupled with predictive analytics, it can maximize its profit by highlighting products that are likely to produce the most sales. Analyzing transactional data and measuring the success of marketing campaigns will allow companies to reach their desired audience more effectively and foster consumer commitment to their brand. Marketing tends to be ineffective when done blindly; looking at the data enables businesses to identify their target customers and tailor their strategies accordingly.

Especially when under unprecedented levels of competition, businesses must be able to constantly identify and navigate risks. These risks can range from customer fraud to legal liabilities, and can threaten a company’s security if left unaddressed. Prevention is the best form of protection, and businesses can prevent these issues from arising through data analytics. A propensity model, for example, is a statistical model that enables companies to predict future events and trends, such as which areas of operation are most susceptible to fraudulent behavior. By tackling these issues before they come up, businesses are able to minimize company losses. However, complications are inevitable, and a business can employ statistical models to assess the situation and produce the most optimal solutions.

Not only does data analytics help businesses maintain their performance, it can lead to outperforming their competitors. By comparing their own metrics to those of their rivals, companies will be able to see how they stack up against others and identify pain points relative to their competitors. With markets changing quite rapidly, it is essential for businesses to reflect those changes in their strategies and products. Therefore, staying on top of all fronts is crucial to a business’s success.