Predictive Analytics: The Power to See the Future
Posted: Sat Dec 21, 2024 4:12 am
A very common wish is to predict the future and when we think about this applied to marketing, it would be even better for brands and companies. Although this is not entirely possible, data is a good way to better understand what is to come. Understand this issue better!
Predicting actions is no longer the preserve of science fiction. In fact, it never was.
Analyzing past information to increase the probability of success in future actions is something that humanity has been using for quite some time.
About 500 years before Christ, Confucius, a Chinese philosopher, antigua and barbuda email list 19714 contact leads had already said that "if you want to foresee the future, study the past."
And he was right!
Of course, we're not talking about a prediction like that of Tom Cruise and his team in Minority Report, but the tendency of stocks is to repeat themselves.
So if we have an accurate reading of events in the past, we are much closer to predicting what may happen in the future.
This is precisely what predictive analytics is all about. But with one difference: a huge help from technology!
What is predictive analytics anyway?
In recent human history, we have always had a lot of information about past events. And that was often the source of wisdom for the main leaders and sages.
The thing is that today we achieve much greater accuracy in this information. This is due to the high volume of data we are generating, making it possible to read more facts and have a greater probability of analysis .
But with this we also have a problem: no human being is capable of structuring and analysing such a large amount of information. To do this, the use of technology is essential.
Predictive analytics is exactly the union of the technological advances we have, which include data mining, machine learning, artificial intelligence and statistics, with the high volume of information we create daily.
When we use computers to process and understand standard behaviors, we are able to anticipate certain events and actions .
How about an example?
You have a SaaS (Software as a Service) company and analyzing your customer information, you notice that 75% of cancellations are made by people who remained inactive for more than 30 days, and this represents a significant curve in your churn graph.
That is, the likelihood of someone cancelling your product plan is much higher when that period of inactivity occurs.
Now you have a clear trend and can act more effectively to avoid cancellations.
Predicting actions is no longer the preserve of science fiction. In fact, it never was.
Analyzing past information to increase the probability of success in future actions is something that humanity has been using for quite some time.
About 500 years before Christ, Confucius, a Chinese philosopher, antigua and barbuda email list 19714 contact leads had already said that "if you want to foresee the future, study the past."
And he was right!
Of course, we're not talking about a prediction like that of Tom Cruise and his team in Minority Report, but the tendency of stocks is to repeat themselves.
So if we have an accurate reading of events in the past, we are much closer to predicting what may happen in the future.
This is precisely what predictive analytics is all about. But with one difference: a huge help from technology!
What is predictive analytics anyway?
In recent human history, we have always had a lot of information about past events. And that was often the source of wisdom for the main leaders and sages.
The thing is that today we achieve much greater accuracy in this information. This is due to the high volume of data we are generating, making it possible to read more facts and have a greater probability of analysis .
But with this we also have a problem: no human being is capable of structuring and analysing such a large amount of information. To do this, the use of technology is essential.
Predictive analytics is exactly the union of the technological advances we have, which include data mining, machine learning, artificial intelligence and statistics, with the high volume of information we create daily.
When we use computers to process and understand standard behaviors, we are able to anticipate certain events and actions .
How about an example?
You have a SaaS (Software as a Service) company and analyzing your customer information, you notice that 75% of cancellations are made by people who remained inactive for more than 30 days, and this represents a significant curve in your churn graph.
That is, the likelihood of someone cancelling your product plan is much higher when that period of inactivity occurs.
Now you have a clear trend and can act more effectively to avoid cancellations.