They analyze a customer's purchasing history

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They evaluate the probability that a specific customer will complete an action such as, for example, purchasing a product or signing up for an offer and estimate the probability of abandonment and disengagement Recommendation models .  to estimate sales opportunities and make proposals on relevant content, products, services and offers To obtain the maximum possible results from your predictive analysis you must integrate these three models together .

You will thus have the opportunity to get to know your customers better and to identify emerging trends and "submerged" opportunities. Shaping products and services based on the real needs and requirements of the target will make sales take off and  Turkey Phone Numbers 32 Million List establish a solid relationship capable of resisting over time. The importance of context in predictive analytics Contextual marketing can be very useful for predictive analytics. Contextual marketing aims to provide extremely personalized content by offering messages and ads that can be perceived as relevant to the individual customer.



This type of approach has the ambition of reaching the target in real time by adapting to the target context. A Salesforce survey highlighted that 64% of customers now expect real-time brand interaction . The key word is timing. Integrating contextual data with predictive analysis means knowing more in-depth the context in which customers live and move, understanding every habit and aspect of their daily life.