Are you curious about what is data mining used for? If you have heard this term pop up in the media in recent years, you’re not alone. Data mining refers to the examination of large databases in order to draw conclusions that can be useful in health care, business, marketing, and other realms. While this is not a new practice, the evolution of computer technology is making it easier than ever to mine data for knowledge and profit. Read on to learn more about scenarios when data mining is used.
How Data Mining Works
Also referred to as predictive analytics, data mining refers to the use of specific software applications to find patterns and make predictions using large sets of information. Data refers to collections of facts and figures around cost, behavior, utilization, and other hard information. These data numbers can be used to provide information. For example, data mining can tell us which products are selling when. From this information, those working with the data can make predictions about behavior and plan accordingly. Read on for some real world examples of how data mining is used.
Predicting Customer Behavior
Sometimes called “market basket analysis,” data mining is used to suggest similar items to people who are shopping for certain items. For example, if you buy books at Amazon, data mining techniques are used to produce recommendations based on the selections of other customers who have similar purchasing habits. Amazon sees this not only as a perceived benefit for the consumer, but as a way for them to upsell and make more money on each transaction. By the same token, grocery store loyalty cards are used to select targeted coupons for you based on the items you frequently buy.
Deciding what items to stock and how much of those items is challenging for online and brick-and-mortar business alike. By keeping track of how much your customers purchase and when, businesses are better able to monitor their inventory and thus, keep a better handle on potential profits and losses. This can not only inform you about what kind of items to buy and how much to keep in stock, but also how to price specific items based on supply and demand. And for manufacturers, data mining can help them predict the need for new products.
By monitoring customer behavior on social media networks like Facebook and Twitter, companies can keep an eye on where your customers are spending their money. Are they remaining loyal, and if not, why? What can you do to keep them? A good example of this would be a clothing company that targets a special offer to customers who have recently purchased from a competitor. They can also examine the behavior of customers who are loyal to determine how to replicate that behavior in other customers.
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This is just a small sampling of the infinite ways that data mining is used across industries. As technology advances, the scope of what data mining is used for will only continue to expand. To learn more, consult this article from the New York Times.