The Definitive Guide to Sales Metrics

Ralph Grimse

Never before has sales had access to so much data. And you’d think that with this level of data there’d be more fact-based decision making. Unfortunately, too many sales organizations are overwhelmed and under-leveraging their data. They lack the time and acumen to really dig into the numbers. They're unable to turn the mountain of data into insight or action.

So, what should sales management look at to determine the health of their organization? When we execute our diagnostic work, we advise sales ops, enablement, and leadership to look at a several core elements of their model. We then benchmark those elements against others in the same industry or with similar sales models. The key is taking a structured approach, using select data factors to gain specific insight.

Without a model for leveraging data, it’s easy to get stuck in analysis paralysis. In our model, we look at seven major data categories to evaluate the health of a sales team:

1. Overall Sales Performance – These are by far the most common and easiest metrics to gather. In this part of our model, we’re most focused on two things: 1) Growth (or lack of!) and 2) the efficiency of that growth.

As we look at growth, we seek to understand where it’s coming from (customers, geographies, and product mix). We also want to understand how well the organization is performing against budget. This provides great insight into forecasting, goal setting, and comp plan performance. These metrics provide a quick assessment on the overall health of the organization. But all growth comes at a cost, so it’s important to also understand key productivity and efficiency metrics.

Sample Metrics:

  • Sales growth
    • Net new growth
    • Base customer growth
    • Growth vs. budget
  • Average Revenue per Rep
    • Per Hunter
    • Per Farmer
    • Per Sales Support

2. Generating Opportunities It’s not just marketing’s job to generate leads. Sales must be generating their own opportunities. Diving into lead generation metrics can often be a black hole and a ‘he said, she said’ scenario. Marketing will likely have metrics that differ from those used by sales.

What’s important is that we understand the mix of the various lead sources and their respective conversion rates. Too often we see investments in lead sources that are actually converting at the lowest rates!

Sample Metrics:

  • Percent of total leads by lead source
  • Volume of leads generated
    • number of opportunities sales needs to hit quota
  • Conversion rates by lead source
  • Marketing spend per lead source

3. Managing Opportunities to Close – Opportunity management is often the low hanging fruit of every sales organization. Small improvements in key metrics and can make the difference between hitting the number or not. In this part of the model, we’re looking for effectiveness. How fast do we close our opportunities? Are we leaving dollars on the table?

We also want to understand how the sales organization handles RFPs. Depending on the industry, we’ll dive into more detail around RFP success rates and deal size. These should be easy metrics to report since they’re the lifeblood of any sales team. However, poor CRM adoption can make these metrics challenging to uncover or misleading.

Sample Metrics:

  • Sales cycle length
  • Average deal size
    • Upsell
    • Net New
    • RFPs
  • Win rates
    • Existing customers
    • Net New
    • RFPs

4. Growing Customers The land-and-expand model is not a new concept (despite what you read in your SaaS industry blogs). Yet, many organizations do a very poor job on the expansion part. When we assess the base of accounts, we want to understand the concentration of the largest accounts. We’re looking for the 80/20 rule. Is 80% of the revenue generated by the top 20% of accounts? After customer concentration, we’re focused on retention rates and whitespace opportunities. Can we effectively retain the customers that we ‘land’ and do we have the potential for up- or cross-sell? These simple metrics will help define the account manager and customer success selling motions.

Sample Metrics:

  • Revenue concentration within top 20% of customer
  • % of the revenue generated by each customer segment
  • Customer retention rates
  • Whitespace opportunities 

5. Getting the Most out of Your Sales Talent – The first four elements of our model focus on how we handle leads and customers to hit the number. The next set of data factors transition into the sales support elements of your sales model. The first factor is focused on how you’re maximizing your sales talent. To make your budget, you’re going to need to field a full team. This is why we obsess over the number of field rep jobs open. Too often the number one indicator of success is simply whether or not you have enough coverage.

Beyond open seats, what’s your current coverage both on a geo and account basis? What are the ratios for lead developers / hunters / farmers / technical sellers? These ratios will also help reveal whether you have enough coverage to make the number.

Talent effectiveness also includes how much we’re spending on technology, tools, and training to enable our teams. These are the metrics that often deliver eye-popping reactions when teams realize what they’re spending on ‘enablement’ for a dubious return.

Sample Metrics:

  • % of open field jobs
  • Rep Coverage
    • Customers per rep
    • AEs / AM / SC / SDR
  • Turnover rates
  • New hire Ramp time
  • Tenure of reps
  • Budget on sales tools
  • Training/enablement spend per rep

6. Sales Management Effectiveness – Maybe the most critical part of the model is the effectiveness of sales management. This role is responsible for ensuring that pipeline coverage exists and that deals are forecasted accurately. In addition, you need to understand how they’re spending their time. Maximizing front-line manager coaching time has a demonstrative impact on results. But for this role to be most successful, they need to have a manageable span-of-control. Our benchmarks show a significant correlation between span-of-control and overall team quota attainment.

Sample Metrics:

  • Pipeline coverage
  • Forecast accuracy
  • Span of control
  • Selling time vs. non-selling time

7. Leveraging Compensation Costs The final type of data to review relates to the compensation of the sales team. This data helps us understand the total compensation cost of sales and how on-target earnings compare to market. It also reveals how the compensation plan generates winners vs. losers. It’s also important to evaluate goal setting distribution and effectiveness. These metrics will help assess if and how the compensation plan may need to adjust each year.

Sample Metrics:

  • Total compensation cost of sales
    • Net New/Upsell
    • Retention
  • Rep Performance curve
    • % of reps in ‘win zone’
  • How does a $1 of revenue get paid out?
  • Quota size vs. performance

Move from Insight to Action 

While today's sales teams have massive amounts of data at their disposal, data collection is just the start. High-performing sales functions build dashboards with baseline data for these sample metrics. This baseline then helps leaders quickly diagnose gaps and prioritize needed interventions. This continuous review and action planning process becomes the standard sales leadership language. It is also at the core of building a truly accountable culture.

Contact us to participate in our next benchmark study and for more guidance on building a health score for your sales team.

Ralph Grimse

Ralph Grimse

Ralph is a partner with The Brevet Group, and for 20 years he has led sales performance teams in the United States and Asia. Recently he also served as a sales leader in both the media and technology industries. Ralph’s work has focused on a unique blend of management consulting and sales enablement to help companies execute their sales strategies. Prior to this role, Ralph was the APAC sales effectiveness leader at Mercer.