With Predictive Analytics you look into the future

When it comes to predicting the future, we often think of palm reading, coffee-gazing, or ancient writings of the Incas or Nostradamus. But these days, things are different. By applying Predictive Analytics you can use data, science and A.I. and Machine Learning software predict what will happen. Predictive Analytics is a lot closer than the fortune teller at the fair.

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    Making connections and recognising patterns

    Predictive Analytics use a mass of data to make connections and recognise patterns. This allows you to quickly discover certain trends and to project them into the future. The possibilities of this technology are growing, because we are collecting more and more data as we use more and more digital tools and give them more and more sensors. More data, in other words! The more different variables, the more complex the correlation is and the more accurate the predictions are.

    Predictive analytics makes it possible to anticipate the future with foresight and make appropriate choices. This can be very useful in many areas! How this works exactly is clearly explained in the video below:

    Predictive applications

    We do not need complicated models to predict that this can be useful in many industries. Here are some examples:

    What marketer wouldn't want to be able to predict who might become a customer? That would make advertising much more effective. Instead of determining target groups based on gender, age, interests, wealth etc., Predictive software can find the customer based on individual variables. Based on socio-demographic data, search and purchase history, online interaction and environmental factors, the potential customer can be picked out and estimated for the best approach.

    There are so many things that influence the stock market that a lot of investing comes down to gut feeling. Today, you see more and more predictive models to map market forces. By letting software analyse as many internal and external variables as possible, companies can make the right investments. You can see more financial applications here:

    How many lives could a doctor save if he could look ahead. Currently, there are already many examples of data analytics that identify which patients are at risk of certain complications, such as diabetes, asthma or cardiovascular disease. With the integration of better sensors in devices such as smartwatches, healthcare can increasingly prevent complications in advance rather than cure them afterwards.

    There are still many ways to apply the technology of predictive analytics. Predictive analytics are often complex and cost a lot of time and attention to develop. Nevertheless, with a lot of data, effective questions and the right models, you can already achieve significant results in the short term.

    Do you want to start digitising data or applying A.I. or Machine Learning to get ahead of the game? We like to think along with you. Ask about the possibilities via this button