June 02, 2021
Data due diligence seed-stage

Venture Diligence at the Seed Stage



Note: This post is optimally viewed as an interactive model on Tactyc here


In our previous post, we took a look at venture fund portfolio construction and the tradeoffs fund managers have to consider when building out their investment strategy. This blog post will explore the diligence process at the seed stage and will again use Tactyc to illustrate dynamics around the quantitative side of diligence, specifically return the fund analysis.

Diligence at the seed stage of venture capital involves a mix of qualitative and quantitative factors. There is no one way to run a diligence process, and often it comes down to the individual feel, style and preference of the investor. The following Tactyc model enables you to quickly run scenario analysis for your own fund to answer the “what we need to believe” question in order to hit your fund’s return thresholds. If you are interested in customizing this model for your fund, sign up at Tactyc today or drop us a note at venturecapital@tactyc.io


Qualitative Diligence Factors

While this list is not exhaustive, qualitative diligence involves the following factors:


Quantitative Diligence Factors

Quantitative diligence also takes many forms. The factors below are some of the key ones MaC focuses on at the seed stage:

The final portion of quantitative diligence involves return the fund analysis. At MaC, a key part of our diligence is a firm understanding of core explicit and implicit assumptions around what needs to happen for a company to both return our fund and also return a multiple of our fund. Venture capital returns follow a power-law distribution meaning that outlier companies will deliver the vast majority of a fund’s returns. To be a top-quartile fund it is almost necessary to invest in a company that can return a fund and more.

To perform this analysis we start at the top with our fund size and gross return target. Typically, to be in the top 25% of all venture funds, a 3x net return is required or a 25%+ IRR. A 3x net return means that a fund will return three dollars after all fees and carry for every dollar invested into the fund (for simplicity’s sake we are using a targeted gross return in this analysis). This gives us the gross dollar amounts that our share in a single company has to be worth to achieve our objectives.

Setup this analysis for your fund here


Company Ownership and Dilution

From there we calculate our anticipated initial ownership in a company which is determined by the size of our investment and the post-money valuation of the company. If we are investing through a SAFE or a convertible note we estimate our ownership based on the valuation cap and a pro-forma analysis of the cap table where we look at what our ownership stake would be should all the existing SAFE and note holders convert to equity.

We then consider the future fundraising rounds the company will undergo, typically looking at series A through D rounds. We will model out the estimated size and pre/post money valuations of those rounds and what our dilution in those rounds would be. We also consider if we will take some or all of our pro-rata share in those rounds to reduce dilution. Typically, to maximize returns, a fund needs to consistently participate in future rounds through its pro-rata rights.

Finally, we may factor in additional dilution that may occur in rounds past the series D round. The net result of this process is our estimated ownership in the company at the time of exit.


Implied Company Valuation

Dividing this percentage by both our fund size and our targeted gross return will tell us at what value a company has to exit at for our share of the company to be at a level to reach our fund-return and gross-return objectives.


Implied Company Revenues

Next we apply an industry-average revenue valuation exit multiple to those valuations to determine the level of revenue needed for a company to reach those valuations. Dividing the valuation numbers by the revenue multiple gives us these figures.


ARPU and Paying Customer Targets

We then take the analysis into one of two directions: we either take an assumed average revenue per user (ARPU) figure informed by the company’s business model, or an assumed number of paying customers/users based on company projections or anticipated share of the market. Using an assumed ARPU, we can divide the targeted revenue numbers by the ARPU to get an implied number of paying customers needed to hit those sales targets. Using an assumed number of paying customers and dividing that number by the sales targets would give us an implied ARPU to hit the same targets.

We then compare the ARPU and paying customer numbers to what we see in the market to help us gauge our confidence of the likelihood that this company can return our fund and also allow us to hit our targeted gross return figure. For example, if the end result of this analysis is that a company would need 1M paying customers paying an industry-average ARPU and the current market for this product or service is 2M, then the company would need to achieve 50% market share, or dramatically increase the size of the market to hit our objectives. That might make us think twice about investing. Alternatively, if the company can earn at or below an industry-average ARPU and still only need a volume of customers that makes up less than 1% of a market, there is reason to be bullish about making an investment.


Sensitivity Analysis on Revenue Multiple and Exit Revenue

In this section we evaluate implied exit values, the value to fund (after taking into account the fund’s ownership in the company) and the MoIC on the investment


Final Thoughts

Obviously, all the quantitative analysis mentioned above are just approximations. At the seed stage this is far from an exact science. But doing this diligence is important, and can often provide a worthy gut-check during the process. And equally important is understanding how changing the various inputs in the process from fund size and targeted gross return to initial ownership stake, to future round details and the taking of pro-rata, to assumptions around valuation, ARPU and paying users all affect the dynamics of return the fund analysis. Using Tactyc to explore how all these factors relate to each other is a fun and simple way to better understand this process.


By Michael Palank (MaC Venture Capital) and Anubhav Srivastava (Tactyc)

We hope you enjoyed this quick primer. This interactive analysis was built on Tactyc, a platform to build and work with interactive models for smarter scenario analysis. If you are interested in transforming your firm’s model templates into re-usable dashboards such as these for fast scenario analysis, please drop us a note at venturecapital@tactyc.io

For any questions about the underlying model or analysis please reach out anubhav@tactyc.io or mike@macventurecapital.com


About MaC Venture Capital

MaC Venture Capital is a seed-stage venture capital firm that invests in technology startups leveraging shifts in cultural trends and behaviors. Our diverse backgrounds in technology, business, government, entertainment, and finance allow us to accelerate entrepreneurs on the verge of their breakthrough moment. We provide hands-on support crucial for building and scaling category-leading companies, including operations strategy, brand building, recruiting, and mission-critical introductions.


About Tactyc

Tactyc is a no-code platform that transforms spreadsheet models into interactive web apps that enable smarter scenario analysis. Powered by the Tactyc Spreadsheet Engine that translates spreadsheet logic automatically into code, Tactyc enables users to create interactive presentations with narratives, extract model insights and build embeddable calculators in seconds. Tactyc was founded in 2020 by Anubhav Srivastava and is based in Los Angeles, CA.


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