By establishing AI-calculated scores as objective rules for assigning projects, you can prevent opportunity losses and maximize your team's overall close rate.
When distributing leads to multiple sales members, including agencies and freelancers, we recommend a data-driven optimization approach rather than relying on subjective judgment.
1. Prioritize assigning projects to high-scoring members
A consistently high AI score indicates that the member is "successfully replicating the company's winning patterns and appropriate listening techniques." To avoid wasting limited, high-quality leads, set a rule to prioritize assignments to members who consistently achieve high scores. This also serves as a fair motivation booster for members, knowing that "improving my score gets me better leads."
2. Objective lead-pausing and retraining based on data
For members whose scores do not improve despite repeated meetings and role-plays, you can use "objective AI data" rather than personal feelings as the basis to temporarily pause new lead assignments. This proactively prevents the loss of leads (lost deals) due to inexperienced handling. Following this, you can transition them to a positive retraining flow, such as conducting role-plays with the AI as the examiner (self-coaching) and resuming lead assignments once they reach a passing score.
Perspective on improving ROI (Return on Investment)
If you can use data to detect members who are "not yet ready for the field" early on and prevent the loss of even a few promising leads per month, the resulting increase in sales will easily exceed the cost of implementing the tool. Please utilize the AI as an "excellent balancer to maximize your close rate."