What metrics to track in sales

There’s a ton of stuff you could track in sales. But most of it is just noise.

And if you don’t track it in the right way, you might actually set yourself up to be demoralized.

I see this happen a lot with founders. They look at MRR or ARR metrics, and it’s not where they want to be.

But they have no way of digging into the metrics to improve their sales process.

So they’re left with a sense of despair. A disconnect between ideal world and realistic state. And no real way to make it better.

So today we’ll go through what metrics to track between $20k-$200k+ MRR, and how to use those metrics to improve your sales process.

Here we go!

Table of Contents

• Sales as Math

  • Key Metrics

  • Benchmarks

• Building a Useful Dashboard

• What to do before $20k MRR?

Sales as Math

If you haven’t read Revenue Architecture (or formerly Sales as a Science series) by Jacco Van der Kooij of Winning by Design, I highly recommend.

He focuses on what’s called the bowtie metrics - where you have acquisition on the left, and retention/expansion on the right. The middle is the inflection point where you close deals.

I’ve implemented Jacco’s work at 3 different startups - one bootstrapped where we went from $200k ARR → 1.6M ARR in 18 months. One where we had a $6M ARR PLG motion and added a $3M ARR sales motion in two years. And another company where we were post IPO in a mature market.

This stuff works well, as long as you have some consistency in metrics. Before $20k MRR, it doesn’t matter as much.

Once you hit the $20k+MRR run, and trying to build profitable and repeatable sales motions, here’s the formula for each sales motion:

MRR = Volume of SQLs (intro calls booked on calendar) X Qualification Rate X Win Rate X ACV (average contract value)

And you stagger MRR by average sales cycle length.

You can apply the same formula before and after this part of the funnel - for Leads contacted X response rate X meeting booked rate. And you can do it for renewals and expansion as well.

But essentially, it breaks down sales into a formula (which I love, I’m a nerd).

And math can be manipulated.

Each piece of this formula can be mapped to key components of a sales process, key behaviours, skills, etc. We’ve gone through that a lot in previous newsletters and in the FOUNDER playbook.

So if you know these metrics, and you know which one is off, then you have a path to explore. You can go and check execution and come up with a fix pretty quickly. That’s a major advantage.

Key Metrics

So everyone pretty much tracks MRR or ARR, bookings, etc. That’s fine, but that’s a business-level metric. Meaning it’s a snapshot of how healthy your business was over the last 6-months of decision making.

And it includes product decisions, marketing decisions, sales decisions, etc.

So it’s really hard to look at MRR and know exactly what to do - there’s too much that goes into it.

So from a sales process standpoint, you want to start tracking the following:

• SQLs (Sales Qualified Leads) - these are meetings booked on your calendar with whoever is doing sales. They are not trials, they are not webinar signups, they are not MQLs. Those numbers are fun to track, but tell you little about future sales success. Your sellers need to be busy, with calls on calendar. Period. You want to track this number, and you want to make sure it’s going up every week.

• SQOs (Sales Qualified Opportunities) - those are meetings that were had and qualified. They’ve entered your sales pipeline. This number needs to be increasing every week, and your sellers need to be at a full-enough capacity in their pipeline, always.

• Qualification Rate - % of intro calls that are qualified. You want this to be between 80-90%. Below 80%, you’re only allowing easy deals in your pipeline, or you booking too many meetings with the wrong people. Above 90% means you’re likely not in enough deals (or maybe in an insanely hot market).

• Win Rate - How many deals are closed won. Formula is Won / (Won + Lost). I calculate this from qualified to close, remove the disqualified SQLs from this number.

• ACV - what’s the average contract value on those deals.

• Duration (cycle length) - measured in days from qualified to close.

Benchmarks

This changed a lot in the last few years - everything became harder to sell. But general rule of thumb for bad - good - great:

• Qualification rate:

  • Bad = <70% OR 100%

  • Good = 70-80%

  • Great = 80-90%

• Win Rate:

  • Bad = <20%

  • Good = 20-35%

  • Great = >35%

Now, ACV and duration are very circumstantial. They’re more about the combination of the two together, and whether or not you’ll be able to run a profitable sales motion.

General rule of thumb is higher ACV, longer sales cycles. Lower ACV, shorter sales cycles. So examples of good / bad / great here could be:

• Great = $50k in 60 days

• Great = $10k in 14 days

• Great = $3k in 7 days

• Good = $50k in 90 days

• Good = $10k in 30 days

• Good = $3k in 14 days

• Bad = $50k in 9 months

• Bad = $10k in 120 days

• Bad = $3k in 60 days

There’s infinite combos of this, but these are just examples. You can afford to run long sales cycles on small deal sizes, that’s really what to look out for.

Building a Useful Dashboard

I have to give huge props to a career mentor of mine for this one, Mark Ramsay. He’s had 5 exits as a sales leader (1 IPO), built and scaled many sales orgs. Helped me a ton when I was VP Sales at Proposify.

I was already pretty good with numbers having done sales ops my entire career, but after working with him, he really showed me how to investigate the sales numbers. And one of the most impactful things he showed me was how to build a sales dashboard.

He basically said to break down all the key elements of the funnel, and track “what did you get paid?,” “what are you about to get paid?,” and “what will you get paid in the future?”

So basically a full view of what closed, what’s about to close, and how will you continue closing in the future.

Track volume and conversion metrics. And pay close attention to where the volume and conversion metrics matter the most.

You dashboard should show you were to investigate stuff daily. Where to dig deep. It should clearly scream at you if there’s trouble. And the underlying source reports should allow you to dig into and find explanations as to why the metrics are good or bad.

You start with this broad lens of what’s working and not working. Then you zoom into hypotheses for what’s not working. Then you fix.

And you repeat this formula daily/weekly/monthly/quarterly.

And also make sure you’re tracking for the right timeframe. So the way I kept all of our numbers increasing at Proposify was by isolating 3 sales cycle length. I knew that anything before that was outdated, because we were constantly improving the sales process. I see a lot of founders make mistakes here - they track win rate year-to-date (YTD). And it’s June. And they’ve changed the sales process twice since January. So that number is not accurate of current way of selling, because it includes old ways of selling. So you have to account for that.

Here’s what my dashboard looked like at Proposify and Q4 Inc:

I built this in Salesforce. Here’s my thought process behind every tile:

• Rolling 7-days bookings: I wanted to know how much money we made this week. I divided our annual target by 52, and wanted to see how closely we were pacing every week if we shot for a specific number.

• Rolling 30-day bookings: Same calculation, but monthly. Are we generally on track.

• QTD bookings by month against trendline: I would see variance month over month, for the quarter. Did we hit the quarterly target even if one of the months was off. That helped me track if we were closing what we said we would.

• Close rate last 90 days: How good are we at closing against our benchmark number (for us we set 35%).

• AVG Bookings (ACV) last 90 days: If we aimed for a $20k average deal size to make plan, are we closing at the average deal size we need.

• Cycle last 90 days: Are we closing on average at the speed we need to

• Stage 3+ pipeline amount: These are folks who gave verbal and are into procurement. How much is that pipeline worth - that’s where deals mostly come from, I can expect that to trickle in within the average close date timeframe.

• Weekly SQL trend last 90 days: Are we booking the right number of meetings every week. Is there fluctuation in booking meetings. Are we on track based on the number of meetings we need to book to hit targets.

• SQO or Discqualified Rate last 90 days: Of the SQLs we booked, what percentage made it in the pipeline

• # of open deals sorted by funnel stages: I don’t care about total value of pipeline as a main metric. It’s often incorrect. Default values in CRM, reps not updating often enough, etc. What I care about is number of deals. Because I can anticipate what’s going to close by applying my math # of deals X win rate X ACV. And I can look at that and see whether or not we have enough deals in the pipe to make plan.

• QTD Weighed Forecast by Month and forecast category: I had this as commit / best case / good case / unlikely. I then had a % weight based on stage in CRM, so it would tell me a weighed amount based on the stage and probability of closing, then the forecast category on top of it. I usually was 90% confident in committed deals, 80% confident in best case. The rest, I tended not to forecast.

• QTD full pipeline value by month and stage: This was all deals in the pipeline, with full amounts, by CRM stage. It was another way to look at what could close. Usually, between weighed forecast and full pipeline by stage, I could “call my number” withing 80-90% accuracy. That’s important for when you’re making promises to the board, or when you’re managing your first team of AEs. How good are you at predicting how much revenue you’ll make before you make it.

• Top deals open: I had the top 10 deals displayed here by deal size. I always wanted to know about any chunky deals that could get us to our number faster.

• Top stalled deals: I had the top 10 stalled deals here by duration. I was looking for decay in the pipeline. Why are certain deals in there for 200 days when our average cycle is 60 days. Helped me spot anything that might be messing up my forecast.

This was my main dashboard. I also had a spreadsheet that took snapshots of the key funnel metrics every month, so I could track MoM % change and make sure we were always improving. And if something was on the decline, I would go investigate.

NOTE: If you have multiple GTM motions, split them up. Do not combine funnel metrics. You should know how each motion is performing.

Inbound needs a separate dashboard from outbound.

Enterprise needs a separate dashboard from SMB.

Partnerships needs a separate dashboard from direct sales.

You do not - I REPEAT - YOU DO NOT want to combine sales motions. Your metrics will be diluted.

And inbound number might carry up the performance of outbound, making you think you’re not performing so bad (happened at Proposify, we needed to fix).

Your partnership motion might carry up the direct sales motion (happened at Q4, needed to fix).

When you combine the performance of the motions, it doesn’t tell you which motion is performing well vs which one is suffering. It doesn’t isolate exactly where to go fix things. It doesn’t tell you which motion you might want to drop.

So if you have clear segments, motions, use cases, etc., that run very differently - separate those dashboards. They are not the same, should not be treated as the same.

I’ve seen so many founders and sales leaders make HORRIBLE decisions because of generalized funnel metrics. Using the performance of one motion to set goals for a very different motion. It always ends in the same way - somebody gets fired or the company burns through too much cash in the wrong places.

What to do before $20k MRR?

Before you’re at 20k MRR and have consistent deals in your pipeline, don’t worry about measuring any of this stuff. You will spin your wheels and just get depressed.

There are only 2 things that matter in the early days:

1. How many conversations are you having daily? Email, LI DMs, cold calls, intro calls, follow-up calls, etc. Doesn’t matter how the conversation is happening, just are you having them. And are those convos going up?

2. Number of total meetings in calendar. Including intro calls, follow-up calls, etc. Is that number going up?

Anything else is a distraction in the early days. You just need to learn as fast as you can about your prospects and the market. Some of this stuff will head into a sales cycle and close. Eventually you’ll spot patterns for what leads to closing. And you’ll need a dashboard to track and improve the key metrics. But until you’re swamped with conversations, none of this stuff matters.

Let me know what you think of the newsletter! Always want to cover topics that you care about.

For more practical early-stage sales tips, connect with me on LinkedIn.

If you’re looking for more hands-on help implementing your first sales process, reach out for coaching packages.

Here’s what Patrick had to say about coaching with SalesMVP Lab:

Reply to this email or book a quick coaching call if you’re at $20k+ MRR, have good pipeline, but struggling to consistently close deals.

P.S. I also work with founders who have small sales teams, but no sales leader yet. Ping me for details.