This article originally appeared on HBR.org (subscription may be required).

Customer relationship management software revolutionized how companies manage their sales pipelines. It also allowed organizations to communicate and coordinate more effectively across large sales account teams.

Now a new breed of software applications is reshaping sales force management. Their common characteristic: Using digital data exhaust, which is the data generated from the regular activities of a sales force or their customers, to change the behavior of frontline sales representatives in ways that dramatically improve sales productivity and effectiveness.

I will highlight three tools that hold particular promise, though many others are proving valuable as well.

VoloMetrix, acquired last year by Microsoft, scrapes an organization’s calendar and email metadata to analyze how employees collaborate and spend their time, providing a high-resolution dataset that complements traditional tools like sales force surveys, interviews, and “ride alongs.” Among other things, the software shows how the sales capacity is being deployed across different customer segments, so managers can see whether their sales organizations are truly focused on high-priority customers. And it provides hard data on what resource allocations and which behaviors – such as collaboration between generalist and specialist reps – correlate with better sales outcomes.

At one B2B technology company, for example, account managers were supposed to focus their efforts on their highest-value, “top of the pyramid” accounts. But VoloMetrix data showed a different picture: Account managers were spending more than one-third of their time on accounts at or near the bottom of the pyramid. The company also looked at which activities took up reps’ time. Whereas reps reported spending 60% of their week, on average, meeting or communicating with customers, VoloMetrix showed that in fact they spent less than 30% of the week directly with customers; the bulk of their time was spent going to internal meetings and attending to non-customer emails, administrative tasks, and other activities. These insights spurred the company to realign its sales force to match the intended coverage model. Once that happened, executives realized they had too much sales capacity, and were able to take out costs by reducing sales resources.

A second software tool, currently in pilot stage by Citrix’s GoToMeeting business, uses voice recognition technology to scan conversations between inside sales reps and existing or potential customers, and then analyzes the text to determine which behaviors correlate with positive outcomes such as closing deals or increasing deal size.

The tool’s analysis of inside sales calls at one company found that although reps had long been coached on a broad set of practices, four specific behaviors correlated most closely with sales close rates. For example, reps were using phrases that described product features or conveyed empathy more frequently than they used language that qualified customers or helped them quantify product benefits. When the GoToMeeting team looked at the relationship between language and sales outcomes, they found that the less-frequently used phrases actually correlated more strongly with sales.

The tool showed individual sales reps how they performed on the desired behaviors, and provided targeted coaching to improve performance in areas where they were behind their peers. Sales reps found the data-driven insights and targeted coaching to be a valuable complement to coaching from sales managers, which often is broader and more subjective. More than 70% of reps changed their behavior after receiving insights from the tool. (Transparency and security around employee data collection is essential, of course, if these tools are to work. VoloMetrix pulls the data anonymously and aggregates it. Data collected by the GoToMeeting tool is protected by strict privacy policies.)

A third class of software, which does predictive analytics, uses a different type of data exhaust to identify the prospects, on any given day, who are most likely to close a deal and spend above-average amounts. For example, Lattice Engines’ analytics software pulls data from third-party vendors and independent websites including information about firms’ regulatory and compliance activities, changes in credit rating, financial performance, job posting trends and firm-related social media traffic. It notifies a company if one of its competitors files a credit check on a customer, signaling potential defection. It combines that external data with firms’ own internal customer data, such as loyalty scores and product purchase history. The software assembles an evolving digital portrait of each account, and its algorithms flag the accounts that merit an immediate sales call. This type of software has consistently improved call response rates, close rates and average order value.

These are just three examples of software that taps digital exhaust to improve sales force performance. There are dozens of others, as well a vastly broader suite of tools that help optimize compensation, integrated planning, and other sales force management tasks. Increasingly, the challenge for sales managers is figuring out precisely what they want to accomplish, and then selecting the right tool from an abundance of options.

Mark Kovac is a partner at Bain & Company who leads the global Commercial Excellence group.