At this point, stating that the importance of analyzing lead behavior is essential seems redundant. It is a crucial statement in the world of marketing, and one of the starting points of practically all the campaigns that can be launched.
Leads and the ways in which they are captured provide companies with a series of data that can be used to strengthen ties between the web and the user. In other words: they serve so that those responsible or experts in charge of the strategies can hold those users by the hand, and take them through each sale cycle to the buy button.
Within this lead analysis strategy there is a new trend known as data mining. Today we talk about this term.
Data mining: What is data mining
Data mining is a process that large companies are carrying out to take advantage of all the information that users leave in their communication channels.
The data mining or data mining is actually the way in which the set of strategies that explore the databases is called; the mountains of data that accumulate in companies.
But it also refers to the technology used to carry out all these processes.
Therefore, it is the way in which the patterns or algorithms that give meaning to the behaviors are searched among that data.
It is about identifying repetitive patterns, trends and, ultimately, the rules that users follow in order to get the most out of those mountains and mountains of data. It is a kind of filter in search of unique and relevant information aimed at achieving the objective: conversions, sales, subscriptions or any other call to action.
The main features of data mining
Many experts agree in highlighting the ability of this process to discover the innate intelligence of each business. It is about guessing that intelligence through factors that are not detected with the naked eye: trends, correlations, patterns, behaviors, etc.
The ability to take advantage of the competition due to its power to forecast future situations is another of its characteristics. Now, these characteristics and results are not only applied to companies, but also in investigations or even in government affairs, among others.
People who engage in this analysis are called miners. They are in charge of applying the necessary tools and software at each stage of the analysis depending on the problems to be solved. In any case, normally the stages are:
- Sequence analysis
Regarding the analysis, these miners determine the objectives with the clients in advance. The application for finance jobs will not be the same as for fraud detection, for example.
Once this objective has been set, the data is processed and the model is determined. This is where the first statistical analysis is performed. Finally the results are analyzed. All this through a system that can be descriptive or predictive, depending on the objective.
The advantages and disadvantages of data mining for your business
Knowing that with the application of data mining you will optimize time and help you attract and retain customers, how long will it take to request a quote for a data mining service?
And not only that, it also brings many other advantages to any company in a global world where competition has never been so fierce.
- The combinations that the algorithms allow will make you discover data or information that you would not have even imagined.
- The final data is easy to interpret.
- You will anticipate what your customers want or what they need. You will know how to predict what things are going to demand or need.
- Information in the digital world is more than power, it is the best way to attract, capture and retain customers for your business.
- The valuable business opportunities that the application of data mining opens up mean that this means cost and effort savings in the medium term.
Disadvantages of applying this technique
However, in this universe of data analysis, why are we going to fool ourselves? Not everything is advantages.
It can happen that, depending on the job, the magnitude of the data is a huge task even for miners and their software. All this also implies, as is to be expected, a greater investment in technologies and means necessary for these works.
It is to be expected that all the areas subject to data mining will not have the same scope. You must not forget that, at present, data mining is used both in the field of statistics and in artificial intelligence, passing through any company that is going to be the object of a marketing strategy. Obviously investments in technology cannot be comparable between some fields and others.
Precisely the cost of this technique applied to companies, and the time investment involved in its application, means that today it is not affordable for everyone.
In recent years we have witnessed the silent data revolution. Data and more data that have been accumulating without us even realizing it. But those who have been more attentive have been those who have realized that the transformation of data into information is the best asset for any company.
It is precisely here that data mining has entered the scene, that technique that has made such a basic and pioneering idea a reality in our times. The technique that has delimited in many cases the success or failure of those who have been able or not to make the conversion.