While historically AI and machine learning tools have been segregated to technical data science and development roles, the past several years have seen a democratization of these tools to more business-centric roles, including sales.
This new-age of AI and ML technologies offer the front line sales manager predictive insights to more consistently build sales pipeline and forecast their team’s deals.
AI analyzes and learns from the behaviors of top-performing reps in order to benchmark and predict the health of deals. Looking at indicators of deal engagement such as the number of upcoming meetings, and what titles are involved in a deal, AI solutions can alert sales managers of things like “phantom deals” in their forecast or potentially healthy deals that could get pulled up into the current quarter.
In addition to alerts, sales managers are able to have a better understanding of how their team spends their time. Using AI to aggregate their team’s activities and match those activities to deals and accounts in their CRM, sales managers have the ability to monitor not just the number of activities (number of emails, phone calls, meetings, etc.), but rather are they conducting the right activities. Using this information, sales leaders can monitor things such as the time reps spend “hunting vs farming,” or time spent working specific accounts.
Using AI to both capture data and deliver insights on their team’s performance, sales leaders have the ability to surface previously hidden patterns in their team’s behavior. These patterns and insights allow sales leaders to optimize their seller’s playbooks, benchmark rep activities, and ultimately coach their teams with data rather than emotion.
In “The AI-Augmented Sales Leader” ebook, we explore how sales organizations are leveraging AI to both capture the data they need to gain these insights, as well as specific use cases of how sales leaders are using this data.