Collection scoring uses data from customer interactions to predict the probability of collecting their debts.
It helps collection representatives focus their efforts on customers who are most likely to repay their debts. In other words, collection scoring helps businesses collect money from customers who owe them.
Example:
A collection team might have a collection score of 80 for a customer with a history of paying their bills on time and a small debt. The team might have a collection score of 40 for a customer with a history of late payments and a large debt.
The collection team would be more likely to focus on the customer with a collection score of 80 because they are more likely to pay their debt. The team might call this customer more often or send them more detailed payment reminders.
The Collection Score is applied at the conversation level. After the call, it analyses each interaction and offers a comprehensive Collection Score analysis.
Types of Collection Score
The Collection score is divided into three main categories:
Good
Average
Poor
It's possible to adjust the score ranges that align with your business use case for these categories through the settings module.
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