Predictive analytics puts information gained from data in correlation in order to forecast events which are likely to take place. In economy, especially in marketing, there are many possibilities. More and more companies are recognising this as a competitive advantage. According to Forbes, 89% of marketers have predictive analytics on their roadmap for 2016.
In predictive analytics, forecasts on future developments are made based on the analysis of data, e.g. on the purchase behaviour of customers. This helps companies to adapt their actions to these forecast models, as well as identify risks and possibilities. The procedure basically detects reoccuring patterns and therefore, the forecasts should only be considered as probabilities and not as facts. There are many different deployment scenarios for predictive analytics, in marketing, for example, for the assessment of customer behaviour and automated response with suitable communication. 49% of marketers already use predictive analytics, another 40% are planning to implement it within the next 12 months (Forbes).
With Predictive Analytics to Customer-centred Communication
Requirements of customers on marketing and service communication of companies are increasing. Customer-centricity is a vital success factor. If you can predict your customer’s future interests, actions or purchases, you can adapt your communication accordingly and automatically output the right measure at the right time. For companies based on subscriber business models, predictive analytics may be useful, e.g. to forecast cancellations and thus initiate automated counteractions.
The system registers responses and purchases of the customer, analyses them, tries to find communalities with the data of other customers and thus derive generally valid patterns (customer who buys product A and shows these properties, later buys product B with x% probability). Over time, the system independently learns (machine learning) and develops increasingly more precise prognostics.
You can find more information on the topic of machine learning and artificial intelligence in our trend post on The Next Web Europe 2016.