Perhaps the most common question among those who are new to using big data is how it can be useful in problem solving and in avoiding mistakes. Those who are not familiar with how big data works often find themselves in a position of wondering how to analyze it.
Big data can provide valuable insights for an organization. When used in conjunction with business intelligence software, such as QlikView, big data can offer useful information about your customers, their purchasing behavior, and other trends.
There are many ways data can be analyzed. One example is cluster analysis which allows commonalities and disparities between sets of data to be revealed in such a way that behaviors and patterns can be presented.
In cluster analysis, you can see your customer segmentation such as demographics, age, and income levels. You can discover who your loyal customers are, and separate them from those who had an experience with you that was more of a "one hit wonder."
For any business, satisfaction is clearly the main goal.
What keeps the customer coming back to you rather than searching for the same goods and services from one of your competitors?
For example, what makes your customers like your accounting software versus what else is out in the market? Do they like simple usability more than comprehensive features?
Solving Customer Satisfaction
Another analytics tool is regression analysis, which gives managers the power to determine how satisfied your customers are
Variables outside your control can be measured to determine what else may be going on that is preventing customers from being loyal to your brand.
Are you too far away if you have a storefront? Are your customer reps hard to access?
By learning more about what's important to your customers, you can take action to fix issues and optimize their experience with your product or service.
There are other forms of data analysis. However, cluster and regression analysis can be effective ways to anticipate and make changes to your business processes.
You can treat your customers right by tracking what works and what doesn't. Big data and analytics can help.