Raiz Capital: How we quantitatively assess founders’ odds of success

I’m excited to share the latest in PEVCtech’s periodic series on the tech and analytics stack of investment management firms. We’re fortunate to interview Greg Raiz, Founder of Raiz Capital, and Jess Lynch, Partner.  Raiz Capital is a member of the most recent Coolwater Capital cohort of emerging venture capital managers.

David Teten: Please give us an overview of your firm. 

Raiz Capital is a data-driven pre-seed fund investing in disruptive software user experiences. The common element isn’t just the technology, but the way that it impacts people using the technology.  The biggest waves of technology including Web, Mobile, and AI are catalysts for changes in user behavior. 

We have developed a first-party data set we call “The Founder Index” that uses founder psychology and AI to aid in identifying exceptional founders. We are founded by two exited founders with a strong track record (5X TVPI), and bring a hands-on approach to investing and enhancing the trajectory of high impact founders.

David Teten: Who are your peers/competitors, and how do you differ?

As a pre-seed firm, we often are first-check and sometimes compete with accelerators like YC, Techstars and 500 startups. Unlike these other programs, we tend to focus on more experienced founders who are further in their operational and career experience. We also focused on more personal, one-on-one and peer support over generic workshops and speakers. We align philosophically with firms like FirstRound, Founders Collective, and Initialized Capital.  

David Teten:  What’s your background? How and why are you in your role today?

Greg: I got my start at Microsoft working on User Experience, before starting my own company that I exited in late 2017. I started angel investing shortly thereafter and then ran Techstars Boston for a few years.

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I started this fund in part because I saw there is shockingly little data applied to early stage investing. There’s a ton of data and research on what is success​​ful and sought to apply objective data like we do in every other part of the investing ecosystem, and use data systematically. 

Jess: I got my start at PwC working in financial forensics as a CPA where I consulted on fraud investigations and valuations in business disputes. The foundation in finance was really helpful in raising capital and strategizing when I started my own company focused on improving subscription company user experiences with text message marketing. 

After exiting my company to one of my customer firms, I started angel investing and did a lot of reflecting on my experiences with startup programs. Greg was an investor in my company and when he shared his vision for the firm I realized we had been exploring similar themes around reducing bias in investing and optimizing post-investment support. With our complementary backgrounds and shared values it became a no-brainer to team up! 

David Teten: What did you think of your experience as a member of the Coolwater community?  (For another GP’s view, see Learnt more in 3 months in Coolwater than 20 years in AVC . )

It was awesome to be surrounded by peers. We really appreciated the opportunity to ask questions of active investors into emerging managers. We got a bunch of introductions to active investors and other managers, who are interested in exactly what we’re working on, which has been very valuable. We’re now in 12 active conversations with LPs who we sourced from Coolwater.

David Teten: What technologies/databases have you found helpful in winning LPs?  (I wrote about this in Why Isn’t Sales As Efficient As Online Dating and Fundraising hacks for VC and private equity funds.)

Using our network.  Mostly HNWs, exited founders. Use Airtable to track everything. Have created our own Kanban boards to track.  We send investor update emails using YAMM (“Yet Another Mail Merge”), which plugs in between Google Sheets and email. We find that unlike Mailchimp, Hubspot, etc., messages sent via this channel are less likely to get relegated to marketing; they’re authentic emails sent via gmail. 

We do some activation on Linkedin around emerging manager topics. This keeps us top of mind among the potential LPs with whom we’re connected.

We use Docsend for sharing pitch decks.

David Teten: What are you using for your front office more broadly: sourcing, LP relations, investing analysis, etc.? What are the strengths and weaknesses of these providers?

We search and discover founders on Github, Linkedin, TikTok, and Twitter. We particularly look for people who are building in public and seeking feedback on a new product, and getting preliminary positive feedback.

We funnel & channel all inbound into Airtable. Founders are discovering us in-person at events, through our personal networks, and via numerous social channels: Linkedin, Tiktok, and Greg’s Youtube channel.   

David Teten: What are you using for investing analysis?

We ran a survey across hundreds of founders, where we asked them questions about how they think & operate. Based on this, we developed the “Founder Index”, a data model which we use to assess inbound founders’ Founder Aptitude. This gives us calibration (-1 to 10) of how overlapped that founder is against founders who’ve had a high degree of success. We use the score to signal which founders in our cold pipeline to spend more time with. Then we pair that with our due diligence process which requires us to also turn subjective assessments into quantitative scores, enabling us to more quickly analyze an opportunity, make an investment decision, and improve our process over time.   

David Teten: The Founders Index is based on historical data about successful founders, who tend to be mostly upper-income white men. How do you leverage that resource, while also appropriately seeking out founders of more diverse backgrounds? (See The iconic VC-Backed founders are almost all White & Asian men. So why invest in diversity?

Great question – this aligns with our findings also. We built the founder index to de-bias our own investing by providing objective scores on founder aptitude and psychology.  Our current version of the index has surfaced a number of founders who may otherwise have been overlooked. We’re working with two data-science interns this summer to validate our approach, and also to augment our data with demographics to ensure that we are scoring for aptitude and not modeling-in some metric around privilege. 

David Teten: What did you learn?  And what was your most surprising finding?

In general, we found that humans are really bad at discounting or handicapping. By having a more objective model, that helps us to prioritize our time. 

Unsurprisingly, we found that higher education and immigration status correlate with success.

David Teten: How does your data set, methodology and findings compare with other similar studies, e.g., Ali Tamaseb’s Super Founders: What Data Reveals About Billion-Dollar Startups; The impact of founder personalities on startup success; Harvard Business Review 10 Characteristics of Successful Entrepreneurs; Unicorn Founder DNA Report)?

We took inspiration from a number of these books and studies. Because we invest in the early stages, we wanted to quantify the founder’s psychology and the interpersonal relationships between these predictive factors. Many studies look at traits individually, we wanted to see how these could be combined into a “money ball” for startup founders where we could have a quantitative approach.   Because of this we’re able to combine public research papers as well as our own first-party data. 

David Teten: What are the tools you’re using for supporting your portfolio companies? What are the strengths and weaknesses of these providers?

We ran a test of this last year with our initial cohort. We removed some of the pieces that our research showed didn’t work. A lot of these programs overemphasize speakers and “Startup 101”. The best founders don’t need this. According to our research, the mean age of a successful unicorn founder is 45 according to HBR. But many accelerators target much younger founders. We focus on what founders say is most valuable. We don’t provide generic advice, we provide targeted counsel.

We run an event, “Anti-Demo Day”, where we introduce our companies to investors. We observed that most accelerators run Demo Days at the end of their programs. But investors want to meet founders over time, so we put this event in the middle of the program, not end.

We host a CEO Forum, so founders can meet & build relationships with one another. 

David Teten: What tools do you find helpful for expediting due diligence? 

We use a detailed series of founder questions, check-the-box legal diligence steps, and subjective scoring via Airtable so we can continuously iterate with learnings over time. We focus on capitalization, product, customer discovery, market & timing, and team because that’s what our experience and the research shows is most important. 

We’re looking at automating the finance/legal onboarding. 

David Teten: Do you envision graduating from Airtable to a CRM?

Maybe. We’ve used CRMs extensively in the past. Like most VC funds, we’re small. We appreciate Airtable’s customization ability. The more users you have, the more governance you need over the ability to add/remove fields, and you might need a CRM.

David Teten: What are the tools you’re using for your middle office: tracking, risk management, etc.? What are the strengths and weaknesses of these providers?

Because we’re on Fund I, we haven’t yet built out much of this. We’re exploring using ChatGPT to ingest and process some of this.

David Teten: What are the tools you’re using for your back office: settlements, records maintenance, accounting, human resources, etc.? What are the strengths and weaknesses of these providers?

Fund admin: Vector AIS

HR/salary/1099: Gusto 

Legal: Gunderson

David Teten: What are the most creative or unusual ways you’re using AI & analytics in your organization?

Our Founder Index is based on data science. Used some image-gen tools (MidJourney, Dall-e) to create graphics for some of our posts. We believe we need to understand these tools, to see who’s legit and who’s a tourist.

We explored using synthetic interviews of founders: tell ChatGPT to act like a certain founder, e.g., Mark Zuckerberg, and answer our questionnaire. 

David Teten: What are your unmet technology needs?  Places in your firm where you’re seeking a solution and haven’t found an appropriate one? These may indicate room for Versatile VC to build or invest in a startup addressing that need.

Greg: I could use a personal CRM, ideally one that I don’t have to manually update. 

I currently use Rewind.AI . It watches my screen, and I can ask it questions but it has limitations in terms of understanding relationships. 

Jess: I’m looking for the right solution to stay in sync with our portfolio companies. Something that tracks investor updates over time, and reaches out to founders for updates when we haven’t heard from them, especially for how we can support. And overall enables transparency so we can track burn rate and cash balance without troubling our founders for that information.

David Teten: What processes are you focused on improving?

All of them!  Measure, iterate, repeat.

Fundraising and building deeper relationships with LPs is top of mind for us.

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