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Early stage funds have a notoriously tough job. Very high deal flow volume, weak signals, high risk and heavy power law. And to make matters worse, often tiny teams with razor thin management fee. This game is not for the faint hearted. But it's exciting, right?
What's not so exciting are the many "monkey tasks". You'd rather maximize time budget for high impact tasks. That's where a coherent tech stack can unlock operational Alpha for you. Arguably your top funnel formula (defined as everything until Term Sheet) hinges upon a few main multiplicators. Visibility, Throughput, Access and Analysis. Let's dissect together.
Visibility determines how many new companies you can identify. Either through inbound leads, network syndication or active outbound sourcing. Technology can help with this a lot.
Throughput defines how many companies can give you a qualified look given your resources. Clearly this is also a function of how many other tasks the same resource needs to fulfill. Technology can help with this, too.
Access often is a function of your brand, network and thesis. Technology can help with this a little.
Analysis is your ability to quickly assess a market, a team and triangulate chances. Technology can help with parts of this.
Technology is not a fertilizer; it is a force multiplier. It makes you faster.
High performance stacks for Pre-Seed and Seed typically have the following components.
You don’t need a stand-alone tool for each purpose. But you’d want the functionality in your stack.
Major factors for defining the right tech stack for you;
A low cost stack productivity for many users in the Western Hemisphere can look like this.
Total baseline cost would hence sum up to $98 per seat per month($1.2K seat / p.a.).
Optionally, some teams prefer to use overlapping solutions for some features that are already included in above subscriptions.
The optional solutions would add another $53 per seat per month to the $98 for the base set. That you make a total of $151 per month equaling $1.8K per year.
For comparison. Top quartile funds spent 10-20% of their management fee on tooling. Let’s assume you manage $20M AUM with 5 FTE and go for the lower benchmark.
With 2% management fee your total budget would be $400K p.a. 10% of your management fee would be $40K.
The above tools would cost you $9K p.a. for 5 FTE. Hence you still have a budget of $31K p.a.
If you outsource the integration of above systems, you will have a one-time cost of $10K and yearly maintenance cost of $2K. You can do it yourself, but it will take you 4x as long as an expert. And your time is scarce.
Even if you outsource, you still have the budget for more advanced tools. We would invest into two data sources. Examples:
Why did we pick these two over Crunchbase or Apollo? We like Inven for a number of reasons. Great UX. Very good coverage of companies. Major difference - Crunchbase essentially covers the startup world. Inven also covers the possible B2B clients of your companies. With it you can quickly estimate TAM/SAM/SOM including client revenues. You also have financial data for private companies from the trade registry next to hiring trends. And you can even unlock phone numbers and mail for credits. It does cost ca. 3x of Crunchbase ($49 seat / month). So, if your case does not warrant the extra spend you can save some money.
We picked Linkedin because most users are native in the UI and the ability to reach out via InMails. Arguably the Apollo “Organization” subscription for $119 seat/month could work as well in combination with Crunchbase.
Now back to budgeting. If you stick with Inven and Linkedin for 5 seats this would add another $319 per seat per month or $3.8K annually. Previously we had $29K left annually. The 5 users will eat away $19K, leaving you with a $10K budget. And arguably you might not need subscriptions for all 5 FTE.
Hence even if you outsource integration for $10K you are within budget already in year one. A system diagram of a coherent stack connected via APIs would look like this.
What you don’t yet have at this point are automated portfolio monitoring and reporting, advanced automations, a proper data lake and custom machine learning algorithms. These would only become feasible, if you spent on par with top decile funds (20% of 2% Management Fee). You need to plan half an FTE for that. Depending on your labor cost this might be $50K per year. If you have a solid pipeline and want to compound knowledge internally, it makes sense to hire internally. If you are looking for speed and cost efficiency, outsourcing is more prudent.
Assumptions:
Total per seat per month = $18 + $45 + $25 + $10 = $98 Total per seat per year = $98 * 12 = $1,176
Rounded to $1.2K per seat per year as mentioned in the text.
Additional cost per seat per month = $14 + $14 + $25 = $53 Total additional cost per seat per year = $53 * 12 = $636
Total cost with add-ons per seat per month = $98 + $53 = $151 Total cost with add-ons per seat per year = $151 * 12 = $1,812
Rounded to $1.8K per seat per year as mentioned in the text.
Baseline cost for 5 seats = $1,176 * 5 = $5,880 per year Total baseline cost rounded to $6K per year as mentioned in the text.
Total data cost per seat per month = $170 + $149 = $319 Total advanced tool cost per seat per year = $319 * 12 = $3,828
Data cost for 5 seats = $3,828 * 5 = $19,140
Initial budget = $40K Baseline tool cost for 5 seats = $6K Remaining budget after baseline tools = $40K - $6K = $34K
Advanced tool cost for 5 seats = $19K Remaining budget after advanced tools = $34K - $19K = $15K
Integration cost = $10K Remaining budget after integration = $15K - $10K = $5K
StackGenius’ Founder Silvan worked for Silicon Valley Corporates for 10 years. Afterwards he spent another 10 years founding Machine Learning companies in Europe. When his last company was sold in an Asset Deal in May 2024 he thought about building a “datanative” Micro VC. But he realized that he doesn’t know enough about investing. But he knew enough about building coherent tech stacks and applying machine learning. This is how StackGenius came to life. A hyper-specialized system integrator that helps investment teams of all shapes and sizes to build Alpha with technology.
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