Deep: How are companies building network effects?
Moat-enhancing features from top tier tech companies. Network effects, switching costs, economies of scale and more.
🔒 DoP Deep goes deeper into the concepts and ideas covered in the Weekly Briefing to help you learn lessons from the experiences of top tech companies. If you’d like to upgrade to receive these in-depth pieces of analysis you can upgrade below. New reports added every month.
Hi everyone 👋,
In the briefing, we recently mentioned that Spotify is rolling out a new generative AI capability and a new social feature that could potentially boost its network effects and fuel growth in ways that are difficult for competitors to copy.
In this Deep dive, we’ll explore 20+ examples of how other product teams from top tier tech companies including Google Maps, Bluesky, GitHub, Square, Perplexity, Miro and others are building new features which boost the network effects of their product.
As well as network effects, we’ll also explore other strategic ‘moats’ including IP, brand, economies of scale and more.
If you’re currently thinking about your own product / company’s strategy ahead of the new year and you’re exploring which features to build which might strengthen your differentiators and boost your growth or retention metrics, this collection of moat-enhancing features might help give you some inspiration.
Coming up:
How to identify and build network effects and other types of moats in your product
How Shopify is leveraging their scale of 2M+ merchants to build an unbeatable economic moat
GitHub’s new no-code platform and how it simultaneously creates network effects through shared templates while raising switching costs through accumulated workflows
Why Google Maps’ new feature could improve the overall user experience while strengthening platform lock-in
The 20+ companies featured in full
How this analysis is structured
For this deep dive report, we’ve hand-picked 20+ companies along with some features they’ve recently released which boost their network effects and other strategic moats.
The report breaks down each feature across the following dimensions:
Company - the company featured in the report. This includes 20+ companies spanning B2B SaaS and B2C consumer products including GitHub, Square, Miro and more to help give you a broad sample of different types of businesses.
Feature - the specific feature that creates a network effect or boosts another type of strategic moat. To some extent, all features boost strategic moats but we’ve specifically chosen ones that are explicitly tied to moats. For example, Notion’s template marketplace or Netflix’s new Moments features both boost network effects by encouraging users to share and bring other users onto the product, making it more valuable for all users.
Moat category - as well as network effects, there are 4 other moat categories. Some features span across 2 or more moat types. More details on the moat types included below.
How it works - more information on how each feature works - and how it boosts the specific network effect or moat feature.
Link to example - links to an example to find out more about how this specific feature works.
Moat categories explained
A network effect refers to the scenario where a product or service becomes more valuable to its users as more people use it. As well as network effects, other types of moats include: economies of scale, brand, intellectual property and high switching costs.
There are 5 core types of moat categories featured in this deep dive. Here’s a bit more about each of them:
Network effects - the feature draws other users to the product, making it more valuable for everyone who joins the product.
Economies of scale - features that are made possible thanks to the larger scale of certain companies. This can help them negotiate better rates with suppliers or spread higher costs across their user base.
Brand - brand recognition and brand naming can give companies an unfair advantage. Microsoft’s rollout of a single brand (Copilot) has enabled it to gain an early lead in AI for example.
Intellectual property / technology patents - proprietary technology or IP which can be leveraged to build difficult to copy features e.g. Stripe’s ML fraud detection technologies or Instacart’s proprietary shopping carts.
High switching costs - switching costs make it difficult for users to switch to competitors as a result of adopting a specific feature e.g. products built upon Google Maps’ new APIs might find it difficult to switch to a new provider. We’ll share some example of how other companies are doing this.
A closer look at the companies featured
Now that we’ve set the context, let’s take a closer look at some of the companies featured.