Managing sales has never been easy, and it does not promise to be any easier in the near future. However, the field of sales management is changing rapidly and new possibilities change how sales teams can be managed.
One of the biggest changes to the discipline of sales management that has been seen in recent years is triggered by a single new metric; software can now calculate the strength of a relationship between someone on your team and someone in the buying organization. This one new data point makes a number of new approaches to sales management possible that were not possible previously, and in doing so pushes modern sales teams to rethink their approach to take advantage of the new opportunities that are offered.
Historically, teams had attempted to log sales activity in CRM systems and build basic reports that attempted to proxy the strength of relationships between team members and buyers, but these efforts had fallen flat. Activity logging is a perennial challenge for many organizations, and even those that solve it find that CRM systems are wholly inadequate for modeling the way in which relationships grow and decay over time. A new approach was needed if sales managers were going to be able to use relationship strength as a tool for managing sales teams.
Adding to this new metric, of course, is the advent of artificial intelligence. Sales teams are now supported and enabled by AI-based systems that can perform certain tasks with speed and accuracy that would never have been possible historically. Together, these new capabilities change the art and science of sales management.
Relationship intelligence systems fill this void by accurately measuring the strength, and decay over time, of every relationship. This enables new approaches to sales management across the spectrum from territory definition and sales prospecting to forecasting and account growth.
In some areas of the sales process, this new ability to measure relationship strength leads to new ways of accessing accounts, and can increase rep effectiveness. If other areas, the ability to watch relationship strength and ensure no balls are dropped increases rep efficiency. At the end of the funnel, the ability to use relationships as a litmus test on forecast deals allows sales managers to decrease their own risk as they commit to a forecast for the quarter.
Much of territory definition relies on classic sales management tools and data sets such as industry and company sizes in each available geography. However, adding the new dimension of relationship strength allows sales managers to begin to look at territories in a new way. When sales reps leave a territory, it has historically been difficult to bring a new rep up to speed in the territory as they do not know which relationships are available to be picked up.
With relationship intelligence, sales enablement teams can enable managers to bring a rep into a territory with awareness of how active the relationships had been with the previous rep, and confidence that the new sales rep can quickly pick up from where the territory had been left.
The art of contacting prospective buyers has changed drastically in recent years. A wave of automation tools promised to turn sales development into a highly automated, finely tuned machine. In that brief era, sales management was able to tune cadences and watch buyers line up for demos. However, as quickly as it started, the effectiveness of “did you get my last email” plummeted and sales managers were left searching for how best to manage their prospecting teams.
The best sales managers of today measure relationship development, and work diligently to avoid “spammy” behaviour. By carefully measuring the growth of relationships, rather than the raw outbound volume, reps can be guided to find insightful points of view and compelling ideas that are relevant for individual buyers.
Artificial intelligence assists in this as it is core to modern sales intelligence systems. Enabled by AI, prospecting teams can have timely, relevant, and actionable insights on each of their accounts The management of these teams focuses more on building a compelling point of view for each unique situation, than on automating generic touchpoints.
Insight into relationships, coupled with software built upon AI, gives a new sales management ability where it matters most – the ability to accurately commit deals to forecast. Near the end of the quarter, filtering through the deals that the team has placed in a “commit” stage, is mainly art. However, by allowing AI-based systems to flag deals where the relationships are not as broad or as strong as they have historically been in deals that closed, sales managers are able to turn this high stakes analysis into science.
Once a deal is closed, a new phase of sales management begins. Ensuring that a deal renews on its annual cycle, and any opportunities for growth and expansion are capitalized on is a task that falls to an account team or a customer success team.
Often, the ratios of accounts per person are higher in this phase than they are in the new account phase, and the management challenge becomes making sure that the team is keeping all relationships alive, and is aware of any external events that could indicate an opportunity to expand.
This management challenge is again greatly enhanced by relationship intelligence and AI as the account team can focus on the activities that build trusting relationships, while automatically being notified of any interesting trigger events such as new executives, new projects, scandals or growth announcements. If any accounts become “single-threaded”, or fall below a threshold of relationships, a warning can automatically flag those accounts for immediate attention in order to maximize the opportunities for growth and expansion.