What I learned from spending my Saturday reading Reid Hoffman’s Blitzscaling

Buy the book ! Disclaimer: I make 0 revenue when you do.

Blitzscaling helps accelerate your startup growth into a 1B opportunity. Break things like Mark (facebook), and move fast like Brian (AirBnb) and Reid (Linkedin).

It also helps if you can raise a ton of capital pre or early stage revenue:)

These are some of my initial impressions. Here is my approach.

Whenever I read a book, I’ll typically treat it as a homework type book assignment. For me, this meant having a copy of the book (now often an E book) in one hand and a notebook in the other (now a laptop/tablet).

This often means I’m missing a lot of details, and also focusing only on what’s relevant to me or in this case our team at Pollen so I can save time for others by highlighting shared learnings.

We are in the FAMILY stage that Reid talks about, meaning 1–10 employees. Thus my notes are skewed towards things for very early stage startups.

Therefore, the below notes are not intended to be a definitive list or learnings or observations, but hopefully enough to give this great book some decent coverage for you to consider reading more on your own.

Main factors to blitzscaling

Technology.. obvious.

Business Model.. less obvious

Management.

Maximize Growth

1. Market Size TAM.. VCs want Billion Dollar markets. If 100M fund, need return 300M in 7–10 year life of fund to IRR of 15–22%. (1B ->3B) TAM must have >1B annual sales. Uber est was 10B, in 2016 actual was 26B. Startups create new demand so will be more than current sizings.

Advice: Find related markets, put it together, and think big

2. Distribution

Virality ->Linkedin used address book. Dropbox paid $40 for in person user ability tests, no one was able to signup, so they fixed the product issues for adoption first. MVP learnings.

High Gross Margins -> 60–80pct gross making goal for software, Amazon is 35%, GE 27%. Design high gross margin business. Xiaomi targets net margin of 1–3 pct(same as Costco)

3. Network Effects

A product or service is subject to positive network effects when increased usage by any user increases the value of the product or service for other users. Demand side economies, positive externalities. Nodes in a network create custom lock in. Look up Simon Rothman who built Ebay automotive marketplace.

1. Direct Network Effects- increase in usage, lead to increase in value (WhatsApp, WeChat)
2. Indirect Network Effects-increase in usage encourages consumption of complementary goods, which increases value of original product. Adoption of IOS/Android leads to more 3rd party devs, which increases value of platform
3. Two sided Network- increase in usage by one set of users increases the value to a different set of cap users (Airnb, eBay, uber, buyers/sellers)
4. Local Network Effects- increases by usage by small subset of users increases value fora. Connected user. Ex) wireless carriers ‘favorites’ list where calls didn’t count against monthly allotment of calls
5. Compatibility and Standards- Like Windows, MS office

Growth Tips:

Must get past Tipping point, even if losing money . Early adopters to mainstream, see Moore, Crossing the Chasm. Start with one market, then like bowling pins, get the others.

Linkedin discovered profile, even without any connections was valuable as an independent profile

AVOID GROWTH LIMITERS

1. Lack of product market fit. A good market with a product that can satisfy that market. Use NETWORK INTELLIGENCE. Leverage smart people in your network to vet your product.
2. Operational scalability- scale business.
3. Human limitations- try to create business model that doesn’t need a lot of headcount. WhatsApp leveraged address book. Find ways to outsource work, Airbnb hired photographers. “Do everything by hand until its too painful, then automate it”
4. Infrastructure Limitations- Friendster has server issues. Use AWS to modular scale up

Proven business model patterns

1.) Bits rather than atoms- focus on digital, not physical. AWS is amazon most profitable business

2.) Platforms- Build the standard platform, API to other platforms. Platform revenues like iTunes (30pct). Amazon merchant platform, facebook social graph

3.) Free or Freemium- Linkedin knew had to make profiles free, goal was 1M profiles to get critical mass

4.). Marketplaces- 2 sided network effects. Positive feedback loop with each transaction. Liquid market, where buyers/sellers both participate, supply/demand price better, and more efficient. Google Adwords is efficient market pricing with bidding, vs TV super bowl ads

5.). Subscriptions- video, music, com.

6.) Digital Goods- Line stickers. IAP in apps 37B vs 29B paid apps.

7.) Feeds- news feed like facebook. Twitter, slack, instagram.

Business Model Innovation

1. Moores Law- from Intel founder Gordon Moore. Computing power doubles every 18 months. Try to predict it like Reed Hastings, Netflix DVD-> digital.
2. Automation- computers work faster than humans
3. Adaptation, not optimization- continuous deployment, A/B testing, growth hacking
4. Contrarian- zero to one. “What important truth do very few people agree with you on” test courage.

Linkedin Case study:

1) Market Size , all “white collar workers” professional online identities

2). Distribution- initially VCs thought was a friendster for business relationships. Had to raise from friends/family until get to 1 M users from greylock. Got free office for 3 months.

Advice: Free office space is better than paid coworking. Paid Coworking is better than your own office. Scale accordingly to stage.

Core distribution was organic vitality. Users would invite contacts via email, because helped them build networks and keep track of key connections. Used EMAIL address book importer, to increase number of invites

1. Gross Margin- assumption was that business professional user worth more than social user. First model was freemium, limited number of requests users could send (in mails) and chance buy more . Big growth when companies wanted to pay to find job candidates. Enterprise subscription model
2. Network effects- direct and 2 sides network effectors.. Each LI user makes network more valuable, 2 sides more users get corp employers, while more employers increases job hunting tool.
3. Product Market Fit- hired salesperson with mockup of enterprise product, all wanted to buy
4. Operational scalability- Both consumer and enterprise product, created internal sales tools (merlin) to help sales teams prospect to companies

Amazon Case study:

Initial idea unlimited virtual shelf space where customers can buy anything.

Started with books because large enough market with product amendable to commence (durable, fairly standard sizes, readily avail through wholesale)

1. Distribution- 1st successful affiliate program. Retail is low margin business. US business profitable, but Asia isn’t.
2. Ecommerce, buys direct and sells
3. Marketplace- third party sellers sell on amazon. Store in amazon warehouse, and pay amazon to deliver. 50% of sales from third parties. Margins are closer to eBay (no inventory of its own, capital is from third party)
4. AWS, 150 pct of operating margins

Network effects- only amazon product reviews. Amazon sellers attacked to huge number of buyers, but buyers don’t care about number of sellers. Uses ‘Flywheel’ effect. Lower prices led to more customer visits. More customers increases volume of sales and attracted commission paying third party sellers to the site.Allowed amazon to get more out of fixed costs like fulfillment centers and servers needed to run the website. Greater efficiency enabled to lower prices further. Feed any part of flywheel and should accelerate the loop.

Product Market Fit- AWS started with just storage , S3 before expanding.

Facebook case study:

1. Distribution- start with universities. Wouldn’t launch as new university, until 50pct of students requested it
2. indirect network effects- graph api, facebook connect
3. Move fast and break things

Strategy Innovation

1. Make sure have network effects, customer lock in, otherwise a commodity like food delivery

Advice: Don’t build a food delivery type business (or try to in a new way)

Do things that don’t scale, then make choices for some things that have opportunity to scale

Hiring and Getting Started Tips

1. HIRE GENERALISTS when starting up 1–10 employees with ppl with early stage startup experience.
2. Choose 3–5 top metrics. E.g) youtube was watch time . Linked counted user registrations. # of sellers
3. Choose single channel, single product working first
4. Linkedin MVP- user professional profile, ability connect to other users, search function to find other users, messaging to friends. Learned needed address book

Fighting Fires. In this order.

1. Distribution
2. Product
3. Revenue model
4. Operations
5. Competition
6. What’s next

Make sure get distribution, what’s blocking. Then with distribution get product, then product get revenue

Do things that don’t scale (Paul graham of y combinator). Example airbnb manual photos