Datafinder’s LifeData® contains more than 800 billion attributes including online behavior, social behavior, purchase interests, financial data, and more. LifeData® combined with your historical customer data is used to provide signal to the predictive model.
When working with Big Data, machine learning models historically outperform rules based models. Datafinder’s Predictive Lead Score uses machine learning to analyze the data, train the predictive models and then test to maximize model performance.
Datafinder’s Predictive Lead Score service allows easy upload of historical customer data and automatically builds a custom predictive lead score model. Once the model is built, it is used to score leads through an API or file upload process.
All leads are not created equally – some leads are higher quality than others and are much more likely to convert than others. Datafinder’s Lead Score predicts the propensity of a lead to convert on a scale of 1-100. As a result, Marketers can focus on high value leads to improve top-line revenue growth.
Datafinder uses industry leading matching technologies to augment the historical customer data with LifeData®. Datafinder then applies machine learning to look for “signal” in the combined dataset and automatically builds a custom lead score model. After the model has been developed, customers can submit new leads or prospect lists to be scored in real time through an API or a file upload and download process. The steps to develop a lead score model are fully automated and new models can be developed and tuned in one day.
A sales representative will contact you to set up an informative demo. There are no high pressure sales and no obligation to purchase.
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