26 sales metrics successful sales teams are tracking in 2025

Think of metrics as a report card for your sales team. In school, your report card could spell the difference between whether you get rewarded with a new video game for straight A’s or find yourself spending Saturday mornings with a tutor because of that C- in math.

The same goes for sales metrics. A high win rate might mean it’s time to celebrate and scale successful strategies, while a low rate in pipeline velocity could signal the need for immediate coaching or process improvements. However, unlike school report cards, sales metrics can predict future outcomes and help you course-correct before it’s too late.

This article will cover everything you need to know about sales metrics, from the top 26 metrics to track, how AI plays a part, and how solutions like monday CRM turn data into action.

What are sales metrics and why do they matter?

Sales metrics are sets of data that organizations use to track performance, both for teams and individuals. Sales metrics help team leaders track progress against set goals and identify strategies that either need improvement or that have proven to be successful.

Tracking sales productivity metrics is important to understand what’s working in your sales funnel.

Additionally, sales managers can use data gathered from sales metrics to set compensation or incentives that help boost revenue growth.

Sales metrics vs. KPIs: What’s the difference?

Sales metrics and KPIs (Key Performance Indicators) are often used interchangeably, but they serve distinct purposes. Sales metrics are raw data points that measure specific activities, like the number of calls made, emails sent, or deals closed. KPIs, however, are strategic measurements that are directly tied to your specific business goals, such as revenue growth rate, customer acquisition cost, or sales conversion rates.

While all KPIs are metrics, not all metrics qualify as KPIs. The key difference is that KPIs align with broader business outcomes, and sales metrics don’t necessarily need to align with broader company goals.

Tracking every stage of your sales funnel and pipeline

Sales metrics aren’t just something you glance at after a deal wraps up. To really reap the benefits of monitoring sales metrics, it needs to be done at every stage of your sales funnel. Without keeping tabs on everything from your initial leads all the way through to closed revenue, you’re operating in the dark and likely missing out on opportunities to make improvements to your pipeline and double down on what’s crushing it.

Let’s say a SaaS company brings in 1,000 leads in a month. Of those, 200 become qualified prospects, 100 book demos, and the company closes 25 deals. Suddenly, the demo-to-close rate tanks, and the company needs to understand why. Maybe it’s the pricing, or your sales reps aren’t following up in time. Whatever the reason, without tracking metrics in each step of the sales funnel, it would be much harder to nail down why revenue dropped, and the team would spend a lot more time and resources figuring out where to start fixing things.

26 essential sales metrics to track

When it comes to tracking sales metrics, there are three main categories that give you the full picture:

• Sales activity metrics, which track what your team is actually doing day-to-day
• Sales performance metrics, which look at how well those activities are converting
• Customer satisfaction metrics, which track whether you’re keeping customers happy

Together, these three help sales teams understand not just whether they’re hitting numbers, but what they can do to keep improving. In addition to these three types of sales metrics, it’s also important for sales leaders to track sales employee metrics to understand factors that can impact performance, onboarding, or goal attainment.

Below, we’ll look at 26 different sales metrics spanning each category that are important to track to build and maintain a successful sales strategy.

Sales activity metrics

1. Number of calls made

What it measures: The total number of outbound calls made by sales reps in a given period.

Why it’s important: High call levels typically lead to better results, and this metric helps managers identify reps who might need coaching on activity levels or time management.

Formula: Total outbound calls ÷ time period

2. Email open rates

What it measures: Email open rate measures the percentage of sent emails that are opened by prospects.

Why it’s important: Shows how well your subject lines and sender reputation are performing, helping teams optimize outreach effectiveness before prospects even read your message.

Formula: (Number of emails opened ÷ number of emails sent) × 100

3. Email response rate

What it measures: The percentage of sent emails that receive a response from prospects.

Why it’s important: Indicates the quality and relevance of your email content, helping you refine messaging to generate more engagement and conversations.

Formula: (Number of email responses ÷ number of emails sent) × 100

4. Meetings booked

What it measures: The number of qualified meetings or demos booked with prospects.

Why it’s important: This bridges the gap between initial outreach and serious sales conversations, showing how well your prospecting efforts convert to real opportunities.

Formula: Total meetings scheduled ÷ time period

5. Follow-ups sent

What it measures: The number of follow-up touchpoints completed after initial contact.

Why it’s important: Most deals require multiple interactions to close, so tracking follow-ups ensures prospects don’t fall through the cracks while measuring rep consistency.

Formula: Total follow-up activities ÷ time period

6. Social media interactions

What it measures: The number of meaningful interactions with prospects on social platforms.

Why it’s important: Modern buyers research vendors online, so social engagement helps build relationships and credibility before formal sales conversations begin.

Formula: Total social interactions (likes, comments, shares, messages) ÷ Time period

Sales performance metrics

7. Lead conversion rate

What it measures: The percentage of leads that convert to qualified opportunities.

Why it’s important: Shows how effectively your team qualifies prospects and identifies which lead sources produce the highest-quality opportunities for better resource allocation.

Formula: (Number of qualified opportunities ÷ total leads) × 100

8. Win rate

What it measures: The percentage of qualified opportunities that result in closed deals.

Why it’s important: Indicates overall sales effectiveness and helps identify coaching opportunities, while also informing more accurate revenue forecasting.

Formula: (Number of deals won ÷ total opportunities) × 100

9. Average deal size

What it measures: The average dollar value of closed deals over a specific period.

Why it’s important: Helps with revenue forecasting and identifies opportunities to increase deal values through upselling, cross-selling, or better positioning.

Formula: Total revenue ÷ number of deals closed

10. Sales cycle length

What it measures: The average time it takes to move from initial contact to closed deal.

Why it’s important: Longer cycles can tie up resources and impact cash flow, so understanding this metric helps create systems to optimize processes and set realistic expectations.

Formula: Total days from first contact to close ÷ number of deals

11. Pipeline velocity

What it measures: How quickly revenue flows through your sales pipeline.

Why it’s important: Combines deal size, win rate, and cycle length to show the overall health and efficiency of your sales process.

Formula: (Number of opportunities × average deal size × win rate) ÷ sales cycle length

12. Monthly recurring revenue (MRR)

What it measures: The predictable revenue generated each month from subscriptions or recurring contracts.

Why it’s important: Provides a stable baseline for forecasting and helps track business growth trends, especially crucial for SaaS and subscription businesses.

Formula: Total monthly subscription revenue

13. Customer acquisition cost (CAC)

What it measures: The total cost to acquire one new customer.

Why it’s important: Shows whether what you’re spending on sales and marketing is sustainable and helps determine pricing strategies and budget allocation.

Formula: (Total sales and marketing costs) ÷ number of new customers acquired

14. Year-over-year growth

What it measures: The percentage increase in revenue compared to the same period in the previous year.

Why it’s important: Shows long-term business trajectory and helps identify seasonal trends while providing context for performance beyond short-term fluctuations.

Formula: ((Current year revenue – previous year revenue) ÷ previous year revenue) × 100

15. Weighted value of pipeline

What it measures: The total potential revenue in your pipeline adjusted by the probability of each deal closing.

Why it’s important: Provides a more realistic forecast than raw pipeline value by accounting for deal likelihood, helping with resource planning and revenue predictions.

Formula: Sum of (deal value × probability of closing for each opportunity)

16. Average profit margin

What it measures: The percentage of revenue that remains as profit after subtracting all costs associated with generating that revenue.

Why it’s important: Shows the actual profitability of your sales efforts and helps identify which deals, products, or customer segments are most valuable to the business.

Formula: ((Revenue – total costs) ÷ revenue) × 100

Customer satisfaction metrics

17. Net promoter score (NPS)

What it measures: Customer loyalty and likelihood to recommend your product to others.

Why it’s important: Predicts customer retention and organic growth potential, while identifying customers who might churn or become advocates.

Formula: % of promoters (9-10 ratings) – % of detractors (0-6 ratings)

18. Customer satisfaction score (CSAT)

What it measures: How satisfied customers are with your product or service experience.

Why it’s important: Direct feedback on customer happiness helps identify improvement areas and correlates strongly with retention rates.

Formula: (Number of satisfied customers ÷ total survey responses) × 100

19. Customer retention rate

What it measures: The percentage of customers who continue using your product over a specific time period.

Why it’s important: Retention is cheaper than acquisition and indicates product-market fit, helping predict long-term revenue stability.

Formula: ((Customers at end of period – new customers) ÷ customers at start of period) × 100

20. Customer lifetime value (CLV)

What it measures: Customer lifetime value measures the total revenue expected from a customer throughout their entire relationship with your company.

Why it’s important: Helps determine how much you can spend on acquisition while informing customer success investment decisions.

Formula: Average order value × purchase frequency × average customer lifespan

21. Churn rate

What it measures: The percentage of customers who stop using your product or unsubscribe from your services in a given time period.

Why it’s important: High churn indicates product or service issues and directly impacts revenue growth, making it essential to identify at-risk areas.

Formula: (Number of customers lost ÷ total customers at start of period) × 100

22. Renewal rate

What it measures: The percentage of customers who renew their contracts or subscriptions when they expire.

Why it’s important: Critical for subscription businesses, such as SaaS companies, as it directly impacts recurring revenue and shows customer satisfaction and product value.

Formula: (Number of customers who renewed ÷ total customers up for renewal) × 100

Sales employee metrics

23. Employee turnover rate

What it measures: The percentage of sales team members who leave the company within a given time period.

Why it’s important: High turnover disrupts revenue flow and increases hiring and training costs, so this metric helps track team stability and employee satisfaction.

Formula: (Number of sales reps who left ÷ Average number of sales reps during the period) × 100

24. Coaching impact score

What it measures: The improvement in performance after targeted coaching sessions.

Why it’s important: Provides proof of coaching effectiveness and helps managers refine training strategies for maximum impact.

Formula: ((Post-coaching performance – Pre-coaching performance) ÷ Pre-coaching performance) × 100

25. Rep engagement score

What it measures: The overall engagement and morale of the sales team, typically gathered through surveys or performance tracking tools.

Why it’s important: High engagement usually means lower turnover and better performance, so this metric gives managers insight into team health and potential burnout risks.

Formula: (Total engagement points ÷ Total possible points) × 100

26. Average time-to-hire

What it measures: The average number of days it takes to fill a sales position, from job posting to offer acceptance.

Why it’s important: A long hiring cycle can lead to lost revenue opportunities and increased strain on existing team members. Tracking this metric helps identify bottlenecks in the recruiting process to improve hiring efficiency.

Formula: Total days to fill all open sales positions ÷ Number of positions filled

Sales metrics and AI: A powerful partnership

While any of the sales metrics mentioned above can give you important insights into past performance, artificial intelligence takes your reporting a step further by also giving you predictions on how certain metrics can be expected to perform.

For example, an AI-powered platform teams use to track metrics, like monday CRM, can offer predictions on customer churn. By analyzing things like historical patterns of customer churn rates along with current data like customer engagement rates and sentiment analysis of recent interactions, your CRM can forecast future churn rates. This way, teams can intervene early to counteract behavior that often precedes customers leaving, and essentially improve the customer churn rate in the long run.

Aside from predicting specific metrics, AI also goes a long way in helping teams automate critical insights. Instead of manually sifting through mountains of data to spot trends, AI can instantly flag when performance deviates from expected patterns or highlight opportunities for improvement. This gives sales teams more time to spend on selling and building relationships instead of analyzing data.

Leading indicators vs lagging indicators in sales

When tracking sales metrics, it’s important to understand the difference between leading and lagging indicators. Both tell completely different stories about your sales performance and require different approaches.

• Leading indicators predict the future so that teams can adjust in real time. These include activities like the number of calls made, emails sent, meetings booked, and follow-up activities. If you see your leading indicators dropping, you can immediately adjust activities to get back on track.
• Lagging indicators show the results of past actions and can’t be changed once they’ve occurred. These include things like sales cycle length, win rates, and customer churn. While you can’t control these metrics, they still help teams understand whether their strategies are working and provide historical data to inform future decisions.

The magic happens when you track both together. Leading indicators help you make meaningful changes in real time, while lagging indicators validate whether your efforts are paying off.

How to measure sales metrics in 7 steps

Now that you have a full picture of all the different types of sales metrics, you may be wondering how to actually put them into practice. Sales metrics require ongoing monitoring, which means you need a specific process in place to first establish the metrics you want to follow and then see them through to the result. Here are some quick steps you can take to start measuring sales metrics.

Step 1: Define your sales goals and objectives

Before diving into metrics, get crystal clear on what you’re trying to achieve. Are you focused on increasing revenue, improving conversion rates, or reducing customer acquisition costs? Your goals will determine which metrics matter most.

Step 2: Start with a few key metrics

Pick a mix of leading and lagging indicators that directly tie to your goals. Consider starting with the basics like win rate, sales cycle length, and lead conversion rate, then expand as you get comfortable.

Step 3: Choose the right tracking tools

Look for an analytics tool, like CRM software, that can capture, store, and analyze your data. Prioritize solutions that integrate with your existing tech stack and that can automate data collection to cut down on manual work for your team.

Step 4: Establish baseline measurements

Gather at least 3-6 months of historical data to understand current performance levels. This gives you a realistic starting point and helps you set achievable targets.

Step 5: Set up regular reporting cadences

Create daily, weekly, and monthly reporting schedules. Daily reports should focus on activity metrics, weekly on sales pipeline metrics and movement, and monthly on broader performance trends and goal achievement.

Step 6: Train your team

Ensure everyone understands not only how to correctly input data, but also why each metric matters and how they connect to individual and team success.

Step 7: Review and optimize regularly

Schedule quarterly reviews to assess which metrics are driving action and which aren’t adding value. Swap out metrics that aren’t helping you reach your goals or adjust targets based on what you’ve learned.

Dashboard deep dive: Creating a sales metrics report

There are endless configurations for sales dashboards that will help you visually track metrics. However, before you even think about what you want included on a dashboard or in sales metrics reports, you first need to decide on the software you want to use to track it all. A visual solution like monday CRM can help teams track and visualize metrics in real time and even apply AI insights for deeper analytics.

Sales teams can also have different dashboards and reports to serve different purposes. For example, some of the dashboard configurations you might consider implementing include:

• Sales leaderboards with real-time deal closure metrics such as win rate, meetings booked, and MRR
• Sales activities dashboard that shows emails sent, number of calls made, and follow-ups sent
• Performance overview dashboards that include a mix of different metrics, like revenue, deals in a pipeline, conversion rate, and forecasted deals
• Sales manager dashboard that shows daily, monthly, or quarterly sales performance, MRR, sales target progress, new accounts, and more

Leveraging monday CRM for sales metrics that drive growth

While there are standalone analytics platforms teams can use to track sales metrics, opting for an all-encompassing solution like an AI CRM can turn simple metrics into actionable strategies. With a platform like monday CRM, teams can not only track and visualize key metrics in real-time, but also use the information to instantly improve pipeline management, team performance, and sales rep productivity.

Packed with advanced CRM automation and AI features, monday CRM can help teams update deal stages, assign tasks, and send automated notifications based on data. The platform’s AI capabilities can help teams analyze sales data and predict future performance to identify opportunities for improvement.

Let’s take a closer look at some of monday CRM’s key features for using sales metrics to improve efficiency.

Customizable AI-driven dashboards

With monday CRM, sales teams can build and customize their own sales dashboards that display essential data in real-time. To give them even more of a boost, dashboards can pull AI data such as sales forecasts and predicted sales to give teams more insights into goal attainment and deals in the pipeline.

Predictive analytics and sales forecasting

Sales teams can make the most of predictive analytics and sales forecasting tools in monday CRM. These metrics help teams understand where to focus both their efforts and resources, whether it’s a deal that’s at risk of falling through or incoming prospects that have a high likelihood to convert based on historical trends.

AI-powered pipeline management

The metrics you track in monday CRM can be used to create AI-led automations in your sales pipeline. For example, if your sales cycle length metric shows a deal has been stuck in the same stage for longer than your average cycle time, the system can automatically assign a follow-up task to the right sales rep and notify the sales manager to intervene.

AI customer sentiment analysis

When it comes to customer satisfaction metrics, sometimes numbers alone aren’t enough. With monday CRM, teams can track sentiment from email chains, meeting notes, and call logs to uncover further insights about how a customer really feels. For example, if sentiment analysis detects negative language patterns in recent customer communications while their CSAT scores remain average, the system can automatically create a task for the sales rep to schedule a check-in call before potential issues escalate.

Turning metrics into results

Tracking the right sales metrics is essential for driving growth, but the real power comes from turning that data into action. By focusing on a balanced mix of activity, performance, and customer-focused metrics, teams can optimize processes for a smoother path to success. With monday CRM’s AI-powered analytics, predictive forecasting, and automated workflows, sales teams don’t just track metrics, they transform them into competitive advantages that lead to sustainable revenue growth.