Molequle offers a powerful feature called Predictive Lead Scoring, which uses machine learning models to score leads based on various factors. The score is calculated by analysing closed marketing opportunities (both won and lost), the history of lead status changes, and lead activities such as involvement in marketing campaigns.
Molequle uses data from different sources to make accurate predictions. For example, people and account data can come from Marketo, lead status history from SAP, and sales data from Salesforce. The goal is to use all available data to create the most accurate lead score possible.
Molequle doesn't make any assumptions about which parts of the customer profile or activity are essential for conversion, unlike manual scoring models that rely on predefined criteria. Instead, it learns from all available data, allowing it to identify patterns and correlations that might not be immediately obvious.
For clients with extensive data history, Molequle can customise a model specifically tailored to their robust dataset. Machine learning allows Molequle to analyse and learn from unique patterns and trends in your data, optimising the model to provide the most accurate lead scoring for your particular context. This personalised approach ensures that the model's performance is maximised, leveraging the full value of historical data.
However, for new clients with a limited amount of historical data, the model has to complement specific data with more generic, data-driven knowledge. This includes factors such as the completeness and integrity of the customer profile, as well as patterns in customer behavior. While the model starts with a broader foundation, it continues to learn and refine its knowledge as more business-specific data is accumulated, ensuring ongoing improvement in lead scoring accuracy.
In summary, Molequle's predictive lead scoring is a flexible and adaptive tool that improves as more data is collected. It leverages machine learning to provide a data-driven and increasingly accurate approach to lead scoring, regardless of how much historical data is initially available. By understanding and effectively utilising this feature, you can enhance your lead management and marketing strategies.