Used by the professional that is looking for tools to give them the edge in making decisions and finding customers.
Understand your customers true intent and propensity to act, match that with your knowledge to deliver hyper personalized experiences.
Before acting the underlying artificial intelligence will simulate account and contact response to engagement activities
Automated number crunching by the underlying predictive data analytics platform makes it easy for you to work with the outcomes
Account and contact management can take advantage of being able to forecast in the moment what a decision making process is looking like.
Delphi embeds predictive data analytics into your favorite tools so you can see what's moving the needle
Surface the benefits of machine learning directly to the business people working with an account or contact
Shape What Happens With Customer Prediction Analytics
Configuration based propensity models that know where your customers are going to come from and what's going to turn them into one.
Predictive Analytics for Revenue Generation
By analyzing past data and trends along with in-the-moment data, you can predict your customers’ behavior and use this information to target campaigns, identify high-value customers, and plan for future growth.
Propensity modeling is a statistical technique used to predict the likelihood of a certain event occurring.
For example, a retailer might use propensity modeling to predict the likelihood of a customer making a purchase, or a bank might use it to predict the likelihood of a loan being repaid.
Propensity models are typically built using historical data, and the predictions they make are based on the relationships between different variables in that data. For example, a model might use a customer's past purchase history to see if the person is likely to make a purchase in the future again.
There are many benefits of customer propensity analysis, including the ability to:
Customer propensity analysis software makes it possible to understand a customers' true intent by studying past customer behavior and analyzing trends.
This software can help identify patterns and correlations in customer data that would otherwise be difficult to discern. This information can then be used to make predictions about future customer behavior, including the likelihood of making a purchase or taking a particular action.
Customer propensity analysis can be used to improve marketing campaigns and target customers more effectively.