Avoid Virality. Leverage Network Effects.

How to Transform Your Product Strategy to Unlock Long-Term Growth

Network effects - where your product provides more value the more users - is seen as the holy grail of product strategy.

However, many product leaders assume that network effects are the same as virality (they are not).

They also fail to understand that AI-driven network effects are not the same as user network effects.

In this article, I’ll outline why network effects are so powerful to bake into your product strategy, as well as the difference between virality v. network effects v. AI network effects.

Network Effects

A network effect is where your product provides more value the more users there are using the product.

Instagram is a great example: If you join Instagram & there are no other users or posts, it’s just an empty app (i.e. no value). However, if your friends are on it, and other users are constantly posting new content, there is more & more value for you over time as they post new content and/or you discover interesting users to follow.

Specifically, that means more engaging, more relevant content every time you open the app i.e. more value.

The more value you get, the more likely you are to invite your friends to join the app, thus fuelling a virtuous cycle of more users & more value creation.

(As we move into an AI-driven world where it’s very easy for anyone to build anything, it will be very easy to copy a product. Therefore leveraging network effects will become even more important as a way to defend your market share through a product with ever-increasing value).

AI Network Effects

An AI network effect follows the same principle of a virtuous cycle of value creation. The difference is that, with an AI network effect, you leverage AI to do two things:

1) Synthesise & learn from data to create insights about product usage

2) Leverage those insights to create more value

Google Search is a great example: The more searches made, the more the AI can learn about user behaviour. The more the AI learns, the better the search experience (better suggestions + more relevant links = more user value) & it unlocks the ability for advertisers to create relevant ads (more business value). The data created through Google Search even allows Google to launch other valuable services for its users, such as Google Maps.

Virality

Virality is where we see users sharing a product with each other. 

We say something has gone “viral” because, as each person shares the product to a few people, those few people share with a larger number of people, compounding quickly into thousands - even millions - of shares.

Sometimes, vitality will be combined with a network effect. Miro is a great example of this, where a user creating a work board & sharing it with their team drives other users to the product (vitality). By my team then collaborating on that work board, Miro becomes really valuable the more team members on there (network effect).

BuzzFeed is a good example of a viral product that failed to create a network effect. Despite hugely popular content that millions shared each week, BuzzFeed has since faded into obscurity as no extra value was created for users with each extra share or new website visitor. 

Why You Should Avoid Virality & Leverage Network Effects

Virality can be a powerful tool to drive user growth, but it rarely lasts.

You could gain 1m new users through “going viral”, but if you can’t retain those users, it doesn’t matter. You’ll see them all churn eventually.

Clubhouse is a great example - a great warning, in fact - of virality without network effects.

Clubhouse rode a wave - the pandemic - where those craving some sense of socialising with other people in a meaningful way translated well to the world of audio conversations through Clubhouse.

Clubhouse achieved virality (see the spike around March 2021 below). However, Clubhouse ultimately failed to create a network effect.

Despite the core value being user-generated content, which usually creates a strong network effect, Clubhouse failed to deliver largely because of things like:

• Too many low-quality conversations

• Difficulties discovering relevant content

• Inability to access valuable conversations (they were only streamed live, meaning you missed the conversation if you were busy at the time)

• Buggy experience because of the explosion of new users putting a strain on the tech infrastructure

Beware virality without proven retention and/or strong network effects.

Better, instead, to ignore - or even throttle, like Superhuman have done with a new user waiting list - virality.

Focus on building network effects. That’s the way to unlock meaningful, long-term user & revenue growth. Growth you can actually sustain.