Series A Benchmarks



Probabilistic Mental Model

There’s a tendency to think of Series A metrics as inputs to an IF statement:

IF metrics >= benchmarks
THEN get funded  
ELSE don’t get funded  

I think this paints a deterministic, binary vision of the VC decision-making process that isn’t very realistic. The truth is more fluid.

At Series A, most VCs look for three underlying characteristics in a business:

Unfortunately, it’s usually not possible to provide direct evidence of these characteristics. So investors have to rely on proxy signals aka pattern-matching.

The most common proxy signal or pattern is something like this:

“1M+ ARR, growing 3x year-over-year, with efficient customer acquisition and strong retention.”

Why is this a useful signal? Because it’s very unlikely that a startup can exhibit all of these attributes unless they have the underlying characteristics (PMF-TAM-GTM) in place. And the reason for that is that these attributes pull in opposite directions.

For a startup to hit 1M ARR with rapid growth implies a large underlying market. Of course it’s possible to hit 1M in a small market, but in that case, you would expect growth to be much slower. (If 1M is 0.01% of the TAM, it’s much easier and quicker to capture than if it were 5% of the TAM – simple market share dynamics). Conversely it’s easy to grow fast when you’re at low absolute numbers, but continuing to do so at 1M is harder, and hence meaningful.

Similarly, you can get rapid growth with either strong PMF, or with aggressive (brute-force) sales and marketing. But aggressive GTM is usually expensive. And if there’s no PMF, it inevitably results in high churn, sooner or later. So if you see rapid growth along with cheap GTM and sustained low churn, that suggests that there is, in fact, true PMF.

What it comes down to is an exercise in combining probabilities. If all these attributes (revenue, growth, efficiency, retention) are present simultaneously, it seems very likely that the startup has strong PMF-TAM-GTM; and conversely, if the startup doesn’t have strong PMF-TAM-GTM, it’s very unlikely that it can hit all those attributes simultaneously.

Mind you, only the very best companies manage to hit everything perfectly. More often, “fundable” companies are good-to-great on some of these attributes and average-to-good on the others. The VC’s job is to triangulate across all of these; your task as a founder is to make sure you satisfy that triangulation. The next section explains how.


Primary Metrics

As of Q4 2022, here’s what you need to raise a Series A of 10M at a pre of 40-50M (my best estimate of the current market). I use letter grades:

A = best in class
B = very solid
C = acceptable
D = disqualifying

First, note that almost no start-up has all As.

You should aim to have mostly Bs, and that’s fine. B is the baseline for fundability by a top venture firm. Not saying they will all fund you, but if you score Bs on all criteria, you will get a whole bunch of conversations, some serious interest, and hopefully a handful of term sheets.

It’s okay to have one C among the Bs, but as a rough guideline every C needs to be counter-balanced by an A. If you have multiple Cs, the top firms may not look at you and fund-raising is likely to be a long hard slog across lesser-known firms.

Avoid Ds. If you have any Ds, you’ll find it hard to raise a Series A at this valuation range.


Metric A = great B = solid C = okay D = poor
ARR USD 1-5M USD 1-3M USD 800k USD 500k
Growth y/y >5x 3-5x 2-3x <2x
NRR >120% 100-120% 90-100% <90%
Burn Mult <1x 1-2x 2-3x >3x
Fndr Eqty >80% 60-80% 40-60% <40%

(Founder equity going into Series A is the one that people are sometimes surprised by. There was a time when VCs would refuse to fund startups where the founder owned too little of the company, going into the A, for fear of misaligned incentives. But I suspect that’s changing; in the current market environment, VCs understand that sometimes founders have to dilute a lot, just to stay alive.)

(Update, Q3 2023: Valuations have corrected and are now in the 30-40M range if your grades are mostly Bs. Also, the hurdle for a Series A today feels like it’s a bit north of 1M ARR – closer to 1.5 or 2M. AI startups are an exception, there are no rules for them.)


Secondary Metrics

In addition, there are some secondary metrics that people will dig into.

SaaS Sales Metrics for a strong company:

One final piece is length of sales cycle. Of course, this depends on your ACV. But here is what people would like to see:


Category Deal Size Sales Cycle Quota: deals/year Quota: dollars/year
SMB 5-20k 0-2 weeks 30-60 300-500k
Mid-market 10-40k 2-6 weeks 15-30 500-700k
Enterprise 80-300k 2-6 months 5-15 700k-1m
Mega 500k-5m 6-12 months 1-2 1-2m

Take all these secondary metrics with a hefty grain of salt! I’m a lot less sure of these metrics than I am of the primary metrics, simply because each business is very different. (E.g. if you’re a marketplace, or have a hardware component, or a data business).

Also, a lot of these secondary metrics are likely to take a hit in the current economic climate – longer sales cycles, higher churn rates etc. – so some VCs are recalibrating their expectations. Others, unfortunately, are not.


Qualitative Metrics

Series A is the last round that leaves room for investor discretion and subjectivity; after that, it becomes a lot more numbers and financial model driven. But at Series A, there are still some qualitative metrics that investors care about – a lot.

Here are some things that people look at:

Some of these are quantifiable but it’s hard to put a number on them from a founder’s POV. But you should be aware of these criteria nonetheless. To the extent that you can paper over weaknesses in your quantitative metrics, by using strengths in analogous or corresponding qualitative metrics, you should do so!


Other Rounds

If Series A is the PMF round, Series B is the unit-economics and scalability round. By Series B, your basic assumptions – PMF, TAM, GTM – should be proven beyond doubt. The next set of questions to be answered are: are the unit economics sound, and therefore can the company deploy capital (usually on acquisition) in a performant and sustainable way.

Going in the other direction, Seed is the round where you don’t yet have definitive evidence of PMF-TAM-GTM, but you have the first inklings – sometime quantitative, sometimes qualitative – that such evidence is emerging. One VC I know describes it as “the round at the intersection of art and science” and I think that’s a good description.

And then Pre-Seed is even before that: at Pre-Seed, there’s no real evidence yet, but there are reasons to believe that the evidence will eventually emerge. (Usually, those reasons boil down to team and macro; everything else can and will change.)



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