When they are used together, data mining and predictive analytics can really make marketing more efficient.
There are many techniques and methods for this, and one of them is business intelligence data collection.
Now we get to a point, what is business intelligence data?
First of all, we can define the 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 for weeks, or even a month for data, managers are now able to mine data and perform predictive analysis from multiple sources daily.
So now we come to predictive analytics. What predictive analytic really is?
Predictive analytics is using business intelligence data for forecasting and modeling. It presents a way to use predictive analysis data to predict future patterns. This means making better business decision. For example, it is used a lot in the insurance, medical and banking industries. Assessment of credit and assignment of a credit score is probably the most widely known use of predictive analytics. Managers are able to estimate the likelihood of future events, only based on events from the past.
Now we get to marketing. Business intelligence data mining can be important for your marketing campaigns. If you would use proper data mining algorithms and predictive modeling, you could narrow your target audience and in this way be more precise and effective. Your marketing team will have the opportunity to develop multiple advertisements based on, for example, the past clicks of your visitors.
Predictive analytics can also help in choosing marketing methods, and marketing more efficiently. Only by 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. It's pretty simple formula. Of course, in the best cases, predictive analytics can reduce the amount of resources spent to close a sale.
But maybe the most important point of view when we talk about marketing is that business intelligence data mining can help marketing professionals anticipate and prepare for customer needs, and not just to react to them. Also, data mining can present data on demographics which may have been previously overlooked. For example, how and what is changed in behavior of your loyal customers? Are they now shopping for maternity clothing, instead of clothing to wear to a club? 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.
This is just a top of an iceberg, but even this is enough to realize that when applied to marketing strategy, predictive analytics and data mining can help managers to bring in more sales, while spending less on campaigns.