Which of the Following Statements is Correct of Big Data?
Which of the following statements comes closest to the one you ask yourself when thinking about big data analytics? It analyzes customer wants based on their geographical proximity to your store. It focuses on knowing the general behavior of your target market. It evaluates customer preferences based on purchasing behavior, time-frame or cost. In the end, it predicts how those behaviors will evolve in the future.
Of course, this last statement is a prediction, but not always. If you had the resources and the manpower required, you could use behavioral and chronological data analysis to give you an idea of what kind of sales will slow down or increase over time. You could even take a sample of your customers’ shopping habits, identify which of them behaved differently over time, then use all the trends that emerged to forecast what kind of activities are likely to take place in the next six months or year. If your sales predictions include a measure of customer likelihood of being dissatisfied with the way you treat them, you have a problem.
However, even the best predictive models can be wrong. There are inherent limitations in data analytics. For example, if your data only covers the people who can access your site at some specific times, you cannot use location-based processing and expect to reach true predictive results. Likewise, big data analytics will fail your mission if you cannot integrate your data with yours. For example, if your sales process does not involve customer acquisition, you will have no way of knowing whether or not they are buying. If you cannot get close enough to the customer for customer acquisition, you cannot provide them the value that they want or need.
So, which of the following statements is true of big data analytics? Big data analytics is absolutely true. If you can integrate it with your sales process you will reach true predictive results. If you cannot, you are wasting your time.
There is no single solution to every business problem. Most problems have multiple solutions. Big data allows businesses to extend their reach by identifying business problems that have multiple causes and developing a unified solution that addresses each of those problems. Today’s data mining capabilities allow businesses to mine customers’ data to uncover not only purchasing trends but also behavioral and environmental patterns that may impact customers’ satisfaction with the services you offer.
Even if your business is not experiencing a growth, there is still potential for big data analytics to provide excellent results. You may not yet be seeing results from data mined from social networks, but if you focus on areas such as marketing efforts, customer segmentation, or even geographic targeting, you will eventually optimize for areas where your customers are grouped. As you learn more about customers and how they make buying decisions, you can tailor your product or service to better serve your customers. This will result in better conversions, which improve your profit margin. Eventually, you may see a shift in which of the following statements is true of big data?
In order for analytics to be truly effective, data must be processed quickly and efficiently. This requires businesses to partner with data-intensive technology. In the past, many organizations invested in traditional computing technologies such as hard disks and processors. However, now many smaller companies are deploying mobile computing, cloud computing, and other innovative approaches to make their data processing as efficient as possible.
Big data continues to play an important role in business decision making. You may have questions about the accuracy of some of the data sets that are being used by your competitors or by the government. No matter what type of business you are involved in, whether retail, consumer packaged goods, or healthcare, big data analytics can help you become a better decision maker. As you implement it more fully into your organization, you will be able to reap the rewards of using this powerful analytical tool and improve your bottom line.