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How to Predict and Reduce Sales Turnover with Data

For sales organizations, it can be costly to replace a top-performing sales rep. Learn how data and AI/ML technology can help predict and reduce sales turnover.

7 min read

This is the fourth in a series of blogs by Xactly Sr. Product Marketing Manager, Michelle Howard, focused on the impact of data and how it helps sales leaders make strategic decisions. (Check out part one on data-driven sales, part two on the importance of benchmarking, and part three on gaining more performance visibility.)


In our last few posts, we’ve discussed the value of data-driven decision making, and the important role data plays in the success of sales organizations. Part one focused on data-driven sales, part two discussed the value of benchmarking, and part three touched on using data to get more visibility in to sales performance

Even with the flood of data available, turning it into actionable insights is crucial for sales leaders in order to create change within an organization. One of the most sought after data applications is to pinpoint sales rep behaviors. For example, one is particular is identifying the characteristics of top performing reps in potential candidates during hiring. Equally as useful is the ability to proactively understand if certain behaviors indicate a rep attrition risk.

The Real Cost and Impact of Sales Turnover

Attrition, also known as turnover, churn, or the dreaded “A word”, is sometimes expected—it’s a part of any organization. There will always be some form of turnover due to seasonality, growth, etc., but the impact of losing a top performing rep can be more severe. 

Consider the following: attrition comes with a big price tag with estimates to replace a top-performing rep landing between $115,000-$150,000. Let’s break it down even further by the figures.This includes acquisition and hiring costs, training costs, and loss of sales in the open territory. Furthermore, it takes about six months to hire a new rep, plus another 12 for the rep to be fully ramped. 

Aside from the figures, there is an impact to morale when a top performer leaves. It can create a domino effect of uncertainty, make other reps question their own job security and a spur a potential exodus of top talent. 

Long story short: losing a top-performing rep is a very bad (and costly) situation.

Reducing Sales Turnover with Data Intelligence

So how can sales leadership stay on top of attrition and increase sales rep retention? Sure you can hold the traditional one-on-one meetings with reps, check in on performance, and hope reps come to you with their concerns—but what happens when that doesn’t work like it’s supposed to? That’s where deeper visibility into sales performance is vital—and it comes in the form of data.

Being proactive in turnover and attrition scenarios is a game changer. Imagine you could identify performance dips and reps at risk for attrition. Sales leadership could realistically predict attrition, intervene sooner, and reduce sales turnover. 

Xactly Insights takes more than 14+ years of anonymous sales data to help sales leaders benchmark pay and performance in their industry. Combined with Xactly’s Rep Attrition Algorithm, Insights leverages AI and ML to pinpoint if a rep is at risk of leaving an organization. 

So how does it work? Insights predicts rep attrition and helps reduce sales turnover by analyzing more than 50 data points related to the rep’s current status, tenure, manager, and more. The algorithm is able to identify attrition in a clear, easy to read scatter plot. What could a sales organization due proactively to stem attrition if armed with the right data? 

Putting Insights to Work for Xactly’s Sales Team

Although the algorithm is unique to Xactly, we are not immune to attrition. In fact, we decided to use the Insights Rep Attrition Algorithm on our own sales team, and the results were shocking to say the least. The algorithm was enabled for sales leadership on a Friday afternoon and immediately flagged our top two sales reps at risk. Ironically, over the weekend the top rep put in his resignation—but it was still a shock. Why didn’t leadership see this coming? 

The rep had just closed a massive deal and had been with the organization for a handful of years. In retrospect, this caused us to look deeper into our Insights data to identify what was happening under the hood and evaluate our sales environment. 

The ability to identify attrition risk is one part of the equation. When armed with the right tools, it’s up to sales leaders to evaluate the situation. It could mean conducting a stay interview (the opposite of the exit interview) in order to gauge happiness and engagement with a rep. It could mean enhanced sales enablement and coaching, or a potential promotion or financial incentive. It could also mean moving that middle core group of performers up so they could grow in their careers. 

Avoid the dreaded A-word and reduce sales turnover. The stronger sales organization are those that use data to inform better decision making, better their sales environment, and turn attrition to engagement. Great sales managers and leadership must do everything they can to keep top performers in their seats.

Want to learn more about reducing sales turnover? Download the guide “How to Build and Retain Sales Reps to Drive Top Performance” to learn how tenure impacts sales performance.