9 Sales Forecasting Metrics Sales Teams Need to Track and Report

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Michael Lowe
Director, Content Marketing, Clari



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Stylized illustration of magnifying glass overlapping a 3D bar chart and line graph

B2B organizations spend a tremendous amount of time and effort on figuring out how to best track sales forecasting metrics to accurately predict sales. Accurately predicting sales helps every organization determine growth strategies by identifying where to invest, when to transition funds from low-performing areas to better opportunities, and which of your team members stand out.

But what is the recipe to building a confident forecast? It comes down to tracking the sales forecasting metrics that matter most to your business.

Before we dive into the different types of sales metrics, let’s define what these actually are.

What are sales metrics?

Sales metrics are the data that represent a company’s, team’s, and individual’s performance. Organizations use sales metrics to gauge performance and progress towards overall goals. Without accurate sales metrics, organizations will fall behind in preparing for future growth, incentivizing and awarding reps, identifying pain points in the sales process, and, ultimately, create inaccurate sales forecasts. Just about every sales forecasting method relies on rigorous tracking of sales metrics to create accurate sales forecasts.

Why metrics matter in sales forecasting?

With so much to think about, it’s no surprise that 9 out of 10 sales organizations fail to have accurate forecasts within 5 percent. Yet so much rides on building out an accurate sales forecast. Why are sales metrics important for sales forecast accuracy? Metrics are the foundation that give revenue operations team visibility into whether a forecast is in line or off course in supporting business objectives.

Jeff Williams, Partner at Bain Capital, explains how he used a specific set of metrics to move ahead of the operating plan on their way to one of the most successful IPOs of 2013.

This makes the importance of accurate sales metrics critical. Undisciplined forecasting leads to things like missed quarters, unknown close dates, and unpredictable growth. When you use inaccurate sales metrics, you run the risk of impacting several internal functions, leaving teams to feel the brunt and having to clean up the mess.

  • Sales: If the sales team is inaccurately tracking performance, they could be building bad habits which can snowball into an increase in closed/lost deals.
  • Finance: When inaccurate sales metrics are used for forecasting, that could have consequences for overall company financial reporting and future funding opportunities.
  • Human Resources: Sales metrics help determine hiring needs — and without them, HR won’t know when and who to hire.
  • Marketing: The marketing team could be building entire campaigns based off of bad metrics or missing out on opportunities to build awareness in new undetected areas.

There’s no denying that a lot of sales teams are under constant pressure to meet their numbers and having reliable data plays a huge role. In fact, Clari found that 4 out of 5 sales teams have had more than 10% of their committed deals slip out every quarter. This is where revenue operations teams can make a difference.

Revenue operations teams define and use better, more consistent processes and tools across the organization; eliminating disconnection, silos, inefficient sales processes, pipeline blind spots, inaccurate forecasts, wasted time, interrogations and finger pointing.

For a successful revenue operations team, sales, marketing and customer success must come together to analyze sales metrics and hold each other accountable. If you're a sales leader at your organization, you can start the conversation to shifting to a revenue operations team rather than everyone operating in silos.

What are the key metrics used in forecasting?

Depending on the maturity of your sales team, you may be more or less advanced in your sales metrics tracking. We’ve broken down our 9 sales metrics for sales forecasting into the following categories:

These forecasting metrics are critical to track through sales reports and dashboards regardless of which sales forecasting method you are using. Take a look below.

The 3 basic sales metrics for sales forecasting

These are the foundational sales metrics for sales forecasting that most (if not all) revenue teams should be thinking about. They help define the revenue target and team’s progress throughout a time period.


A sales quota is the overall sales goal for any given period of time across the entire sales organization and individual reps. For example, the overall sales quota for the quarter could be $1.2 Million. Individual reps are each responsible for a different sized chunk, depending on factors including seniority and position (SMB, enterprise).

Having a solid sales quota lays the groundwork for all other sales metrics and overall sales forecasting success. If your team doesn’t know what their goal is, how are they ever going to hit or exceed it?

You can’t forecast a quarter and know what percentage you are to hitting your goals if you don’t have a goal to begin with. A sales quota can be used as a motivational force at an organization as the team can rally around a number, with compensation tied to hitting or exceeding that quota.


Attainment is the tracking between sales quota and what was actually closed. This important metric is not only used to measure closed deals against goal, it's also used to identify reps on your team in need of coaching or more direction or possibly even highlighting the need for a team structure change.

Measuring attainment is important because it helps you understand what team members might need help, and it’s also important to measure attainment throughout the entire quarter — not just during the beginning or the end. The fifth day of the quarter is going to be much different than the 85th day of the quarter. However, you should track it day by day to make sure your team is closing consistently across the quarter. If you identify reps that are in need of support early enough, you have a better chance of getting them back on track.

You measure attainment by looking at an individual’s overall quota goal for the quarter and measuring what percentage of that they’ve closed over a given period.

Pipeline Coverage

Pipeline coverage is the total amount of all your sales opportunities compared with your quota. For example, if your goal is $1 million and you have $1 million of pipeline, you have 1X pipeline coverage. In that situation, you’d need to close every dollar in every opportunity to make your quota. On the other hand, if you had $3 million in pipeline, you’d have 3X pipeline coverage.

Pipeline coverage is important because it tells you how much of a buffer you have to hit your number. More pipeline means more wiggle room if deals get pushed out or reduce in size.

Track how much pipeline you historically need to hit your target will give you a better sense for how much pipeline you need in the future. More on that in the next section. Here’s a quick video from our team on what pipeline coverage is, typical benchmarks and how we think about pipeline.

The 3 next-level sales metrics for sales forecasting

More mature teams may want additional data points for increased sales pipeline visibility and insights.

Historical conversions

How can historical forecast data improve current forecasts?

Historical conversion is the measurement of how many prospects a team or individual were able to convert over a given period of time. Tracking historical conversions give you a better understanding of what your team members are capable of in the future — and how much pipeline coverage you need to generate to hit your number.

Historical conversions can be measured across the entire team, an individual, and across each phase of the sales process. What’s the historical conversion from an inbound MQL to a closed/won? What’s the historical conversion from an outbound prospect to a closed/lost? Historical conversion is all about using real past data to predict the future.

Having historical conversion data is absolutely critical to an accurate and attainable sales forecast. “There's wiggle room on every side and a lot of it has to do with deal execution,” says Kyle Coleman, Director of Sales Development and Enablement at Clari. “Let’s say your sales process is really efficient and your sales team is really humming and they’re closing every dollar that they qualify. They don’t need 3X coverage. They could get away with 1.5 or 2X coverage. On the other side of that coin, if your sales team is operating inefficiently and closing suboptimally, then you might need 4 or even sometimes 5X coverage.”

Activity data

Sales activity data is any given activity performed by sales or marketing to close a prospect. Sales activity data can include phone calls, emails, ads, blog reads, ebook downloads, direct mail campaigns, and really any other activity performed by your team throughout the sales process.

Sales activity shows you what’s actually happening in the days, weeks and months leading up to a sale and what pieces of content or marketing materials resonate with real buyers. You must measure activity data to understand how your team actually got the number of closed deals at the end of a quarter.

Teams use sales activity data to improve the effectiveness of the entire sales process. For example, if you send a one sheeter to a prospect, how often do they close? How many people closed who watched your webinars last year?

While typical organizations have entering activity data as part of the sales process, it can be hard to actually extract insights from your data. The CRM where this data is collected has its limitations, because it requires sales reps to manually add or update their information, it’s not always kept up to date. This is what makes an AI-backed system like Clari critical for accurate sales forecasting because you can automatically track activity data without manual work, saving reps time and delivering a complete data picture.

CRM Score

One way to really leverage the power of data science for accurate sales forecasting is with a CRM Score. With Clari, your CRM Score is generated using machine learning and AI-based analysis to measure data from historic wins and losses to identify which current deals have a higher likelihood of closing.

This gives you a chance to find the deal most at risk or that need the most attention so that the proper amount of coaching and strategy is put in place. The CRM score lets you see how long it takes or is expected to take to close a deal as well.

By cross-referencing your CRM Score with activity data, you can get a good sense of how a deal is actually tracking, whether it will actually close and how that will affect your forecast. Here are a few scenarios:

If a deal’s CRM Score is high and there is a lot of sales activity data, odds are the deal will close

If a deal’s CRM Score is high, but there is not a lot of sales activity data, you may want to check with your rep to better understand why the prospect is unresponsive and whether or not the deal is tracking properly

If a deal’s CRM Score is low, but there is a lot of sales activity data, it could be a sign the rep is spending too much time on a deal that won’t likely close. It’s a good opportunity to pressure test the deal and determine if the rep should cut bait and spend their time elsewhere.

Here’s how we use the CRM Score and Sales Activity Data to inspect the health of our deals at Clari.

The 3 advanced sales metrics for sales forecasting accuracy

For the most advanced sales organizations, these sales metrics provide another level of visibility into what’s happening in the forecast.

Sales Linearity

We like to define sales linearity as deals closing in a predictable pattern on a week-to-week and month-to-month basis throughout the quarter. Rather than deals closing in a chunk at the end of the quarter as reps rush to make their numbers, sales linearity is the practice of setting up and nurturing opportunities in a way that closes business regularly throughout the quarter.

Sales linearity isn’t just about closing deals consistently. If you can implement a strategic, linear sales process at your organization, your sales forecasts are more likely to be accurate and even keel. Sales linearity is crucial for improving sales predictability, which allows companies to have firmer control of their overall organizational health.

When it comes to driving accurate sales forecasts, having a linear sales process is critical. You want to be able to consistently close deals, not have to offer discounts or rush a closing process to ensure you hit your forecasts at the end of a quarter.

Of course it’s not always easy to get reps to close their deals before the end of the quarter, so consider strategizing with them and providing incentives.

Deal Slippage

When a deal doesn’t close within the committed timeframe, we consider that a slipped deal. TO find your slip rate, take the percentage of deals that were once committed but failed to close within the forecasted period.

Why is this important? First of all, having the ability to identify slipped deals means you can track them down in the next quarter and close them. These should be the first your team focuses on. But beyond that, knowing your slip rates can provide you with some level of predictability to your sales forecast.

Here’s the truth: Everyone slips deals. But if you can track your slip rate and determine how consistent it is quarter after quarter, you can plan for it, work that into your forecast and have a backup plan on standby.

Next quarter pipeline

Most sales teams focus their time, energy and attention on executing the current quarter deals to hit their number. However, once the current quarter comes to a close and the next quarter starts, it can feel like starting from scratch every single time.

Some of the most advanced companies we work with spend at least half of their quarter looking at out-quarter sales metrics. Okta, for example, developed a new meeting cadence to support its aggressive growth plans and an upcoming IPO.

Instead of following a weekly forecast plan that focused on the current quarter, they alternated between current quarter forecast and out-quarter forecast. On the out-quarter weeks, anyone involved in demand generation was invited to attend, including regional sales leaders, marketing, SDRs, partners, etc… and the regional sales leader would discuss whether there was enough pipeline or not. If not, a plan would be created.

Next quarter pipeline is an advanced level sales metric that the most sophisticated teams use to ensure predictable revenue in that out-quarter cadence. Ideally, revenue teams should know exactly how much pipeline coverage they need to generate throughout the current quarter to be able to start next quarter in a solid place that will allow them to hit their number.

Identifying next quarter pipeline targets is slightly different than knowing how much pipeline coverage you need to start the quarter. Here’s the difference:

Let’s say that based on historical sales data, we know for a $1 million quota, we need to start the quarter with $3 million in pipeline. Let's say it's the start of Q1. While we're focused on hitting our Q1 quota of $1 million, we also know we have a Q2 quota of $2 million, which requires $6 million in pipeline.

This means we are ideally not just closing deals to hit the Q1 quota, but also building pipeline to hit the Q2 quota.

Here’s the twist: The most sophisticated teams know at certain points in Q1, they need to be hitting next quarter pipeline (Q2) targets — portions of that $6 million in coverage. For example: By Week 4 of Q1, they might know they need to hit $2 million in pipeline for Q2 in order to put themselves in position to eventually hit $6 million pipeline target.

By establishing next quarter pipeline targets based on historical data, you’re giving your sales team time to develop your coverage, instead of waiting until the end of the quarter when you may be forced to scramble to find pipeline.

How to gather and organize sales metrics and KPIs

Sales forecasting metrics can be a valuable source of information, allowing you and your team to improve forecast accuracy and execution throughout the quarter. Start by identifying where your organization is on their sales forecasting journey and, depending on what you need, identify tools to help automate and provide more intelligent insights.

A few options:

  • Spreadsheets. While almost universally available, spreadsheets can pose a challenge when tracking sales forecast metrics. First of all, it’s hard to trust the data. Even if your rep are diligent about updating every field, by the time you configure your rows and columns, there’s a very good chance your numbers have already changed. Plus, spreadsheets are time-consuming and inefficient.
  • CRM. Existing CRM tools provide a system of record to manage account and transaction information. While the CRM is an essential system of record for business, it wasn’t designed to manage the modern revenue process and the sales reports you pull from CRM are often outdated. CRM systems rely on manual data entry and are rarely up-to-date or accurate and depend on static, ERP-era designs that can’t adapt to changing business initiatives of modern revenue organizations.
  • Clari. Clari works alongside your CRM to automatically capture sales activity data and snapshots the history of every single field in your CRM and maps all your sales activity to provide predictive insights about your deals, reps, and the forecast that are based on historic patterns and past conversion rates.

The cumbersome approach of manual data collection and entry, while the status quo, is outdated. This is why you should be asking what tools are available to automatically capture these sales metrics? How can you achieve more accurate sales forecasting using software/tools/process? How does accurate data improve a sales forecast?

You can continue asking questions to help you gather and organize accurate sales forecasts. Need more hands-on assistance? Reach out to the Clari team today to learn about the untapped potential of your sales data.