As the old adage goes: You can’t manage what you don’t measure. In sales, accurate measurements could mean the difference between hitting your number or coming up short. This is where sales metrics and sales analytics come in. Without them, you’ll be left in the dark when it comes to leading your revenue team to success.
Thanks to powerful, AI-based solutions, we now have more sales data than ever at our fingertips—but just having access to sales metrics isn’t enough. Knowing what to measure and how to interpret the results is key.
What is sales analytics?
Sales data analytics is the review of sales data, metrics, and trends to gain insights that can improve sales team performance, sales productivity, and sales effectiveness, help drive accurate sales forecasts, and refine the overall sales process.
How can sales analytics improve sales performance?
Sales analytics improves performance by revealing the strengths and weaknesses of individual sales reps and the sales team as a whole, thereby allowing sales managers to tweak behaviors and sales strategy to ensure success. This is beneficial on the macro and micro levels.
Sales analytics at the sales rep level: Focusing on the data makes sales reps accountable and provides managers with prime coaching opportunities based on metrics, grounding conversations in data instead of opinion.
Sales analytics at the sales process level: By offering insight and visibility into the sales process, sales analytics offers revenue leaders actionable insights into larger sales trends happening in sales cycles. Are deals taking longer to close? Are average contract values sinking? If so, how can you steer the team back on course?
What are the most important sales metrics?
Identifying the important metrics for your business and your team depends on key performance indicators that you identify as vital to your business model, such as selling motions, sales processes, sales cycles, and more. One way to identify your sales KPIs is to align them with your strategic growth initiatives. Here are a few examples:
Going up market. If you’re aiming for the enterprise sphere, you’ll want to see your average deal size and average revenue per unit increasing. This signifies larger deals from larger customers.
Rep attainment. If the goal is for all reps to meet quota, you may want to focus on activity metrics and performance indicators, such as emails sent, phone calls made, and meetings booked.
Scaling commercial or SMB markets. If your goal is to scale your commercial business, you may want to examine how to decrease the sales cycle length for this higher velocity portion of the business, while increasing average revenue per unit.
These are just a few ways to tie your sales metrics and sales analytics back to strategic revenue goals, which in turns starts with sales goals. The metrics you track are a means to that end goal, not the end themselves.
Here are 15 of the most critical sales metrics we recommend tracking for any revenue team:
- Annual Recurring Revenue
- Average Revenue Per User
- Quota Attainment
- Win Rate
- Conversion Rate
- Sales Cycle Length
- Average Deal Size
- Average Profit Margin
- Deal Slippage
- Churn Rate
- Net Retention Percentage
- Pipeline Coverage
- Sales Productivity Metrics
- CRM Score
- Sales Linearity
Annual recurring revenue, or ARR, is the total amount of contracted revenue that your company brings in each year. It’s a particularly crucial key performance indicator (KPI) to follow for any SaaS business that is subscription based, as it tells you how much money you can expect to receive from customers in a given fiscal year. When tracked historically, ARR can be used to evaluate a company’s growth and assist in long-term forecasting.
The ARR calculation:
Annual recurring revenue (ARR) = (total value of a contract) / (number of contract years)
For a 2-year annual contract totaling $50,000, the calculation would be $50,000/2 = $25,000. Add up the ARRs for each contract to calculate the total ARR. You can also look at ARR by product or region to gain insight into the performance of specific solutions or areas.
The same applies to monthly recurring revenue (MRR), which represents the total amount of contracted revenue your sales team expects to bring in each month.
For a license-based approach, there is an alternative formula that can be used if the contract includes variable revenue per year. For example when growth is baked into the terms, a $60,000 contract over three years could be $10,000 in year one, $20,000 in year two, and $30,000 in year three.
The Variable Revenue ARR calculation:
Variable Revenue ARR = Number of Active Licenses that Year x Average Revenue Per User (ARPU)
2. Average Revenue Per User / Average Revenue Per Account
Average revenue per user (ARPU) or average revenue per account (ARPA) refers to the amount of money that a company brings in per subscriber, user, or account in a particular time period. It is calculated by dividing the total amount of revenue for that time period by the number of subscribers, customers or accounts during that period:
The ARPU/ARPA calculation:
ARPU/ARPA = (total amount of revenue in given time period) / (average number of subscribers during that time period)
This KPI is helpful to track for a few reasons. If your ARPU is increasing, it’s an indicator that your revenue is holding value. You may be able to avoid steep discounts just to get customers on contract, or avoid scrambling to hit your number at the end of the quarter.
Identifying your highest ARPU customers may also give you an idea of your best product-market fit. For example, if you notice that cybersecurity and telecommunications firms are your highest ARPU clients, that may be a signal to double down in those segments because you know they’re willing to pay the asking price for the value your product brings them.
3. Quota Attainment
Quota attainment is exactly what it sounds like: the percentage of deals (either by number or by revenue) a sales rep has closed in relation to their set quota for a given time period. It can be measured per month, quarter or year, depending on you sales cycle.
The quota attainment calculation:
Quota attainment = (number of closed deals or revenue in given time period) / (quota for that time period)
This is an important sales forecasting metric to monitor in order to keep track of how deals have closed against targets, as well as to identify reps who might benefit from more coaching or guidance. Tracked over time, reps’ quota attainment percentages might even signal the need for team structure changes.
This number isn’t static throughout the month or quarter, so you should measure it at a consistent cadence during your rep/manager one-on-one sales meetings. This will also allow you to track whether your team is moving deals through the sales pipeline consistently throughout the current quarter and next quarter.
4. Win Rate
Win rate refers to the percentage of deals that are closed-won within a specific time period.
The win rate calculation:
Win rate = total # of won opportunities / total # of closed opportunities (both won and lost)
Analyzing how the win rate changes over time can help you gauge your sales reps’ performance, as well as how much sales pipeline coverage you need to hit your sales targets. Segmenting win rates by product, team, marketing campaign, or other factor can offer insight into each factor’s variations in performance.
5. Conversion Rate
In sales, the conversion rate refers to the number of qualified leads that result in closed-won deals.
The conversion rate calculation:
Conversion rate percentage = (# of leads converted into sales / total qualified leads)
When tracked over time, this key metric can measure how well your sales team turns leads into new customers and it can improve the overall quality of leads by aligning the sales and marketing teams. Monitoring conversion rates over time, and the characteristics of those leads, ensures that your company focuses on selling to relevant buyers and continues to grow.
For businesses with longer sales cycles and multiple sales stages, it’s beneficial to track the conversion rate between each stage. For example, how often do net new leads turn into sales qualified pipeline and how often does sales qualified pipeline turn into revenue?
Understanding these conversion metrics at each stage will help you continue to tighten your revenue machinery. If the historical conversion rate from net new leads to sales qualified pipeline is very low, you may need to consider fine tuning your top of funnel messaging or instrumentation to bring in a different cohort of leads with more specific qualifications.
Another twist to this is analyzing conversion rates by lead source. To get a sense of which sources tend to convert to new customers, which get stuck and which are lost, sales teams should track the origin of deals in the sales funnel.
6. Sales Cycle Length / Time in Each Stage
Sales cycle length refers to the average amount of time it takes for a new customer to move from the opportunity stage to a closed deal. Understanding this metric can help sales teams determine whether there are any bottlenecks in their sales process—which can not only delay deals but potentially lose them—and streamline the sales process moving forward for a better close rate and more accurate forecasts.
Sales organizations should also track the amount of time deals stay in each stage within the sales process. This will help them spot at-risk deals so they can determine whether the sales opportunities are stale and in need of purging or whether there are actions they can take to push them forward.
7. Average Deal Size/Average Selling Price
The average deal size or average selling price refers to the average dollar amount of each closed deal.
The ASP calculation:
Average selling price = (total $ of closed deals over a specific time period) / (total # of deals)
If a company closes three deals in a quarter, at $60,000, $60,000 and $75,000, the average selling price for that quarter would be $65,000 for that quarter.
This metric is indicative of your revenue teams’ ability to go up market and land larger deals. Is your message resonating with customers with bigger pockets? Are your sales teams able to manage complex sales cycles with larger price tags attached?
Average deal size should be tracked by total business for the given time period (monthly, quarterly, annually), as well as broken down by renewals and new deals to get an understanding of where the most profitable deals lie.
8. Average Profit Margin
Average profit margin measures, in essence, the pulse of your business. This KPI ultimately tells you how your company is doing.
Average profit margin is calculated by dividing your company’s net income by its net sales.
The average profit margin calculation:
Average profit margin = net income / net sales
To find your net income, subtract your company’s total expenses from the total revenue. Net sales is calculated by subtracting the total returns or refunds from total sales.
9. Deal Slippage
Deal slippage refers to the number of deals in the commit stage that fail to close within the forecasted range. If a deal is in commit for Q1, for example, but gets pushed to Q2 due to the project being stalled or budget freezes, that is considered a slip.
The misconception here is that any slippage is bad. The reality is, every company experiences deal slippage. The important thing is to know what your average slip rate is so you can prepare for it.
It’s possible to manually track slipped deals in spreadsheets or CRM, but new sales technology like Clari, allow revenue leaders to not only identify how many deals slipped and how much revenue they represent in real-time with just a few clicks of the mouse, but also which deals slipped and what you can do about it.
10. Churn rate
Churn rate refers to the number of your customers who either cancel or don’t renew their subscriptions during a specific time period.
The churn rate calculation:
Churn rate = number of churned customers / total number of customers
Customer churn is a critical metric to track for any business with a subscription model. If you’re losing customers as fast as you’re gaining them, your net growth remains at zero. This is the core reason protecting your customer base, providing fantastic customer experience, and continuing to innovate in order to provide value is so important.
Identifying accounts at risk of churning can be tricky and often require complex spreadsheets, but new sales technologies revenue teams more visibility into renewals at risk so they can take a proactive approach to preventing churn.
11. Net retention percentage
Given the continued market uncertainty these days, more and more businesses want to keep their current customer bases in an effort to maintain a level of stability. Net retention percentage goes hand in hand with churn rate, but with a slight twist.
The net retention percentage calculation:
Net retention percentage = (Renewal ARR + Upsell ARR - Churn) / (Target Renewal ARR)
Keep in mind that this isn’t a static metric, so you’ll want visibility into real-time renewal, upsell, and churn forecasts to help your sales and customer success teams achieve customer satisfaction and growth.
12. Pipeline Coverage
Pipeline coverage refers to the amount of opportunities you have in your sales pipeline to ensure you reach your sales target. Many organizations follow the 3 times rule, but how you calculate this ratio will depend on many factors, including your business segment, your product, the length of your sales cycles, and more.
In today’s uncertain economic climate, sales leaders would do well to monitor their late-stage sales pipeline coverage as well. This refers to the opportunities still in play near the middle and end of the quarter.
The pipeline coverage calculation:
Late-stage pipeline coverage = (Stage 2 deals + Pipeline $) / (Forecast $ - Closed $)
Knowing this number can help sales management course-correct fast to ensure an accurate sales forecast and successful quarter.
new COVID Revenue Impact Study, we found that organizations slipped 8% more late stage pipeline deals (stage 2 and above) compared to the same quarter last year.
13. Sales Productivity Metrics
Sales activity data includes any activity that any member of the revenue team engages in with a customer or prospect. It can include emails, meetings, calls, and marketing campaigns, for example. When this data is easily accessible and highly visible, sales teams can see whether a prospect is truly engaged and determine the health of the deal more accurately.
Tracking sales activity data not only shows you prospect engagement, but is also a way to gauge your sales performance metrics.
However, reliable sales activity data is notoriously hard to find because it requires manual data entry from your sales reps. Often that data is inaccurate, out of date, or missing. And who can blame them—reps want to , not enter data. New sales technologies are emerging that automatically track sales activity data, so it’s always real-time, accurate, and available from anywhere.
14. CRM Score
Clari’s CRM Score is an artificial intelligence-driven numeric value based on an analysis of historical data from opportunities, such as how long a deal has stayed in a given sales stage, whether the close date has been pulled in or pushed out, and whether the deal size has increased or decreased.
The CRM Score is one of many predictive analytics sales analytics tools that can help revenue teams identify the likelihood that a deal will close based on previous deals with similar behaviors, and can help leaders identify if a deal is at risk and where reps should spend their time.
A deal with a high CRM Score may require less attention than a deal with a low CRM Score. It’s a critical input for pipeline management. Here’s how it works as part of the 4-Point Deal Inspection.
15. Sales Linearity
Sales linearity is the steady and predictable pattern in which deals close throughout the quarter. The idea is that sales linearity helps avoid the end of quarter scramble to get deals in and make quota.
Ideally reps attain 20% of quota by the end of the first month of the quarter, 50% by month two, and 100% by the end of the quarter.
Best-in-class revenue teams strive to achieve this aspirational target for a number of reasons:
- Relief from heavy discounting at the end of the quarter just to make their number
- More predictable revenue, allowing more strategic and sound investments
- Better cash flow
- Customer success teams can plan onboarding resources to support new customers
The Challenges of Tracking Sales Analytics and Sales Metrics
Regardless of the priorities of your sales leadership, sales metrics should be monitored on a regular cadence. Reviewing any metric in a silo, once a quarter, will not give you the information you need to make better decisions. There has to be a disciplined approach to monitor the metrics and address what the data shows.
This requires a lot of analyst time to gather and prepare the data—especially if these metrics need to be updated daily. So how do you balance data freshness with analyst time in order to properly inform how revenue teams should execute?
Real-Time Revenue Operations with Clari
Best-in-class revenue teams use Clari to recognize risk and act on opportunity with real-time sales data analytics. With Clari, revenue teams:
- Automatically track sales activity data
- Spot risk in the pipeline and execute against it
- Get out-quarter visibility for more accurate forecasts
- Identify slipped deals and take action on them
- Combine every critical sales metric into a real-time sales dashboard
Interested in learning how Clari can help give you more sales team visibility with real-time sales analytics? Request a demo or message us to speak with one of our revenue experts.