Data mining is the set of techniques and technologies that allow you to explore large volumes of data, automatically or semi-automatically.
The purpose of data mining is to analyze repetitive processes or trends in order to solve very diversified problems like the prediction of customer behavior, the detection of fraud, or preventive maintenance… These algorithms facilitate informed decision-making. At the origin of data mining are artificial intelligence, statistical analysis and machine learning. AI is able to create algorithms at reasonable costs. Statistical analysis can be used to model the results obtained. Finally, machine learning allows you to go even further in data analysis.
Thanks to data mining, you will finally be able to automatically know which items your customers tend to buy together. You will optimize your procurement and storage processes. It is therefore ideal to plan more realistic sales forecasts.
QWhat a pleasure to finally know the profile of your customers, their preferences, the frequency of their purchases… Your marketing department will be delighted to take advantage of the assets coming from data mining. Here comes the times for the segmentation of the database for more targeted, more personalized campaigns. In short, your ROI will be much better and your customers will be satisfied.
With so much new information, you’ll be able to invent the product (or the service) your customer needs… Customize your products according to the upcoming needs or expectations of your customer. It may appear as a risk but with so many figures and statistics…
As a conclusion, data mining is very useful to analyze data, and thus move from a logic of “big data” to a logic of “smart data”. Of course, the ideal is that all data is centralized into a single tool, the CRM!.
** fuente: sinnexus