A sales director complains that under the client's predictive lead scoring setup, very few leads ever reach the Hot grade, even though her team closes a healthy share of leads graded Warm. She asks whether the boundary between Warm and Hot can be adjusted rather than waiting on a full model retrain. What should the consultant tell her?

The correct answer is D. The score ranges that determine whether a lead displays as Hot, Warm, or Cool are configuration settings on the predictive scoring model, separate from the trained model itself, so the consultant can adjust where the Warm-to-Hot boundary sits to better match how this team's Warm leads actually perform, without needing to retrain anything. Option A is incorrect because thresholds are not fixed globally by Microsoft; they are set per environment and can be tuned by an administrator to fit the client's own conversion patterns. Option B is incorrect because manually editing the Grade field on individual records does not change the underlying threshold logic and would simply be overwritten the next time scores recalculate. Option C is incorrect because the score ranges behind the grade labels are not locked to the original training run; they are adjustable settings that can be revisited at any time, independent of when the model was last trained.