I recently migrated a custom CRM from code (MySQL/PHP/HTML/CSS/Javascript) to No Code, so I naturally look at a lot of these tools. For those unfamiliar, there are an increasing number of tools that allow people to create full blown apps without writing a line of code. Webflow is the king today, they provide both front end and back end functionality for creating an app. You can integrate this with Memberstack or Memberspace to add user functionality to this. Parabola is like Zapier, but for large swaths of data at a time – it can grab a MySQL table, merge it with your Mailchimp data, add columns, do some math, and spit out results in Google Sheets. Use these piping tools to add functionality like enrichment (Clearbit, Norbert, Snov) and machine learning (Intersect Labs, Obviously AI, Colabel, Lobe AI). For building internal tools, there’s also Notion, Coda, ClickUp, and Retool. It’s probably worth noting that Amazon jumped into this space with Honeycode. You can educate yourself at Makerpad or hire a no code agency like 8020.

Following the news cycle, it seems Shelter in Place is driven politically, with conservatives itching to get out and liberals sheltering in place (I’m overgeneralizing). We also know that urban environments help spread the virus, so it would make sense that these people would support shelter in place. Finally, we also know that urban areas tend to be more liberal. So is Shelter in Place really a political issue, or are we seeing urban areas hit hard, and therefor people in those areas (who happen to be liberal), support sheltering further?

If you know me, you know I like to play around with data, but to all of you a warning that I am not a data scientist, and this is really just me playing around. Please share any and all thoughts and resources to further this thought if of interest.

First thing I did was pull together some data around Shelter-In-Place, for this I used the SIP index provided by Safegraph, followed by political ideology, and urbanization. For ease, I did this by state as opposed to county, which would likely show more granular results. What I have looks like this:

The first thing I looked at was deaths per 100k and plotted them against the SIP index:

Not surprising to see a clear trend where the more deaths you see, the more likely you are to stay at home. The correlation coefficient we’re seeing here is 0.645.

Then I looked at % of conservatives in a state vs SIP Index:

Again, not surprising to see, but it’s pretty clear that the less conservative a state is, the more likely they are to shelter in place. Correlation coefficient here is -0.804.

Taking a look next at liberal % vs SIP Index:

Again, not surprising to see that the more liberal states are sheltering more. Correlation coefficient here is 0.658.

Now, let’s look at urbanization rate vs SIP Index:

Again, not surprising to see that the higher percentage of people living in urban areas show a higher shelter-in-place index. Correlation coefficient here is 0.788.

If you want to see these combined, it looks like this:

It looks very similar to when you compare against deaths/100k:

Of course, that’s because we saw that SIP Index and Deaths/100k are correlated.

Here’s where I get a little fuzzy. Can I normalize the percentage of people who are conservative against the percentage of people who live in urban areas and compare agains the SIP index to see a correlation? A high correlation would suggest that SIP index is driven by conservative values (or media) beyond simply their exposure from living or not living in urbanized places.

For this, I multiplied the percentage of conservatives against the percentage of people living in urban areas and compared against the SIP index.

What you see here is the correlation disappearing, with a correlation coefficient of -0.076.

This shows that perhaps Shelter-In-Place isn’t based as much on political values as the media might suggest, but just as much a function of people’s exposure to the virus due to proximity to urban areas.

I’ve received a lot of communication from founders about the impact of the recent epidemic on their business – some informative, some lackluster. Based on what I’ve seen, I created a rather simple framework to help founders communicate the key pieces of information that an investor (current or prospective) would want to hear.

I call it the Four Deltas.

The first two Deltas are the impact of the market on your business (outside of your control) in the short and long run. The second two Deltas are the impact of your actions on your business.

The First Delta (Δ₁) you need to communicate is the immediate impact of the current environment on your business – either positive or negative. This should start with hard numbers that can be measured. For example, you could start by looking at global (or local) changes in consumer spending specific to your industry, and then highlight the changes in your own KPIs. Each of these Deltas is multifaceted, and an important exercise is considering what few key numbers are most important to an investor.

The Second Delta (Δ₂) is the expected bounce back as things open up and return to “normal”. This is your opportunity to communicate your expectations around the future market dynamics of your business, including how long you expect this to last (should be a range), and relevant behavior changes that you expect will stick. Investors are thinking especially hard about the Δ₂ of business that are seeing sudden growth. For example, the Δ₂ of toilet paper should be equal to Δ₁ – meaning people will buy the eventually buy it at the same rate as they did before. For many industries, the Δ₂ is debated, such as for travel (will people travel the same as they did before?) and remote work (will people go back to the office?). I like Fred Wilson’s suggested baseline of expecting Δ₂ to be 50% of Δ₁ (article). Communicate to your investor your viewpoints on the Δ₂ of your business.

The Third Delta (Δ₃) is the impact of your actions on Δ₁. If your Δ₁ is positive, what are you doing to take advantage of the sudden growth? Considerations around this include the robustness of your infrastructure to handle growth, managing increased burn with fundraising expectations, and sensitivity in communicating positive news. If your Δ₁ is negative, what are you doing to survive? This should include everything from your cost cutting efforts to your fundraising plans. Don’t forget – people are here to help, don’t hesitate to ask for help.

The Forth Delta (Δ₄) is the impact of your actions on Δ₂. This is an opportunity to communicate your ability to strategize for the long-term. If your Δ₁ is positive, you want to communicate to investors how you are planning for the inevitable bounce back, and what you are implementing to minimize this – such as measuring and improving stickiness of your product. If your Δ₁ is negative, this may not be as important – people just want to know you’ll survive – but this is a great opportunity to paint a picture of what you’re doing today, to be one of the few survivors that sees an explosion in growth as things open back up.

*******

Take a moment to review how you’ve communicated to your investors thus far and make sure you’ve touched on each of these. This is your opportunity to show investors your thoughtfulness as a founder.

If you liked this, maybe follow me on Twitter @yoheinakajima.

I continue to be amazed at the content available for emerging GPs. This month, the content comes in the form of blog posts, but also zoom webinars and live audio talk shows.

I first heard Beezer Clarkson from Sapphire Ventures being interviewed on Semil’s Talkshow (listen here) on March 11th.  It was right after on Mar 14th that Samir Kaji posted his article “What I’m hearing in venture right now“, where he touches on fundraising for both startups and VCs. The next day he posted an article specific to Micro VC funding. Two days later, Lo Toney from Plexo Capital did his version of the Sequoia Black Swan article, but for GPs: The Economic Impact of  Coronavirus: What GPs Need to Know. Another two days later, Jim at SVB hosted a Zoom webinar:  Fundraising for Emerging VCs Post-Coronavirus, where he interviews three LPs – Joanna Rupp at University of Chicago, Michael Kim at Cendana, and Lindel Eakman at Foundry Group. I also enjoyed Michael Kim being interviewed on Strictly VC (here – Mar 20) and found Samir’s Emerging Manager Q&A mailbag from March 23rd a nice deep dive. Finally, Connie Loizos at Techcrunch shares wisdom from experienced GPs like Charles Hudson from Precursor, Eva Ho from Fika, and Aydin Senkut from Felicis: ‘A perfect storm for first time managers,’ say VCs with their own shops.

I know that’s a lot, so I’ll summarize a few take aways:

• It’s a great time to invest. Great startups are founded during recessions. Congrats if you have dry powder.
• Fundraising will be tough for GPs, especially new ones. Considerations for LPs include general uncertainty, desire for liquidity, allocation (esp. institutional), returning funds, and lack of in person meetings making it tough to build trust.
• For existing funds, an important time to support portfolio companies, communicate with LPs (esp. around expected capital calls and distributions), and review reserve strategy (eg. what percent of your companies need help, and how many can and should you support if they need a life line).

When asked questions by founders, I often send them articles from VCs who’ve said it better than I could. I always wished there was an easy way to search just content from blogs by VCs.

When James Augeri told me about his new startup Jingle last Thursday, I asked if he could help set this up, and we did it in a weekend! What’s more amazing is that our Thursday call was the first time we ever talked, after connecting on the Techstars Connect platform online.

This is a true #domorefaster #givefirst project.

Without further ado…

We’re excited to share askanything.vc – a search engine that only shows results from trusted VCs like Brad Feld, David Cohen, and Fred Wilson.

It’s great for searching startup terminology like “option pool”, “founder compensation”, or “valuation”. Check out some of the industry based searches that show interesting results like “autonomous vehicles” or “blockchain”.

No matter what you search, the results are only from a list of 100 or so VC blogs we’ve indexed for this search engine.

We hope founders and VCs alike find this a helpful tool to quickly find trusted information when they need it most.

Tweet us with questions or comments!

I randomly became curious about the graduation rate of startups from seed round to Series A round, specifically around the context of cities. I thought this might actually be more interesting to look at than total $ invested, or total number of rounds.

For the analysis, I looked at 6 major cities: SF, LA, Seattle, Boston, Chicago, NY.

I used Crunchbase data to pull all startups who raised a seed round in 2014, 2015, or 2016. I picked these years pretty randomly, but mostly because it felt recent enough, but not too recent.

I defined graduation rate as raising a Series A, anytime between their seed round and today.

Total companies in this list were 5114, with an average graduation rate of %20.3.

Here’s the chart:

Interestingly, Seattle and SF are leading the pack. LA was significantly lower.

Not sure why, but it’s interesting to see this.