I discovered about the Network Effect in my recent podcast with Audrey Soussan, General Partner at the global VC firm, Ventech. In her words:
I am sure by now you’d be curious why this mechanism is so special and sought after in business. Let’s start with understanding what the network effect stands for.
What it Means
The network effect occurs when a product or service becomes more valuable as more people use it. This increase in value is not just for the company providing the service but also for every user of it. The basic idea is that the utility or enjoyment a user gets from a product increases when others also use the product.
Let’s check out the different Network Effects:
- Direct Network Effect: More users joining boosts value. Ex: Discord grows as it reaches beyond gaming.
- Indirect Network Effect: Value rises with complementary offerings. Ex: Tesla’s Supercharger network makes Tesla ownership more appealing.
- Two-Sided Network Effect: Value increases when one user group grows, benefiting another group. Ex: DoorDash gains as more restaurants and users join.
- Local Network Effect: Value is tied to personal network adoption. Ex: Signal becomes more valuable as more personal contacts use it.
- Cross-Side Network Effect: Growth in one group boosts value for another group, not vice versa. Ex: Twitch’s value for streamers rises with more viewers.
- Data Network Effect: More data improves the service, attracting users. Ex: OpenAI’s models improve with user feedback, enhancing accuracy and versatility.
Why a VC Would likely Invest
- Sustainable Growth: Companies with network effects tend to grow at an exponential rate once critical mass is achieved, as each new user adds value for all existing users, thereby attracting more users in a virtuous cycle.
- Competitive Moat: The network effect creates a significant barrier to entry for potential competitors. A well-established network is difficult to displace, as the value it provides grows with each new user, making it harder for new entrants to offer comparable value.
- Increased User Engagement: As the network grows, so does user engagement. Products or services that benefit from network effects often become more integral to users’ daily lives or workflows, leading to higher retention rates.
- Data Advantages: In many cases, the network effect coincides with the accumulation of valuable data, which can improve the service, create new revenue opportunities, and further entrench the company’s market position.
- Scalability: Network effects often allow for scalable growth without a corresponding increase in costs. This scalability can lead to higher margins and profitability as the user base expands.
Let’s talk about OpenAI
LLMs like GPT-4 don’t naturally exhibit network effects because each user’s interaction is independent, unaffected by others. This independence makes users more likely to switch to another LLM if it offers similar or better features, accuracy, or pricing. As a result, LLMs face the risk of becoming commodities, where competition is based mainly on pricing and availability.
Open AI could however dominates the LLM market due to 3 main reasons (superior performance of its models, substantial financial resources-largely due to courtesy of Microsoft’s fundings and then it planting seeds of the network effect by introducing ChatGPT plugins, enabling developers to integrate it into their apps.
Improvement of the Model (Data Network Effect)
Every interaction with any of OpenAI’s GPT models, generates data. This includes questions asked, corrections made by users, and feedback on the relevance and accuracy of responses. This data is invaluable for training and refining the AI, making it more sophisticated, contextually aware, and capable of generating accurate and relevant responses.
People Using It (Direct and Indirect Network Effects)
The 2 kinds of Network Effects at play here are:
-Direct Effect: While these models don’t exhibit a traditional direct network effect (where each new user directly increases the value for other users by their mere presence), the collective data contributed by users indirectly benefits the entire user base by improving the model.
-Indirect Effect: There’s also an indirect network effect at play through the development of applications and services built on top of these models. As more businesses and developers use them to create new tools, services, or integrations, the platform becomes more valuable. This increased utility attracts more users, who then contribute more data, further fueling the model’s improvement.
Consider this if you plan to leverage it
- Achieving Critical Mass: To get there, a significant upfront investment in user acquisition is often required without immediate returns.
2. Monetization Strategies: It’s has to be delicate balance while introducing monetization without alienating users, especially for platforms that start free.
3. Network Quality vs. Quantity: Maintaining quality as the network grows can be difficult, and could risk user experience. It could be necessary Implement quality control mechanisms to ensure a positive user experience.
4. User Retention and Engagement: Keeping users engaged and active over time is a constant challenge, even after initial growth.
7. Regulatory and Ethical Considerations: Growing scrutiny around data privacy, content moderation, and market dominance as the network expands.
And most importantly, competitors can still pose a threat, finding ways to attract your market segment. You need to stay alert to competition and continuously improve the user value proposition.
Final Thoughts
Network effects are the #1 way to create defensibility in the digital world. Companies with the strongest types of network effects built into their core business model tend to win, and win big.