Propensity modeling is a statistical technique used to predict future events. Machine learning allows companies to build robust propensity models and make accurate forecasts. In marketing, for example, propensity models are used to predict customer behavior.
Analyzing data graphs can help you discover hidden patterns and relationships. Making better business decisions and improving performance are possible when your data is interconnected.
To run a profitable business, you need to know your customers. For which, you need to first segment them. Segmentation can be done in a number of ways, but one of the most effective one is RFM analysis. RFM stands for the Recency, Frequency, and Monetary value.
Data is used to teach computers how to learn through machine learning, which is a subset of artificial intelligence. In automated machine learning, the entire process of applying machine learning to real-world problems is automated.
Named Entity Recognition (NER) is a field of computer science and natural language processing that deals with the identification and classification of named entities in text. The aim is to automatically extract information from unstructured text such as people's names, of organizations, locations, and so on.
Customer Analytics: How to Use It to Unlock Business Growth What is Customer Analytics? Customer analytics is the powerful and clear investigation of customer information, and behavior with the objective to find out, attract and reach the relevant or suitable prospect. I
What if you knew how to sell more for less? We can help you. Marketing Mix Modeling is the secret to your marketing success.