At a time when digitalisation and technological evolution have driven companies into a constantly changing world, predicting the act of purchase has become an essential element to accelerate consumer conversion . But how can we anticipate the needs and behaviour of Internet users in the face of such information overload ?
This is where predictive marketing and behavioural data come into play . These cutting-edge techniques allow us to analyse all our personal data (messages, transactions, GPS signals, internet searches, etc.) and offer ultra-precise product or service recommendations .
But how do these predictive systems work ? What tools can be used to deploy this type of marketing system ? How does predictive marketing work in practice ? And what is its relationship with Big Data ? Find out in this article.
Definition
Predictive marketing is a method of anticipating and predicting indonesia whatsapp shopping data the most likely purchasing behaviors of consumers. It consists of a set of techniques based on data analysis , which allows companies to define customized and personalized marketing strategies and actions .
The main objectives of predictive marketing are
collect all consumer data (Internet searches, social networks, e-commerce sites, etc.)
predict a consumer's future purchasing intentions and needs,
propose a personalized offer to each consumer in advance.
How it works
Predictive marketing works primarily through Big Data . It is the fuel of predictive systems: without it, analysis would be inconclusive and irrelevant, if not impossible.
Big Data is all the data that concerns us, such as our messages, transactions, the weather, GPS signals, our web searches, our "likes" on social networks, etc.
All this information is then analyzed by algorithms to predict the different purchasing intentions of consumers. Predictive marketing is therefore based on machine learning or scoring tools . These tools are programmed to send automatic alerts when they observe a combination of criteria defined in their database .