Enterprise Seed VC Funding Napkin (At Year 4/5 of Deployment)

What are good “results” for a seed-stage Enterprise VC fund, today (i.e. when it’s early)?

We created the Seed Stage Enterprise VC Funding Napkin about one year ago. Our thinking has evolved over time, just as markets do…

The S&P is now hovering at all-time highs. Exit and IPO markets have seemingly tightened further, buoying private equity firms and secondary liquidity providers around very select private and public targets (this is expected to change in the coming months with the new administration). It is early days, but LLMs and Gen AI technologies are appearing to catalyze one of the biggest technical shifts in recent venture history. All in all — tech continues to deliver tremendous value in our economy despite the market seemingly bifurcating into the haves and have-nots (are you AI or not?!). In times of fast change, it is increasingly important to have measured, consistent judgement which is why we’re updating, and will continue to update, the VC Funding Napkin. You’ll notice a few additional metrics below.

For new readers — this framework provides a window into early fund performance before a fund ultimately settles into its final quartile (and ultimately decile!), typically happening in years 6–10 of a fund’s lifecycle. In 2026 we’ll begin benchmarking Preface III.

Per usual, Fund II (2020 vintage) is highlighted in orange. We’re incredibly proud of our results considering the “happy” vintage of 2020, where we began investing. We’ve maintained a high bar on deploying to capital-efficient, need-to-have, technical assets at compelling valuations:

Seed Graduation Rates: This metric is fairly straightforward. High-performing VC funds have high follow-on rates to Series As. Taking it a step further — a leading FoF disclosed to me that if a seed VC fund has 50% of the portfolio graduate to Series B, the likelihood of a fund achieving above a 3.0X DPI is over 80%.

GP Comments: Excellent is now 65% where previously was 70%+. We’ve revised this figure slightly downward even with further time to have graduated for several reasons: 1) the duration between seed and Series A is now 2 years+ 2) large inception rounds / slower burn rates are much more common within enterprise 3) Series A graduations in aggregate have been less frequent in the past year+ (see Carta’s recent quarterly report).

Pro-rata Accessibility: Seed investors should desire the opportunity, whether contractual or not, to re-invest in their winners. Not all GPs are given the opportunity to protect their initial ownership stake from dilution or grow it. Having the opportunity to invest in follow-on rounds expands the investment universe for the GP — who should have better information on the asset than others — this is a good thing. The follow-on check is more likely to have a modest multiple vs. the entry ticket, though it might still be accretive to the fund’s overall performance. If the GP wishes to have a more meaningful reserve strategy in their new fund(s), this is additionally important. GPs should aim to have pro-rata offered to them the majority of the time, if not always.

GP Comments: Excellent is now 85% where previously was 75%+. Given the relatively less buoyant follow-on market, pro-rata accessibility should increase for Enterprise Seed VCs. Lack of access indicates a problematic dynamic.

Entry: Reserve Ratio in Top 3 Companies: This ratio is a metric for executing pro-rata in fund winners (top 3 positions). For example, investing $1.0M (entry) in a seed round and $2.0M (reserve) in the follow-on is a healthy ratio for a high performing Preface III company. Going beyond that can encroach on single asset concentration limits stipulated within an LPA (commonly 10% but I’ve seen up to 20%). A leading FoF highlighted an even higher ratio (1:3) in their best performing underlying businesses.

GP Comments: Excellent is now 1:2.5 when it previously was 1:2. Seed valuations have risen though Series As have declined / are now somewhat stable in the past year+. This should benefit GPs as they’ll invest further capital in a presumably more de-risked seed-extended or Series A asset.

Weighted Blended Entry Cost (post-Series A): Too often LPs look at entry price / ownership and not the dollar-weighted blended entry cost between entry and follow-on, which is critical if the fund has a reserve strategy (many do). We all hope for asset outperformance — but having low blended cost will generate attractive blended return in “average” exit environments as well. GPs may sometimes write a small entry check and “logo buy” at a high price once an asset gets a strong follow-on offer. This metric should illuminate the downsides of that behavior. Many FoFs have done Monte Carlo analyses on their funds’ reserve strategy — a notable one mentioned that if their underlying VC funds just wrote the same check size evenly across positions with no reserve strategy — they’d outperform the normative fund performance 70% of the time. That might be impractical, but bigger checks, earlier for seed managers tend to be a good rule (particularly in boom times like 2021).

GP Comments: Excellent is now $25.0M — $35.0M where it was previously $20.0M — $30.0M. We’ve revised this figure upward slightly given the dynamic mentioned in the prior comment (with likely a better entry revenue multiple). In totality, this should benefit GPs in the wonderfully large and liquid category of enterprise infra / vertical AI. Looking at M&A outcomes alone — which accounts for the large majority of liquidation events in our asset class — exit values have been increasing (2015–2020 at $220.0M; 2020–2024 at $329.0M).

Cumulative Burn Multiple: This is calculated by summing all $ burned to date vs. current ARR across the portfolio. Many folks reference burn multiple i.e. dollars burned in 12 months vs. net new ARR which is a helpful efficiency metric. However, it’s possible that a company with a healthy current burn multiple may have burned a ton of cash prior to the current year, correlating to low management ownership (which we don’t want — founder led companies tend to outperform). Technology companies should fundamentally be capital efficient and startups cost less than ever to launch. In 2023, a Series A investor would look at $2.5M burned to get to $1.0M in ARR as a highly refreshing and attractive foundation for a company’s future growth.

GP Comments: Excellent is now 2.3X where it was previously 2.5X. On the burn side, launching a startup has never been cheaper. Compute and training costs continue to decline over time and our now AI-powered workforces should be able to do increasingly more with less resources (hasten the “one-person unicorn”). Lastly, in the long-term, a company should burn less and show evidence of operational leverage i.e. cash flow potential.

% Ownership in Winning Positions (top 10%) vs. Average Ownership (post-Series A): We calculate this metric by taking the average percentage ownership of a portfolio’s best post-Series A companies (top 10% of them) and dividing it by the average percentage ownership of the overall portfolio. For example, if the average ownership of a set of post-Series A companies is 4%, but the ownership of the top 10% of the portfolio is 5%, the ratio is ~1.3X.

GP Comments: No change. Managers with information advantages and reserves should continue to be able to concentrate their capital in their winners.

Tail Ratio: Modeled after the “power law” — Sumeet Gajri’s ‘Tail Ratio’ metric offers LPs a tool for assessing what’s required to return a fund of any size. The higher the ratio, the less likely the GP will return the fund on any given investment based on their fund model. Another way to view this metric — can one position be “outlier enough” to return the fund?

GP Comments: No change. A concentrated portfolio of 20–25 positions is generally better, for seed managers :-)

Aggregate GRR (Gross Retention Revenue) / NRR (Net Retention Revenue): Though new to the napkin, these are old SaaS metric(s) which correlate to high-performing companies (both in public and private markets). Leaky buckets are never good and it is widely known that it is 8X more expensive to acquire a new customer vs. retain an existing one. NRR is an increasingly important metric and a reflection of product innovation — interestingly, startups with Generative AI-powered SaaS (key theme at Preface) see 7% higher NRR than their more “lower-tech” peers.

CAC Payback: Also new to the napkin, but increasingly important as gross margins in AI-powered SaaS products fluctuate. In aggregate across a relatively mature SaaS portfolio — contribution margin payback on marketing should ideally be less than one year. Quicker turns on the working capital of marketing enable a company to grow larger off the same sized balance sheet.

TVPI / DPI: Hopefully most of us know what these metrics mean. While directionally helpful and worth including, I see too many folks overweighing them early on. For example, I’ve seen fund TVPI tempered with the advent of convertible notes (quite common today) that don’t change holding valuations. DX, a high-growth company with fund-returning potential in Preface II, is a strong example as they’re still held at 1.0X MOIC. DPI is also hard to see given the holding period of private investments is 5.0+ years on average. Some FoFs look at TVPI / DPI while excluding the top and bottom quartile of investments to see “repeatability”; however again, this is less useful to assess by year 4 of fund life which is what we’re attempting to accomplish.

GP Comments: These figures are updated with Cambridge Associates’ recent benchmarks across TVPI and DPI. One would expect funds that have “excellent” characteristics particularly after years 6–10 will have requisite TVPI and DPI.

% of Portfolio Led by Tier 1 VCs at Series A: Many seed stage VCs reference how they co-invest with established firms like Sequoia, Benchmark, Accel, or a16z. When that happens is critical. According to AngelList, having a Tier 1 fund (multi-stage) invest in a company at seed correlates to a neutral or even negative Series A, defined as a 3X+ mark-up at normative dilution led by a reputable firm. That correlation changes quite a bit when the Tier 1 multi-stage firm follows the seed investor in a Series A. A notable FoF mentioned if one of the aforementioned groups leads the seed manager’s Series A company, the likelihood of a “homerun” i.e. 10X return increases by 4X.

GP Comments: No change. Series As with established, successful funds continue to be correlated with higher exit outcomes.

Early Recycling: Highest performing seed funds tend to recycle and deploy ~106% into companies. At year 4 one would hope some more dollars have been reallocated to existing winners or in new companies i.e. “more shots on goal”.

GP Comments: Excellent is now 6%+ when used to be 5%+. A 4–5 year old fund vs. 3–4 years should have slightly higher recycling rates. More shots on goal is usually the right answer for good pickers.

In some ways, creating and measuring our results is a VC’s version of “building in public”. We hope to continue sharing our learnings as well as evolve our thinking for the better with your feedback. Thank you for reading!