Being fast is no longer enough. Today, it’s best to be able to predict the future. Mathematics has long had suitable methods at the ready. What was missing until now was the computing power and smart software? But the future has just begun: Predictive marketing helps us make better decisions.
The application scenarios for predictive marketing are diverse. But there is a catch: Predictions work best when you have enough relevant data, which also has to be processed accordingly.
Big Data is already having a major impact on our everyday lives. When we use our smartphones, a huge amount of data is generated. Data from which, in turn, conclusions can be drawn. For example, our mobility behavior with apps that inform us in real-time about bus and train departures, or various smart gadgets such as smartwatches that track our daily activities – all this feeds the hard drives and drives Big Data.
In marketing, data has always been accumulated – that’s no secret! What’s new is that enormous computing power is affordable for everyone these days. This enables entirely new possibilities. For example, sending the right message to the right people at the right time, sophisticated targeting!
What exactly is predictive marketing?
Predictive marketing – when technology and data merge. But what does the process look like? It’s about evaluating the amount of data that has already been collected and is being collected on an ongoing basis in relation to your target audience.
Insights gained help you better understand your target customers and fine-tune your marketing strategy.
The difference between traditional analytics (“business intelligence”) is the future-oriented view.
- Who will be my next customer?
- Where do I find so-called hot leads?
- And how do I convert them successfully?
The almost uncannily relevant product recommendations from Amazon, for example, are based on predictive marketing or predictive analytics. It is linked to the purchases we have made in the past and is programmed in such a way that, as time goes on, it becomes easier and easier to estimate what shoppers will buy next.