A sales enablement manager reviews a conversation intelligence report aggregated across the team's Teams calls for the quarter and notices that mentions of a specific competitor's name have risen sharply in calls that ultimately closed as losses. The manager wants to act on this pattern for the whole team, not just one deal. What is the most appropriate next step?
Select an answer to reveal the explanation.
Short Explanation
When a pattern shows up across dozens of calls instead of just one, the right response is to treat it as coaching material, not a technical setting to flip. A competitor's name showing up more often right before losses is a trend the whole team can learn from, so update the talking points and rehearse the objection handling before the next call. What does not make sense is trying to fix it inside the tool itself: you cannot stop a prospect from saying a name out loud, and turning off the tracking the moment you notice the pattern just means you stop finding out whether the coaching worked. Nudging a deal's win-likelihood score upward because the competitor came up is backwards too; the score is trying to estimate how likely the deal is to close, and quietly overriding it to make a deal look more urgent breaks the thing that makes the score trustworthy in the first place.
Full Explanation
The correct answer is C. Aggregated conversation intelligence data across many calls is meant to surface team-level patterns that individual call reviews would miss, and a rising correlation between competitor mentions and losses is exactly the kind of signal that should inform battlecards and coaching, not automated system changes. Option A is incorrect because conversation intelligence cannot block words from being spoken on a call, and even if it could, silencing the mention would not address the underlying competitive pressure driving the losses. Option B is incorrect because disabling the feature for those calls would remove the ongoing visibility needed to track whether the pattern continues or improves after coaching, undermining the very insight that prompted the review. Option D is incorrect because manually inflating the predictive opportunity score for deals mentioning a competitor misuses the model; the score is meant to estimate likelihood to win based on trained signals, and artificially raising it for at-risk deals would make the forecast less accurate, conflating urgency with probability of winning.