In platform business models usually, network effects, meant as positive ones get all the credit. However, understanding negative network effects is as important to make sure you’re keeping the value of the platform improve over time.
As highlighted in the interview with Sangeet Paul Choudary, author of Platform Scale and Platform Revolution:
The more people using the highway system, the more traffic jams you end up in. Or the more people in a room, the less likely it is to have good decent conversation just because it gets crowded, but also because everybody is talking too loudly and so you can’t hear and you can’t meet the right person within that room.
So we understand congestion in traditional terms because in the traditional world we have networks that were limited by scale.
When it comes to the digital world, instead, there are no scale limitations. Or at least those can be overcome. Indeed, that is the whole premise of network effects. Where in a physical world, it’s easy to get to the point of congestion.
However, there is a certain point in which a network effect might become negative. As highlighted in the interview with Sangeet:
What happens is the more users come on board, the more difficult it becomes to manage quality of the interactions.
Examples of negative network effects
Google case study
In a platform that leverages on direct side network effects after a certain number of users, it might also result in increased spam on the platform which can’t be easily managed through automated processes, or human curation, thus diluting the value of the platform.
Take the case of how Google, back in the days, it was offering an index of the web with its core algorithm called PageRank. At a certain point had to figure out also how to manage the spam on its index.
Practitioners understood how to trick Google’s core algorithm into showing up spammy results on top of that. This would have jeopardized the value of the overall platform, thus resulting in a diluted value of that.
Thus Google had to start to build up a solid team dedicated to spam and update its algorithms to avoid spam in search results in order to keep its platform valuable.
Airbnb case study
Take Airbnb where, for instance, more hosts improve value for users on the platform. On the two-sided more value is created by more hosts (travelers have more selection)? On the other hand, the value of the platform is diluted on the hosts’ side of the platform.
They will find themselves competing for the same users.
Thus it becomes crucial to understand what’s the proper ratio between travelers and hosts on the platform to make sure it keeps being valuable on both sides.
Tinder case study
Quite the opposite. If a critical mass is not reached at each local hub, the platform might lose value quickly. Imagine the case of a woman looking for a date. The faster she will be able to meet the best match.
The more the platform will be valuable. However, to be very valuable, the service has to make sure those people can meet in a place nearby. And it there are no matches available locally, the dating platform would lose value quickly.
Platform business models can leverage network effects to enable the core platform to become more valuable over time. However, they need to factor in negative network effects, which if picking up might not only prevent the success of the business but also destroy it.
Other business resources:
- What Is a Business Model? 30 Successful Types of Business Models You Need to Know
- The Complete Guide To Business Development
- Business Strategy: Definition, Examples, And Case Studies
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- What Is Market Segmentation? the Ultimate Guide to Market Segmentation
- Marketing Strategy: Definition, Types, And Examples
- Marketing vs. Sales: How to Use Sales Processes to Grow Your Business
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- Growth Hacking Canvas: A Glance At The Tools To Generate Growth Ideas