It's 10 AM. Do You Know What Your Sales Reps Are Doing?

It's 10 AM. Do You Know What Your Sales Reps Are Doing?

New software can help executives identify which activities and behaviors matter most for sales performance.

  • min read


It's 10 AM. Do You Know What Your Sales Reps Are Doing?

This article originally appeared on HBR.org.

Sales executives with even moderately large, distributed sales forces rely on data to help them understand which activities and behaviors lead to the best outcomes. Yet much of the data from sources such as CRM reporting tools and time studies is self-reported, and thus inherently flawed. That leaves executives in the dark about what is actually occurring on the front lines, or whether those activities advance or impede progress toward desired outcomes.

Using new software to analyze the digital exhaust of calendar and email metadata provides a practical way to build an accurate profile of how frontline sales representatives and managers spend their time, who they interact with externally and internally, and what effect this has on sales performance. By seeing exactly where and how people spend their time—rather than relying on recollections, anecdotes, or assumptions—executives have a solid basis for taking actions that will raise productivity. This view, combined with traditional sources such as quota attainment data, territory and account plans, and qualitative observations from ride-alongs and coaching sessions, allows executives to confidently identify which activities and behaviors matter most for sales performance.

We have worked with several companies in B2B industries to use Microsoft Workplace Analytics as part of a broader effort to improve sales effectiveness. We’ll focus on how the software helps to clarify three situations: design of the sales coverage model, alignment of sales resources to market opportunity, and identification and widespread adoption of the behaviors with the strongest positive influence on sales performance.

Refining Sales Team Structure and Roles

At the highest level, Workplace Analytics can provide a factual foundation for decisions on sales structure and roles. Consider the case of a company selling basic supplies to businesses. The company had experienced lackluster sales growth, especially outside of its core product category. So it decided to examine how the sales group, which consisted 85% of field reps and 15% of inside reps, spends its time.

From customer surveys, the supplier learned that 60% of customers prefer to interact with sales reps by email, 30% by phone, and fewer than 10% by in-person meetings. Field reps had naturally sensed customers’ preferences for email, yet data from Workplace Analytics revealed that the bulk of their time was consumed on purely internal communications. They spent less than one-fifth of their time communicating with customers at all. This raised the question: What was the point of having a large field force? Based on the new time data, the company shifted to a predominantly inside sales model. Because compensation for an inside rep is roughly 55% of what a field rep receives, and an inside rep can cover more accounts, the company saved $40 million per year while increasing coverage and time spent with customers.

Aligning Sales Priorities and Incentives

Sales leaders would dearly like to know whether their deployment of sales capacity aligns with the most attractive opportunities in the market. An enterprise software company confronted this issue after it shifted its strategy to focus on cross-selling in larger, Tier 1 and 2 accounts—those with the most potential spending across the company’s product portfolio. Months later, the company discovered that account managers were still spending only one-third of their time meeting with customers, despite self-reporting a higher share of time. Worse, they were spending 40% of that customer time with accounts at Tier 3 and below.

With this new evidence in hand, sales leaders at the software company were able to make the case for dramatic changes, including reassigning about 30 account managers and 20 specialists, and adjusting the compensation scheme to pay certain reps only for sales to high-priority accounts.

Identifying What Top Performers Do Differently

Besides wrestling with structure and alignment issues, sales leaders have always sought to understand why some of their reps consistently attain or exceed their goals and others do not. They also struggle with how to get more reps to perform at top levels. Are sales stars born to the breed, or do they engage in specific, teachable behaviors that correlate with success? We believe the latter is true, and that sales leaders can use hard data to identify which behaviors matter most.

One business-to-business supplier dealt with similar questions by combining metrics from Workplace Analytics with other sources that measured factors that, we hypothesized, might improve sales performance, such as cross-selling new product categories. Using statistical techniques, we determined which factors explained the difference between the best performers and average ones. We also conducted traditional qualitative research, such as interviews and ride-alongs, to shed light on the root causes.

We learned that top performers did a few things differently. Some were intuitive, such as spending an average of four more hours per week than other reps communicating with customers, or being 25% more likely to cross-sell other product categories. But some behavior was surprising. Top performers were:

  • Three times as likely to interact with multiple groups inside the company. They worked with sales specialists but also people who could bring expertise to bear on, or expedite, the handling of a customer issue, such as staff in finance, legal, pricing, or marketing. The size of a rep’s internal network consistently predicted sales success.
  • Twice as likely to collaborate frequently with peer generalist reps, even though the structure of the sales force made it unlikely that peers would ever work together on a deal.
  • 50% more likely to have weekly pipeline reviews with their direct managers.

Given that software tools typically provide indicative metrics rather than the full scope of underlying behavior, combining quantitative insights with qualitative observations helps executives understand the root causes of performance differences. After reviewing both sets of information, the company learned:

  • The most successful reps came better prepared to their meetings with customers. Rather than showing up to a quarterly review to discuss how much the customer wanted to order, they prepared by assessing the potential needs of the customer, pulling in experts on other products that might be pitched. That allowed them to have richer conversations with customers, in which they could credibly cross-sell new product lines.
  • Top sellers sought out opportunities for coaching and mentorship, whether through formal training or from their direct manager and their peers. That’s why “peer time” became a predictor of sales success.
  • Best sellers often worked on teams where the frontline manager took advantage of weekly reviews to coach reps on how to advance opportunities, rather than to simply inspect their plans.

We do not believe that software will ever spit out algorithms that robotically build supersellers for any market. The data becomes most powerful when blended with other data sets and qualitative information.

Moreover, insights derived from analytics will sit on the shelf if they aren’t used to coach and reinforce reps’ habits. Getting average performers to change their behaviors requires showing them why the change benefits both them and the company, training them in the different behaviors, providing them with the right tools, and urging supervisors to coach them. To assemble an effective account plan, for instance, a rep might need training in additional products, as well as easy access to a heuristic model that can help calculate the customer’s wallet size. The rep’s manager could reinforce the plan by periodically referring back to it in coaching sessions.

The revelation of how sales people actually spend their time paves the way for management based on facts, not myths. It makes clearer what combination of coverage, alignment, and behaviors generates the best outcomes. And it gives frontline managers a specific agenda for coaching and training, all in the service of inspiring greater productivity for the entire sales team.

Mark Kovac is a partner at Bain & Company who leads the global Commercial Excellence group. Jonathan Frick is a principal with Bain & Company’s Customer Strategy & Marketing practice.


Ready to talk?

We work with ambitious leaders who want to define the future, not hide from it. Together, we achieve extraordinary outcomes.