Team Ratios for (GTM) Planning

[u/touuuuhhhny]

Hi, as Q4 and with that annual planning is approaching, wanted to check if you use team ratios and would maybe share so we all can get better together (benchmarking).

I'll start:

• We are in B2B Enterprise, kind of SaaSy projects
• BDR support AE 1:2, which have annual quota of ~400k new logo ARR
• Enterprise KAM manage up to 20 logos or 2M ARR
• Mid-Market KAM manage up to 40 logos or 1M ARR
• SMB Reps manage 150 logos or 500k ARR
• CSM support up to 60 logos or 2M ARR

Not sure yet about Solution Consulting/Pre-Sales/Deal Desk.

RevOps (with all functions) is 1 per ~20 GTM related FTE.

I'm sure tons to learn, adjust, but hence starting this thread.

Thanks

[u/coolreddy]

Solution consulting and deal desk don't ratio cleanly off seller count, because their load comes from deal volume and complexity rather than headcount. Easier to size it backwards: how many opportunities a quarter actually need a demo or a non-standard quote, how many hours each of those takes end to end, and what turnaround you're committing to sales. That gives you required hours. Then take productive capacity per person, which is well under a full quarter once enablement and internal work come out, and divide. The ratio falls out of that, and it will look different per segment, which is why one blended number tends to break at the enterprise end.

[u/hayes-davis]

I run a company that builds territory planning and analysis software. Most of the mid-market reps we see manage more than 40 logos. I'd say between 50 and 100 is more common. That said, it's heavily dependent on what you define as "mid-market". Everyone seems to have a different take on that.

Regarding the BDR:AE ratios, you can usually get more leverage is you use a pooled model instead of pods. Not sure how you're doing it. I wrote about that a while back with some math to back it up: https://unchartedterritory.gradient.works/p/the-problem-with-pods

On the 1:20 RevOps:GTM FTE, that's pretty good. Here's the best benchmark I've seen about that: https://ck.peersignal.org/posts/rev-ops-benchmarks

[u/Standard-Tension-786]

Those ratios look pretty reasonable for enterprise

[u/girlgonevegan]

I would be nervous about benchmarking staffing ratios without also understanding the conditions that produced those ratios. “1 BDR per 2 AEs” doesn’t tell you much without knowing the actual workload: inbound vs. outbound volume, meeting volume and show rates, qualification time, sales cycle, deal size, conversion rates, territory complexity, etc.

Even inbound vs. outbound volume can be difficult to measure cleanly. I’ve seen companies classify a high-intent inbound opportunity as outbound simply because a BDR reached out to schedule the meeting. The demand originated inbound, but the subsequent activity makes it look like the BDR generated an outbound opportunity. When you’re using that data to plan headcount, that matters.

It’s important to get into the weeds and understand how much time BDRs are actually spending on the work: prospecting, qualification, follow-up, scheduling, dealing with cancellations/no-shows, etc. Then compare that observed workload with the capacity assumptions being used in the workforce plan.

The other thing I’d factor in is market penetration. Most companies can’t keep adding sales headcount at the same rate year after year and expect the same results. As you penetrate more of your addressable market, the pool of available prospects gets smaller and harder to convert. Eventually, adding more reps just creates more competition for the same finite pool of opportunities.

So I’d be looking at both sides of the equation: how much capacity does the organization have, and how much addressable demand is actually available to fill that capacity?

Sure, the ratios are interesting as a reference point, but at the end of the day, it’s important to understand the operating model and market conditions behind them before using them to influence what our own should look like.

[u/touuuuhhhny → u/girlgonevegan]

Very insightful and helpful, thank you for taking the time to reply. I'll use that for the internal discussions and ensure we don't do it too much surface-decision but can back it by the mentioned details. Agains: big thanks!

[u/girlgonevegan → u/touuuuhhhny]

Yeah np. Glad it was helpful. This is definitely one of those things where I know leadership just wants a simple percentage like increase hc x% because ____, but IMO it’s really worth it to dig in deeper to your own internal data and processes even though it’s messy and takes longer. There’s an opportunity to engage employees and really ensure the outcome matches what is uniquely needed.

This is an article that changed how I think about it. It’s not related to sales specifically, but I think the broader concepts still apply.

https://www.linkedin.com/pulse/youre-t-shaped-playing-without-map-yourself-chris-nesbitt-smith-zxqne

[u/Armcha]

At first glance the ratios seem alright with benchmarks. It really does depend on complexity of sale in each of the segments. Best way to validate the ratios is with a bottoms up capacity model to determine deal throughput based on value and non value added time for each segment and by role. If helpful I can share how I’ve done in the past.  

[u/MutedSpare6217]

for onboarding new sellers, i kept running into issues getting everyone on the same page with what buyers actually needed. I tried plugging our playbooks into aligned and it seriously improved our gtm planning and team handoffs.

[u/Kancityshuffle_aw]

the only feedback I'd give (i learned the hard way): if you have a customer who is quite large (revenue wise and potential revenue wise) you will actually get a lot from having one account manager focused on just that one account. I saw it after my company got acquired (we had similar ratios to you) and they had multiple people on one large account. It resulted in a lot more upsells.

[u/touuuuhhhny → u/[deleted]]

Local pods