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The DL - An inside view into Pacific Northwest Tech

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Welcome to The DL, a weekly newsletter about tech, startups, and investing in the Pacific Northwest.
 
February 24 · Issue #36 · View online
The DL
Welcome to The DL, a weekly newsletter about tech, startups, and investing in the Pacific Northwest.

This week’s issue has the types of consumer brands and marketplaces that VCs love, a handy chart to find your perfect job, a spreadsheet that teaches you machine learning, and how much you need to earn to be in the richest 1% in different countries around the world.

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Consumer brands and marketplaces that VCs love
A few weeks ago, I wrote an article on why VCs love SaaS businesses, and some readers thought the takeaway was marketplace and consumer businesses are bad. Not what I meant! The takeaway was that SaaS startups should be evaluated differently than marketplace and consumer startups because they have different business models and capital requirements.

Consumer brands and marketplaces can be great VC investments, too, and last week Maveron published an article on what the best consumer companies look like, and a16z published an article on what the best marketplace businesses look like, so here are the key takeaways from both:

Consumer Brands
  • Most of today’s best brands start with niche, early adopter communities (e.g., Yeti and fishermen, Supreme and skateboarders)
  • VC funding should be the exception rather than the rule for consumer brands because niche brands take longer to scale and can’t authentically accelerate growth with Facebook and Google spend
  • VCs want to invest in brands that can grow 50%+ per year for 5-10 years after reaching $50M in revenue
  • Digitally-native brands have more in common with their legacy competitors than one another; Allbirds’ best comps are Nike and Vans, and Glossier’s best comps are beauty brands
  • SaaS companies are valued on revenue, but consumer brands are valued on EBITDA (20-30x)

Consumer Marketplaces
  • Four marketplaces account for 76% of consumer spend (Airbnb, Doordash, Instacart, and Postmates), and they are all in travel or food
  • The fastest growing marketplaces are growing 3-5x annually by connecting suppliers with pent up sources of demand (e.g., wholesale goods, celebrity engagement, streetwear)
  • Marketplaces that have city-by-city network effects tend to be highly fragmented (e.g., Doordash and Postmates) while marketplaces with global/national network effects are highly concentrated (e.g., Airbnb)
  • The “holy grail” of marketplaces are ones where customers spend $100+ per transaction and transact multiple times per month, but none of the 100 largest marketplaces today fit this criteria
  • (Here is a16z’s full list of the 100 largest private marketplaces based on credit card spend data)

Find your perfect job
Ever wonder… if I weren’t a _______, what would I want to do? Well here’s some research showing which jobs are most closely related to one another based on the personality profiles of people in those professions. Lots of great takeaways here:
  • 😆 Financial planners and car dealers have the same personalities (gold, lower left), as do recruiting managers and advertising execs (green, bottom), and paramedics and vice principals (orange, middle)
  • 😂 Politicians (red, bottom left) and software engineers (green, top) are literally on opposite sides of this personality traits and values map
  • 🤣 CEO’s personalities (grey, bottom middle) sit right in between social media specialists and coroners
  • ➡️ For a higher res image, click here, or check out the interactive visualization here

So all of it sounds about right… but where do you all think VCs would go? Maybe somewhere by the talent agents and boxing promoters?

Coolest spreadsheet ever
Excel is the MVP of the Office suite, and here is proof - you can implement computer vision algorithms in Excel without any special scripts or macros!

This spreadsheet was created by an Amazon engineer as an intro to Computer Vision for Amazon employees. He wrote everything in Excel, so you can follow along and understand how computer vision algorithms work using only Excel formulas.

Download the workbook here and check out the step-by-step sheets that slowly build up from how to identify lines/edges in a photo to eventually recognizing faces and text. Super cool!

Other stuff Dan's talking about
🥕 Peak vegan? - Sarah and I watched Game Changers last month and decided to be vegetarian for a week - turns out we weren’t the only ones! Interest in veganism spikes every January, but it looks like it might be plateauing in the US
💰 How to be in the top 1% around the world - What it takes to be in the richest 1% of earners in the US, China, Brazil, Australia, UAE, etc., and how much 1%-ers in each country spend on housing, education, and child care
🚍 2:30am tech shuttles - Tech shuttles move 10M people around the Bay Area every day, and they go as far out as Salida, CA, where there are so many people that the Tesla shuttle lot is “gridlocked” by 3:30am
11 reasons to not be famous - Tim Ferriss on why it’s hard to be famous: death threats, harassment of loved ones, dating woes, extortion, pleas for help, identity theft, and more. Better to have 1,000 “True Fans” – like my DL subscribers (❤️ you all!)

Please hit reply! (Or subscribe or forward!)
About me: I work as an investor at Madrona Venture Group, a Seattle-based venture capital firm that has been early partners with companies like Amazon, Smartsheet, Apptio, and Redfin.

If you have thoughts, questions, or comments, hit reply!

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