Play Moneyball to Reduce Churn and Form a Better Sales Team
Originally published at SalesInsights.org
In Moneyball, Michael Lewis taught Major League Baseball to dig deeper than conventional metrics like batting average, RBIs, and home runs to understand how to build their teams. They did rigorous data-based analysis and found metrics like on-base percentage and slugging percentage were better indicators of offensive success.
Today we might call this artificial intelligence (AI) improving human judgment. And we can apply these AI techniques to build a better sales team.
Use AI to Reduce Salesperson Churn
One of the most important issues to address in building a strong sales team is reducing churn: that is, making sure your best performers don’t leave.
The average U.S. salesforce loses 26% of its salespeople each year. Most companies desire a turnover rate of less than 15% but fewer than half achieve their goals.
And the cost of replacing salespeople has ballooned. Replacing the average salesperson costs almost $115,000. If your sales organization has 100 salespeople, and your retention is only average, you’re losing 26 salespeople a year, and it costs you $2.99 million to replace them.
Now, imagine AI could identify which salespeople are most likely to leave. And you could use this information to reduce churn by a third. You’d add $1 million to your bottom line without landing a single new customer. (And having those sales slots filled would help you get more deals).
Keep Your Winners
If you could evaluate which salespeople are most valuable to retain, you could do even better. Research shows that the Pareto Principle applies to sales teams. Benson and Reising found that 80% of revenue comes from 33% of the sales reps with more than one year of tenure. Identifying and retaining that top-performing one-third is critical to the health of your sales team.
Digging deeper into the data, Moneyball-style, you are likely to uncover key factors like gender. A study Xactly performed on hundreds of thousands of salespeople revealed that women outperform men, and women managers run teams that outperform male-led teams. Coupled with the fact that women are systematically underpaid compared to men with comparable production, your retention efforts should focus on your best women salespeople and managers. It also tells you to correct any unfair, biased compensation practices in your sales organization.
These facts raise two questions: Are you wisely managing retention? Do you have the tools to do it? AI can help: Digging below the common sales metrics, AI can predict salespeople who exhibit behaviors that suggest they’re looking to move, and it allows companies to take steps to retain them.
First, you need data—not just data about your team, but also data about sales churn in other businesses. Your understanding of the varied reasons why sales professionals leave their companies tells you what to monitor. Some common reasons involve corporate culture, frequent changes to the compensation plan and leadership tenure. These factors affect the entire sales team, so while they may be major reasons for the departure of talent, they aren’t red flags all on their own.
What Makes Salespeople Leave?
Some of the reasons why salespeople leave are specific to the individual. These are the ones your AI needs to be trained to identify and use as triggers for action.
Sales Compensation
When management reduces commission rates as reps close larger and larger deals, it feels unfair to the reps. Regularly raising high performers’ quotas makes reps feel like they’re being punished for success, and can cause them to start looking for new opportunities. Conflict over the size and frequency of commission payments also encourages churn.
The failure to capitalize on available bonuses and incentives is another red flag for churn. When salespeople go on autopilot and aren’t moved by new incentives, they’ve disengaged and ready to jump ship.
Training and Coaching
Salespeople want to feel like they’re supported. Often, training stops after onboarding, which leaves salespeople feeling like cogs in the machine instead of valued members of the team. If your company does provide ongoing professional development opportunities, are your top performers taking advantage of them? If not, they may be getting ready to leave. Even worse, when increased use of education fails to move the needle, it frustrates reps and can cause them to move on.
How much coaching are these sales professionals getting from their managers? Managers tend to focus on improving the skills of their B and C players, but A players also benefit from one-on-one coaching and training. When they don’t get it, they can feel ignored.
Support and Administration
Similarly, when increased use of sales support materials doesn’t translate into an increase in sales, a salesperson may become dissatisfied about the support tools decide to leave.
Salespeople want to feel their time is valued, so an exorbitant amount of time spent on administrative tasks can erode their loyalty. So can frequent changes of territory, managers and sales support.
While these are some basic factors that can affect salespeople churn, there are many more criteria that may be unique to your sales organization. AI can uncover your unique factors and predict salespeople who are on the lookout for other opportunities. Understanding your unique factors is the secret to an effective retention strategy.
Training the AI System
The process of machine learning is where AI gains its smarts. The system is fed data and allowed to make decisions, right or wrong. These decisions are then understood as successful or unsuccessful by the system.
More Data is Better
The bigger the set of data and the more decisions the system makes, the more accurately it can refine its algorithms and make better decisions in the future. It’s important to use as large a data set as possible. Use data from your sales performance management software, your commission system, sales enablement, configure price quote (CPQ) and the training platform. And your AI training can use datasets provided by third-party aggregators.
What if you don’t have a huge amount of data? Say, your data don’t go back far enough, your sales team is small and generates a small sample, or your company has only been in business a short time? You can partner with a third party who has compiled these data across many companies. Sales-AI is a young field, and so vendors specializing in sales performance management could be your best data partners for this kind of exercise.
Churn Score
Create a “churn scoring” system that weighs the churn chances for every salesperson on an ongoing basis and allows managers to focus their retention efforts.
Your churn score can also help with planned attrition. “Coach out” low performing salespeople who are dissatisfied, and “coach up” salespeople with lackluster performance but who indicate they are engaged and want to stay and improve their skills.
Testing
Once your AI is trained, you need to test it to ensure it’s going to deliver the right results.
Compare the sales team members who have left recently against their churn scores. This helps you determine whether the AI is properly trained. Through multiple refinement cycles, you will come to trust the churn scoring system and use it to inform your performance management activities.
Training AI to spot key indicators of churn may seem simple, but it’s not. AI challenges sales operations to provide data. It may be tough at first, but the saving associated with lower sales churn will get sales operations the credit it deserves and, at the same time, deliver a stronger, longer-tenured and more skilled sales force.
Examples of Not-So-Obvious Metrics to Monitor
AI can’t read salespeople’s minds, but it can read the data. The obvious factors and forces that lead to churn described above—are like Moneyball’s batting average, RBIs and home runs. The not so obvious—on-base percentage and slugging percentage—that companies have identified for building their own sales teams include the following:
Tenure
Xactly pay and performance data analyses show top and second level performers tend to hit their “sweet spot” of quota attainment within three to five years. It is important for sales leadership to recognize those who show promise in the first year, even if quota attainment is not fully realized. With the right coaching, educational materials and support, those sales reps can sail into their third year and continue to be fruitful contributors for the next several years. The right tools and incentives drive sales motivation, align behaviors, reduce churn, and produce results.
Demographics
The demographics of your sales team plays a part, too. The Bridge Group found that hiring more experienced reps (at least two-three years of experience) led to longer average tenure and more months spent functioning at full productivity. So, the less experienced your sales team members are, the more likely they are to leave prematurely.
Moving the Goal Posts on High Performers
Moving the goalposts on top performers is dangerous. The first quota or commission rate adjustments may make sense because they correct early assumptions about the salesperson’s territory or capabilities. Making adjustments beyond that can cause salespeople to become resentful. They may think their goals will be increased until they fail. This perception pits a salesperson against the company and can force them to seek a more stable and fair culture. AI can reveal this phenomenon. It can do so over time and across the tenure of sales managers, enabling it to search for patterns using a better historical understanding than most humans are capable of.
Sales Enablement Usage
Another area to watch is the use of sales enablement—sales materials, models, pitch decks, etc. A low performing salesperson may simply never use the content. Another may use it but see no increase in sales. They may then become dissatisfied with the support tools and decide to leave the company.
Sales Technology Usage
Not using core sales technology like CRM (customer relationship management) is another not-so-obvious indicator of sales dissatisfaction. Low adoption may signal they are looking for a company with better tools.
Salesperson on Autopilot
The failure to capitalize on available bonuses and incentives is an enormous red flag for churn. When salespeople go on autopilot and aren’t moved by new incentives, they’ve disengaged and are ready to jump ship. (This also represents a good opportunity to evaluate your compensation tactics. If AI detects a failure to seize on your incentives that span the entire salesforce, the problem is with the incentives and not with the sales team.)
AI Comprises a Comprehensive System
Taken individually, each metric is hard to interpret: The strong areas hide the weak. AI develops a system including the relative importance of metrics to anticipate churn. Sales managers lack the time to manually conduct this kind of systematic analysis. AI is the answer.
Actions to Retain Individuals
The retention of individual talent can be a core contribution by AI to the sales function. When warnings come, the actions managers can take range from basic, such as extra coaching, to more dramatic steps, such as adjusting bonuses or accelerators.
AI provides the catalyst for designing individualized dialogue with salespeople to develop retention plans tailored to their needs, taking aim at their frustrations.
Don’t Make AI Look Like Big Brother
Be careful how you construct your discussion of AI. No one likes to be watched. Emphasizing AI could add another item to a salesperson’s list of reasons to leave.
A better approach is to use analytics as the reason for a discussion. You might say: “I was looking at the analytics last week and I saw that we’d changed your territory twice last year and adjusted your accelerator level three times. That has to be frustrating. What can we do about that?” This type of positioning is more effective than leading with, “Our AI said it’s likely you’re looking around for another opportunity.”
AI Does Not Replace Managers’ Intelligence
“Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we’ll augment our intelligence.
Virginia Rometty, Virginia. 2015, Speech to Northwestern University graduates, Evanston, IL, June 2019.
AI is an assistant for sales managers to reduce agent churn. It cuts through large volumes of data to discover specific cases that need attention. But it’s up to managers to use the AI insights most effectively.
AI is not a replacement for a manager’s intuition and knowledge of the personality of individual sales pros. AI is a tool. Expecting it to be a panacea is a recipe for disappointment. But treating it as a new resource that allows managers to work on retention of talent at the optimal time will yield real results, save money on new talent acquisition and retain the most productive members of the sales team.
