Book Summaries

Book Summary – The Cold Start Problem by Andrew Chen

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In The Cold Start Problem: How to Start and Scale Network Effects, former Uber executive and startup investor at Andreessen Horowitz (a16z) Andrew Chen writes a definitive guide on the concept of Network Effects. He provides a framework for building Network Effect into product development and scaling an enterprise.

The Cold Start Problem explores how tech’s most successful products and companies solved the dreaded “cold start problem” by using network effects to launch and ultimately scale to billions of users.

The Cold Start Problem provides practical frameworks and principles that can be applied across products and industries—revealing what makes winning networks successful, why some startups fail to successfully scale, and most crucially, why products that create and compete using the network effect have become vitally important today.

About Andrew Chen: From Uber to a16z

Chen was a member of the Driver Growth Team at Uber, which was responsible for recruiting the scarcest asset in the entire business, Uber drivers. On Leaving Uber in 2018: “The company had a tumultuous few years, a complete changing of the guard, and a new set of priorities that were less entrepreneurial than in the past. ”

Startup Investor at Andreessen Horowitz.

“In 2018, I began a new career after Uber, as a startup investor at Andreessen Horowitz. Started a decade earlier by entrepreneurs Ben Horowitz and Marc Andreessen, the firm made a splash when it launched, making a series of notable investments in startups including Airbnb, Coinbase, Facebook, Github, Okta, Reddit, Stripe, Pinterest, Instagram, and others. ”

The Definitive Guide to Network Effects

The Cold Start Problem is the culmination of hundreds of interviews, three years of research and synthesis, and nearly two decades of experience as an investor and operator. It takes much of the as an investor and operator. It takes much of the knowledge and core concepts swirling inside the technology industry and frames them in the context of the beginning, middle, and end of a network’s life cycle.

What’s a Network Effect?

Network effects, where a product or service’s value increases as more users engage with it, provide a path for fledgling products to break through, attracting new users through viral growth and word of mouth.

A network effect describes what happens when products get more valuable as more people use them.

Network effects are embedded into many of the most ubiquitous and successful tech products around us, in different variations. Products like eBay, OpenTable, Uber, and Airbnb are examples of marketplace networks, comprising buyers and sellers.

Dropbox, Slack, and Google Suite are workplace collaboration products built from the network of your teammates and coworkers. Instagram, Reddit, TikTok, YouTube, and Twitter are networks of content creators and consumers (and advertisers!).

The products become useful as more people use them.

Uber Network Effect Example

For Uber, the more users joined the app, the more likely it would be for riders to quickly find someone to take them from point A to B. It also meant that it would be easier for drivers to fill their time with trips, increasing their earnings.

Although the networks don’t own their underlying resources, it’s the connection that matters. The entire ecosystem stays on because the value is in bringing everyone together. That’s the magic.

Metcalfe’s Law

Originally formulated in the 1980s by Robert Metcalfe, an early computer networking pioneer, this theory defines the value of a network as a mathematical function based on the number of connected devices (fax machines, telephones, etc.).

The systemic value of compatibly communicating devices grows as a square of their number. Said plainly, each time a user joins an app with a network behind it, the value of the app is increased to n^2. That means if a network has 100 nodes and then doubles to 200, its value more than doubles—it quadruples.

The Cold Start Theory

Cold Start Theory lays out a series of stages that every product team must traverse to fully harness the power of network effects. The curve represents the value of the network as it builds over time, and is shaped as an S-curve with a droop at the end.

Five Stages of the Cold Start Theory

It is made up of five stages for creating, scaling, and defending the network effect, and aims to provide a road map for any new product team—at a startup or larger company—to leverage in their work. There are five primary stages:

  • The Cold Start Problem
  • Tipping Point
  • Escape Velocity
  • Hitting the Ceiling
  • The Moat

1. The Cold Start Problem

Most new networks fail. If a new video-sharing app launches and doesn’t have a wide selection of content early on, users won’t stick around. The same is true for marketplaces, social networks, and all the other variations of consumer (and even B2B) products—if users don’t find who or what they want, they’ll churn. This leads to a self-reinforcing destructive loop.

New products die when they flub their initial entry into the market, and their networks collapse before they even start. Every networked product, including Slack, starts with just a single network.

The solution to the Cold Start Problem starts by understanding how to add a small group of the right people, at the same time, using the product in the right way. Getting this initial network off the ground is the key, and the key is the “atomic network”—the smallest, stable network from which all other networks can be built.

Anti-Network Effects

Solving the Cold Start Problem requires getting all the right users and content on the same network at the same time—which is difficult to execute in a launch. It’s a myth that network effects are all powerful and positive forces—quite the opposite. Small, sub-scale networks naturally want to self-destruct, because when people show up to a product and none of their friends or coworkers are using it, they will naturally leave.

Atomic Network

The smallest possible network that is stable and can grow on its own. The smallest network where there are enough people that everyone will stick around.

Example of Atomic Networks: Zoom’s videoconferencing network can work with just two people, whereas Airbnb’s requires hundreds of active rental listings in a market to become stable.

Atomic Network: A stable, self-sustaining group of users who can drive a network effect.

These networks often have “sides,” whether they are buyers and sellers, or content creators and consumers. Generally one side of the network will be easier to attract—this is the easy side of the network. However, the most important part of any early network is attracting and retaining “The Hard Side” of a network—the small percentage of people that typically end up doing most of the work within the community.

2. Tipping Point

To win a market, it’s important to build many, many more networks to expand into the market. As a network grows, each new network starts to tip faster and faster, so that the entire market is more easily captured.

Example – Tinder

As Tinder’s successful initial launch at the University of Southern California unlocked other colleges nearby. This was followed by cities like Los Angeles, then broader regions, and then entire markets—including India and Europe.

3. Escape Velocity

The Escape Velocity stage is all about working furiously to strengthen network effects and to sustain growth.

The three underlying forces of escape velocity

  • Acquisition Effect: Lets products tap into the network to drive low-cost, highly efficient user acquisition via viral growth;
  • Engagement Effect: Increases interaction between users as networks fill in;
  • Economic Effect: Improves monetization levels and conversion rates as the network grows.

4. Hitting the Ceiling

A  rapidly growing network wants to both grow as well as tear itself apart, and there are enormous forces in both directions.

In the real world, products tend to grow rapidly, then hit a ceiling, then as the team addresses the problems, another growth spurt emerges. Then follows another ceiling. Then another cycle after that, each one often successively getting more complex to address over time as the problems become more fundamental.

5. The Moat

The final stage of the framework focuses on using network effects to fend off competitors, which is often the focus as the network and product matures.

Network-based competition

Network-based competition—that isn’t just about better features or execution, but about how one product’s ecosystem might challenge another’s.

The upstart has to pick off niche segments within a larger network, and build atomic networks that are highly defensible with key product features, and, when applicable, better economics and engagement. The incumbent, on the other hand, uses its larger size to drive higher monetization and value for its top users and fast-following any niches that seem to be growing quickly.

The Hard Side

They do more work and contribute more to your network, but are that much harder to acquire and retain. For social networks, these are often the content creators that generate the media everyone consumes. For app stores, these are the developers that actually create the products. For workplace apps, these are the managers that author and create documents and projects, and who invite coworkers to participate. For marketplaces, these are usually the sellers and providers who spend their entire day attracting users with their products and services.

“The hard side of Wikipedia’s network is minuscule—a mere 0.02 percent of highly motivated users create the content for the rest of the network.”

1/10/100 Rule

  • 1% of the user population might start a group (or a thread within a group)
  • 10% of the user population might participate actively, and actually author content whether starting a thread or responding to a thread-in-progress
  • 100% of the user population benefits from the activities of the above groups (lurkers)

All the best in your quest to get better. Don’t Settle: Live with Passion.

Lifelong Learner | Entrepreneur | Digital Strategist at Reputiva LLC | Marathoner | Bibliophile |

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