Sales Pipeline 101: Understanding What To Track

Written by
Tony Yang
Revenue Operations

Sales pipeline – analyzing your company’s sales motions, statuses of potential deals, and tracking them religiously is absolutely essential to the success of every B2B company, particularly those selling into the enterprise segment. This is because understanding your sales pipeline provides a view into how much potential revenue can be generated by the company in future. 

Knowing what pipeline metrics to track will not only help you determine where your company stands in terms of hitting your revenue targets, but it will also help identify where in the process you can speed up the sales velocity, uncover hidden pitfalls, and provide clarity on what to do next. 

If you’re new to B2B sales motions or to the revenue operations function, you may be wondering what you should be tracking in your dashboards and reports. Well, as a rev ops leader at several high growth startups in the past, here’s how I approach pipeline reporting.

Revenue Pipeline...or Highway?

A great analogy to help you understand your pipeline is to think of it like a highway...you know, the kind that you drive your car on. Here’s an illustration:

Highway On-Ramp = New Pipeline Additions

A potential sales deal or opportunity can be represented by a car (I’ll be using terminology commonly found in Salesforce such as “Opportunity” for this post, but many of these have similar terms in other CRMs such as “Deals” in HubSpot). You can think of the size of that deal or Opportunity Amount as how big that car is. 

Whenever a potential deal has been identified by Sales, an Opportunity record for that deal is created in Salesforce, and the overall pipeline is increased – i.e., new pipeline from newly created sales Opportunities. So, new Opps are cars going on the on-ramp to the highway.

The key metrics that I’d want to track here within a particular time period include:

  • # of Opportunities Created – Unless you have an Opportunity Stage 0 or 1 where it’s omitted from Pipeline, which I’ve used in the past for account planning purposes. If this is the case, then you’ll need to count the number of Opps that were actually added to your pipeline within the selected time period.
  • Total Amount Created – Or whichever relevant data field you use to track the size of the deal, which could be a custom field named “MRR” or “ARR” or “TCV”.

Optional, but very insightful data points that I typically like to track here are:

  • Summary of Opportunity or Amount by Type – It could be interesting to understand new pipeline adds by type of deal, i.e., net new, renewal, upsell, etc.
  • Summary of Lead Source or Primary Campaign – I vehemently believe that “first touch” or “last touch” that’s typically identified from these two data points provide a very incomplete picture for attribution, especially in the context of how Salesforce’s architecture was built...but if you must include some data point on where new opportunities “came from” then you can do a rollup from either/both of these data points.
  • Summary by Opportunity Owner – depending on how your sales organization is structured, it could be interesting to see a roll-up of who’s been creating the new deals. Of course, if your internal workflow isn’t where the person creating the opp record is the actual owner of the deal, then you’ll want to adjust your report accordingly. At one of my previous companies, for example, a sales development rep (SDR) who qualified a prospect in an initial discovery meeting is captured in a Lookup field tied to a new Opportunity record created by the Account Executive (AE) who owns that account. In that setup, I was able to run a report that shows not only which AEs created the most opportunities, but also the SDR who qualified the opps...which also made it easier to track SDR quotas and compensation!

Tracking pipeline additions is critical to know if you’re able to hit your future targets and whether or not you have a demand generation problem. If you’re starting to see a decline in new pipeline additions (i.e., new cars getting on the on-ramp) over time, you’ll begin to hear complaints such as “our sales pipeline is drying up”. Getting early indications on this will give you and your team a heads up on whether or not you’ll be able to hit your revenue targets two, three, four quarters from now depending on how long your typical sales cycles are.

Cars On The Highway =  Current Pipeline

At any given point in time, the total number of cars moving along on the highway represents all the open sales opportunities or deals that are still in play. The highway lanes can represent Opportunity Stages or sales forecast categories, such as “pipeline”, “best case” or “upside”, and “commit” or “in-blood”. If you’re unfamiliar with sales forecast categories, here is a good definition from Dana Thierren, who was formerly an analyst at SiriusDecisions/Forrester Research:

  • Pipeline – early stages of the deal.
  • Best-case or Upside –  the deal may close by the close date, given an ideal set of circumstances that the seller documents and shares during forecast meetings.
  • Commit – based on the seller’s best estimates, the sales process will complete by the close date reflected.

The key metrics that I’d track to understand current pipeline at a particular point in time are as follows:

  • Total Open Opportunities – exclude any open opportunities marked as “omitted”.
  • Total Pipeline Amount – sum of the Amount values (or MRR, ARR, TCV, etc. depending on which ones your sales organization is using) for all open opps. In other words, this is the total potential “worth” of all open opportunities in pipeline.
  • Velocity – what you want to know is the average amount of time it takes for opportunities to move from one stage or forecast category to the next. Think of this as the amount of time each of the cars stay in a particular lane before moving to the next one over. This requires that you timestamp each time the opps enter into a particular stage. There are a few caveats to keep in mind though, including 1) Opportunity Create Date (in Salesforce) may not be the appropriate first timestamp to use if the creation of an opp record is not always indicative of an actual potential sales deal (such as when you use a Stage 0 Opp that’s omitted from pipeline for a particular use case), and 2) your sales process needs to be robust enough where it’s highly unlikely that deals move backwards to previous stages in the sales cycle. If you do see a tendency for opps to move backwards to previous stages, you’ll want to run a report to keep track of this. Perhaps in a future post I will write about using validation rules and workflows to keep this from happening.
  • Average Amount –  average of the Amount values (or MRR, ARR, TCV, etc. depending on which ones your sales organization is using) for all the opportunities in open status (and excluding those as “omitted”).  To carry on with the highway analogy, this is the average size of the car on the highway. This is an interesting metric to track as a snapshot over time, especially if you’re evaluating strategic initiatives such as going up-market to  enterprise.

Optional, but a couple of very insightful data points that I also like to track here are:

  • Average Age by Amount – if you do a cut of your average amount by velocity, you can get a sense of how fast deals typically progress depending on the size of the deal. It may be helpful to group the opps by Amount buckets, such as calling opps worth a certain high amount as “enterprise” and lower amounts to “mid-market”, “commercial”, and “SMB”.
  • Average Amount by Owner/Rep – useful because it shows which rep owns large chunks of pipeline. This data point, paired with metrics below pertaining to closed won/lost rates by rep can help your sales leader know how to manage and coach her team as well as get a better grasp at forecasting.

Many consider it a rule of thumb to have Total Pipeline Amount equal to 7-8X of your target bookings at any point in time...i.e., if you are planning on booking $1M in ARR this quarter, you should have $8M in total pipeline now. Personally, I prefer to look at the historical win rate percentage for deals in each forecast category and use that as the basis for any sort of coverage ratio to hit your target bookings number. For example, if you find from your historical data that you typically see a 33% win rate for deals that are later stages then you’ll want to have 3X the number of opportunities or pipeline amount for deals in these stages at any given time to ensure enough coverage to hit your targets. I find that it’s more accurate this way.

Brett Queener from Bonfire Ventures also gives an awesome breakdown of the forecast categories in part 2 of a 3-part article series on enterprise sales forecasting. In fact, all three parts of his post should be required reading for anyone in rev ops.

Highway Off-Ramp = Pipeline Removals

Cars that exit off of the highway represent deals or opportunities that become closed – both won and lost. These deals are no longer part of pipeline. In order to achieve revenue (or more accurately, bookings), the goal therefore is to get as many cars (deals) moving across the lanes to the off-ramp as closed won customers as quickly as possible.

The key metrics I like to track here for a time period that occurred in the past (such as last quarter or year-to-date) are as follows:

  • Total # of Opportunities Closed – remember, this number includes both closed won and closed lost deals so that you can get an accurate representation of all open pipeline by removing opps that closed out, both won and lost.
  • Total # of Closed Won Opps – subset of Total # of Opps Closed.
  • Total  # of Closed Lost Opps – subset of Total # of Opps Closed. 
  • Total Amount Closed – this is the aggregate number for Amount (or MRR, ARR, TCV, etc.) for both won and lost opps in the time period. In other words, this is the total potential “worth” of all opps that got removed from the pipeline in the given time period, whether you won them or not.
  • Total Amount Closed Won – subset of Total Amount (or MRR, ARR, TCV, etc.) Closed in the time period.
  • Total Amount/MRR/ARR/TCV Closed Lost –  subset of Total Amount (or MRR, ARR, TCV, etc.) Closed in the time period.

Now, you can (and should) dig deeper into a whole set of additional metrics to track for closed out deals. A few of these optional data points that I like to track here are:

  • Summary of Closed Lost Reason – a good follow-on data point to track for your closed lost opps would be the summary of closed lost reasons if you’re actively tracking this. Pro-tip: closed lost reason should not include an option that says “lost to competitor”. There could be a number of reasons that a prospect chose to go with a competitor instead of you, such as pricing, product features, compliance or security issues, timeline mismatch...whatever you and your sales team have identified as common reasons. These should be captured via a multi-select picklist. You should then identify the competitor chosen (if any) in a separate data field.
  • Summary by Closed Lost Stage – I’ve always found this to be an interesting report to keep track of because it’ll show me where in the sales cycle do we typically lose deals. To be more specific, this is the last stage a particular opp was in prior to it being moved over to closed lost.
  • Closed Won Opps by Owner/Rep – the total number of opps won by rep within the given time period.
  • Closed Won Amount by Owner/Rep – the amount of bookings won by rep within the given time period.
  • Closed Lost Opps by Owner/Rep – the total number of opps lost by rep within the given time period.
  • Closed Lost Amount by Owner/Rep – the amount of bookings lost by rep within the given time period.
  • Win Rate by Owner/Rep
  • Closed Lost Rate by Owner/Rep


Performance Reporting & Forecasting

Tracking and understanding the metrics above is super helpful for reporting on past performance. I’ve generally had to pull these data points when preparing for quarterly business reviews (QBRs) or board meetings. I’ll go more in-depth in a future post on how I structure my dashboards and reports – be sure to subscribe to this blog if you’re interested in reading it when it gets published.

In addition to tracking historical performance, the highway analogy helps you think about how to accurately forecast future revenue. Take a look at the image below: 


Let’s say that today you are about a month away from your fiscal quarter end. You’ve pulled all the above data to help you understand how you’ve performed in the past few quarters and quarter-to-date. Now, the metrics you want to examine to help you forecast the likelihood of hitting your revenue/bookings goals are as follows:

This Quarter:

  • Close Date = within this quarter.
  • Stage = in a final stage either 1 or 2 stages before Closed Won.
  • Category = Commit or Upside/Best Case.

To know how likely you are to hit your end of quarter bookings targets, you’ll want to look at all open opportunities that have Close Date set to this quarter. These are the cars in the final lane before going down the off-ramp within the near future. Obviously this is heavily reliant on accurate inputs for this field – I’ll cover automation/validation rules that can be set up to address this in a later post. Assuming that close date is within quarter and is in a final stage, the opp is probably categorized as Commit and thus is very likely to be booked as Closed Won soon. 

For any late stage opps closing within quarter that are categorized as Upside/Best Case, you’ll want to figure out what the outstanding requirements or risk factors are to understand why the rep considered the deal as Upside/Best Case for the quarter rather than Commit. 

If there are opps set to close this quarter but are in an earlier stage, check with the rep and sales leader to see if the opp is actually deeper in the sales cycle and just hasn’t been updated to the correct stage. I’d recommend setting up automation/validation rules to address this.

Exclude the opps that have close dates within quarter but are in an earlier stage and/or categorized as Pipeline. You can’t expect these cars to get off the highway in the near term if they are still in the farthest lanes from the off-ramp. Unless you have extremely short sales cycles, these clearly will not close within quarter. Again, this is also dependent on categorizing opps to the appropriate stage – for opps that had an unrealistic close date within the quarter but are in the correct stage, you’ll have to work with your sales leader and the rep on updating the close date appropriately (“hey, you’re not going to be able to exit off this next ramp, so think about the next few off-ramps you’ll be able to safely get off from”). As previously mentioned, understanding the amount of time the deals typically stay in each stage and the overall velocity of your deals will help you gauge how realistic the inputted Close Date really is.

Of course, your CRO or SVP of Sales should be managing all opps closely with her team to ensure no unexpected delays occur – having these metrics handy will help them tremendously.

Next Few Quarters:

  • Close Date = group by quarters in the future.
  • Stage & Age = appropriate stage according to expected close date based on typical sales velocity.
  • Category = Pipeline, or opps categorized as Upside (or even Commit) but got pushed.
  • Sales Qualified Leads (or whatever lifecycle stage you’re using right before opp/pipeline)

As you start to look further out, really understanding how your overall pipeline looks and behaves (i.e., the flow of traffic on the highway) will help you do a more accurate job of forecasting. More specifically, you’ll want to:

  1. Make sure that the deals in current pipeline have the appropriate stage and close date so that you can predict the likelihood of recognizing bookings by certain periods of time such as next quarter or year-end. Analyzing the sales velocity and close lost rates will provide a clearer picture to this end;
  2. Keep a pulse on the upper funnel KPIs such as Sales Qualified Leads or any other “pre-opportunity/pipeline” prospects that are expected to come in over time. This is where collaborating with your demand gen and sales development teams are necessary so that together you can forecast the new opportunities needed to continually feed the pipeline. In fact, good demand gen leaders will likely have their own growth models built out with these metrics.

As you can see, understanding your sales pipeline is essential to maximizing your revenue potential and meeting your forecasts. The more you know about what’s going on within your sales funnel and company as a whole, the greater the insights you’ll have to make smarter decisions about how to move forward with your strategy or business.


Did you like this post and found it informative? If so, I would really appreciate it if you would share this to your network (i.e., LinkedIn, Twitter, Facebook, telling your mother…) using the share links on this page. Feel free to mention me @tones810 to share your thoughts on this topic with me – I’m always open to hearing other points of view and new ways of doing things!

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Tony Yang

Tony is a long-time marketer with over 16 years experience in B2B SaaS companies. While he started his marketing career at IBM, for the past 14 years he's been leading marketing and revenue operations at various startups, including Mintigo (acquired by Anaplan), Qordoba, and Conversion Logic (acquired by VideoAmp). He's been recognized as an ABM thought leader and speaker at past events including FlipMyFunnel and SiriusDecisions. In addition, he serves as a coach and mentor at several startup accelerator programs.

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