For those of us who are immersed in the world of SaaS sales every day, it’s easy to forget how new the SaaS concept is. Salesforce was founded in 1999 and has been selling software for less than 20 years since. Concur, one of the oldest SaaS companies, only moved from selling CD-ROMs and traditional on-premise software licenses to a SaaS model in 2001.
This business model shift fundamentally changed enterprise software sales from what was a relationship-based, in-person sales process that traded in multi-million dollar contracts, or an SMB software sale that occurred via a brick-and-mortar retail channel. Now, we have a sales process that allows companies to purchase software online and on demand, directly from the provider, at a range of price points.
Salespeople shifted their processes to use these SaaS software products and work more in the cloud. Therefore, data about what happens during the sales process could be tracked for the first time. It became both economically feasible and technically possible to set up an inside sales team to sell to mid-market and SMB customers. Sales cycles became more transactional, enabling repeatable approaches.
With this evolution, the “art” of sales made room for sales science to be included. However, this newly available sales data created a new issue – what do we do with it? What are the right sales metrics for management?
What Sales Metrics are Important to Measure?
“You can’t manage what you don’t measure.” – Peter Drucker
Drucker’s oft-repeated management advice means that you can’t know whether or not you are successful unless success is defined and tracked. So, what metrics are really important to measure?
All sales roles – whether it’s sales development rep, account executive, account management, or customer success – have one thing in common. Ultimately, for any sales discipline, there will be certain results they’re accountable for. For closers, this is bookings. For SDRs, it’s often qualified opportunities created or meetings scheduled.
There has to be a “source of truth” to measure how individuals and teams are performing against expected results.
The next question to ask is obvious. What are the key inputs that generate those results?
Defining the Formula
First, there’s a mathematical answer to that question. A formula to calculate the output. In the case of AEs in the B2B SaaS space, that formula is:
Bookings = (Number of Deals Engaged * Win Rate on those deals * Average Selling Price) / Average Sales Cycle Time
Each of the variables in this formula represents a lever that an AE’s manager can pull to drive higher bookings. Here is a calculator you can play with to understand the impact of each of these levers.
Other selling motions will have a similar formula. It could be understanding net dollar retention rate for a renewals business or meeting conversion and AE acceptance rates for SDRs. For non-SaaS businesses revenue will still equal price times quantity, regardless of the sales motion that gets you there.
Results will always be a lagging metric. Effective management and coaching have to take a broader view, far beyond looking in the rear-view mirror. Even the intermediate metrics in these kinds of formulas tend to be lagging indicators to overall performance. They can be difficult to determine how to impact directly. If, for example, an AE manager wants to push their team for a higher win rate, how can they actually coach them towards that?
Further upstream are metrics that correlate to these more intermediate drivers. The specifics of the inputs you want to measure here will depend heavily on your buyer and sales motion. However, they should include efficiency metrics that give an indicator of the quality of sales activities and effort metrics that show the quantity of those activities.
For an AE in the SMB space, those key efficiency metrics may include opportunity conversion rates by stage and number of opportunities progressed through the pipeline. Effort metrics may focus on total number of prospect-facing meetings and count of opportunities left untouched for a set number of days.
If instead, you’re managing an Enterprise AE team of experienced sellers, you might focus on others. For example, stage-weighted pipeline, number of contacts engaged at each account, and the average number of days between touches on open opportunities.
SDRs and AMs will have different metrics feeding into their sales motions, but the principle will hold. That is, a large quantity of high-quality prospect- or customer-facing activity will generate results.
The Bottom Line
As you look at your sales motion, ask yourself which activities are most important in actually driving outcomes? How can you measure whether those activities are being done well? The answers to those questions will tell you which of your up-funnel metrics are most important to home in on.
Once you’ve decided which metrics to focus on, the hard work begins. You must ensure you’re capturing the data to track those metrics. Then, you need to include time in your managerial cadences to consume said metrics and understand their implications. Lastly, you’ll want to take appropriate coaching actions with your team to drive results.
For additional sales math insights from Karen Rhorer, join us at Rainmaker – the sales engagement conference – March 11-13 in Atlanta. Karen will partner with Pete Kazanjy (of MSP fame) to drop more sales math knowledge on sales leaders.
Karen leads Customer Success and Sales Strategy for Atrium. She ensures customers receive actionable insights from their software to improve the way leaders coach and performance manage their teams. Karen’s extensive experience in sales operations is reflective of her passion for helping sales leaders understand performance and plan for organizational growth.