Predictive Analytics and Data Mining

When used together, predictive analytics and data mining can make marketing more efficient. There are many techniques and methods, including business intelligence data collection.

What is Business Intelligence Data?

Business intelligence is a decision support system where information is gathered for the purpose of predictive analysis and support for business decisions. Prior to the widespread availability of data marts and reporting software, business intelligence data was gathered manually. Collecting information across corporate departments such as finance, sales and production, and correlating it into meaningful presentations created further time delays.

Current availability of business intelligence data in computer-readable form, both within a company and from online sources, make incorporation of business intelligence data into business operations more dynamic and bring it closer to real time. Instead of having to wait a week, or even a month for data, managers are now able to mine data and perform predictive analysis from multiple sources daily.

What Are Predictive Analytics?

Predictive analytics is using business intelligence data for forecasting and modeling. It is a way to use predictive analysis data to predict future patterns. It is used widely in the insurance, medical and credit industries. Assessment of credit, and assignment of a credit score is probably the most widely known use of predictive analytics. Using events of the past, managers are able to estimate the likelihood of future events.

Data mining aids predictive analysis by providing a record of the past that can be analyzed and used to predict which customers are most likely to renew, purchase, or purchase related products and services.

Business intelligence data mining is important to your marketing campaigns. Proper data mining algorithms and predictive modeling can narrow your target audience and allow you to tailor your ads to each online customer as he or she navigates your site. Your marketing team will have the opportunity to develop multiple advertisements based on the past clicks of your visitors.

Predictive analytics can aid in choosing marketing methods, and marketing more efficiently. By only targeting customers who are likely to respond positively, and targeting them with a combination of goods and services they are likely to enjoy, marketing methods become more efficient. In the best cases, predictive analytics can reduce the amount of dollars spent to close a sale.

At its most effective, business intelligence data mining can help marketing professionals anticipate and prepare for customer needs, rather than just reacting to them. And data mining can present data on demographics which may have been previously overlooked. For example, have your loyal customers gotten older or younger? Are they now shopping for maternity clothing, instead of clothing to wear to a club? Are they more hip or environmentally aware? Any combination of those changes in your customer demographics could be useful in determining what newspaper or magazine is the best venue for your print campaign and what type of campaign it should be.

When applied to marketing strategy, predictive analytics and data mining can help managers to bring in more sales, while spending less on campaigns.