I met an entrepreneur yesterday who confidently stated that his product was going to grow ‘virally’ because it was the best in its category. That was essentially the optimism that powered the growth slide in his investor deck. (To see why this is wrong at many levels, read point 2 below, but more on that later)

The problem: Investors weren’t buying this pitch of his yet.

Why don’t investors get it?

Frankly, too many startups out there have claimed that they will grow virally and too few actually have. Here are the top three reasons why a startup’s claim to going viral may not be well-founded.

1. They don’t have a clue about user acquisition

Imagine this! You don’t have a clue how you’re going to get users. There’s an empty slide in your deck reading user acquisition, which follows the slide showing hockey stick adoption.

The solution? We’ll grow virally! Three words that fill up the slide nicely.

This may sound naive but investors have seen so many startups use this route that they automatically clam up when someone presents virality as the only source of user acquisition.

The second problem with this is as follows: Virality is users bringing in other users. For that, you need some users on the product in the first place. Hence, virality can only work in tandem with other user acquisition models, which bring in users, who then bring in other users. Relying on virality as a standalone source of user acquisition is fatally flawed to begin with.

Key Point: Virality is unpredictable and works only in tandem with other sources of user acquisition. 

2. They’re confusing Virality vs. Word of Mouth

So here’s one of the biggest problems with entrepreneurs claiming their startup is going to go viral. Often, they don’t understand what virality is in the first place.

Virality and Word of Mouth are two concepts that are often conflated and confused.

Word of Mouth is what happens when people love your product so much, they just can’t stop talking about it. Word of Mouth is driven by your ability to deliver customer delight and your ability to convert users into fans. It’s largely an art, and one that you can’t necessarily structure or control. You can maximize the chances of generating WOM by delighting your users but you can’t force them to start talking about it.

Organic virality, on the other hand, is what happens when users spread the word about your product in the context of using the product. It, unlike Word of Mouth, has nothing to do with how much they love your product. When users share an Instagram photo on Facebook, Instagram gets exposed to other users. When a Kickstarter project creator spreads the word about his project, KickStarter gets greater adoption. In all these cases, the existing users get extra value out of taking an action, which in turn, exposes your product to new users. If you can architect that into your product, you’ve got virality going. You don’t need fans any more, you just need users, to bring in other users.

Word of Mouth works effectively for online as well as offline products. Virality works only for networked businesses, and hence, largely for online businesses. Users need to be connected to each other for them to spread the word about a product during the course of product usage.

Investors like products that have organic virality of the kind shown above. Products that spread with usage are ideal for venture scale returns. Hotmail, Surveymonkey, Paypal, Skype, KickStarter, YouTube and Instagram are all examples of such products that have performed extremely well.

Organic virality is more controllable. You can design your product in a manner that it leverages users’ interest in sharing what they create on the product. In contrast, Word of Mouth cannot be designed.

Key point: Figure out whether you’re relying on WOM or organic virality. WOM can rarely be controlled and designed. Organic virality is something that is designed within the product.

3. They’re The New Invite Spammers

Word of Mouth can’t be designed. But it can definitely be forced and/or manipulated.

We saw a lot of this happen in the early years of the Facebook Platform. Get users to send irrelevant invites and notifications onto the news feed. The problem with these invites were that they were little more than spam.

This notion continues to exist even though Facebook has tightened its policies. Startups still believe that virality is nothing more than an invite loop that can be slapped onto a product after the product is created. More often than not, this approach leads to invite spam.

The problem is compounded with an obsession with optimizing virality by maximizing ‘k’, the viral factor. If your viral loop itself is leading to spam, maximizing ‘k’ will make the spam problem even worse. We’ve seen this play out with Branchout and Skillpages, and with countless games.

Key point: Conning users into sending invites is poor design, unsustainable, and leads to users abandoning in the long run (even if you get adoption in the short run). 

Marketplaces are difficult businesses to run. Like all multi-sided platform businesses, they suffer from the classic chicken and egg problem: the technology has no value unless buyers and sellers are present and you can’t get the buyers on board unless you have sellers and you can’t bring in sellers without having buyers. Hence, building a marketplace is a lot like building two separate companies simultaneously, each dependent on the other.

There are three factors that determine success for a marketplace business:

Liquidity or critical mass

The lifeline of a marketplace (and any platform business for that matter) is liquidity. Liquidity is a state where there are a minimum number of producers and consumers on the marketplace and there is a high expectation of transactions taking place. This is similar to the critical mass of users that is needed on a social network for users to find value in the network. Critical mass is a state where there is enough volume of supply and demand, for transactions to start sparking.

The first and most important metric to watch out for is the percentage of listings that lead to transactions within a certain time period. This serves as a proxy for the efficiency of the marketplace. Merely increasing the number of buyer and seller sign-ups doesn’t serve a purpose unless this metric starts rising. The time period would depend on the category. AirBnB listings would find transactions sooner than listings on a buy-and-sell  real estate marketplace. This could also depend on ticket sizes within the same category. Fiverr and oDesk are both services marketplaces but the turnover on Fiverr is most likely higher, owing to the much smaller ticket sizes.

To get to liquidity, the marketplace also needs to solve the chicken and egg problem and get both buyers and sellers on board. Marketplaces leverage a variety of tactics for circumventing this problem including building single user utility, stealing traction and piggybacking other platforms.

Matching: Curation of products/service

Users visit a marketplace with a highly transactional intent and want to find what they’re looking for at the earliest. In this aspect, transaction businesses are remarkably different from engagement businesses. A user visiting AirBnB or Yelp has a specific intent in mind. Hence, the quality of the search algorithm and the intuitiveness of the navigation are critical to delivering value. In contrast, a user visiting Pinterest often wants to spend some time and consume content on the platform. Hence, the infinite scroll!

The efficiency of discovery and matching is critical to a marketplace’s success. Percentage of searches that lead to listing profile visits within the first page of results is one such metric. When listings are served instead, as a feed, the clickthrough per session can serve as a proxy as well. The best metric to track matching efficiency varies with the business model of the marketplace as well as the category.

Trust: Curation of participants

Building trust is central to marketplaces where transactions carry risk. AirBnB is an example of a player in a high-risk category, that succeeded because of its ability to curate its participants. AirBnB allows hosts and travelers to review each other and has one of the highest review rates among marketplaces. It also takes additional measures to build trust, including having photographers certify a host’s listing.

This was one of the factors that helped AirBnB challenge CraigsListbecause CraigsList never built a strong curation system for participants.

Focus on the trust metric is very important to move from appealing to an early adopter audience to appealing to a mainstream audience. While early adopters use new marketplaces because of the novelty, opening up to a larger market requires the trust and reputation management systems to be alive and kicking.

What’s not as important:

User interface and design are less important with transactional businesses as compared to engagement businesses.

On a marketplace, the ability to search and transact/interact should be as intuitive as possible. Beyond that, the look-and-feel and design are purely hygiene factors. Unlike social networks, marketplaces are transactional and users typically don’t have long visit lengths engaging with the product. Hence, UI is not as important a criterion as the other three mentioned above.

In summary, if you’re building a marketplace:

1. Focus on liquidity, not just user growth

2. At critical mass and beyond, closely track matching efficiency

3. When moving from an early adopter to a mainstream audience, ensure that the trust systems are in place and functioning well.

Short Answer: It’s complicated!

Long answer follows…

Pipes and Platforms are two contrasting business models, as we noted in the last post. However, the internet itself is a platform on which others (you, me, web developers, app makers, everyone) create value. By virtue of this fact alone, every business on the internet exhibits some Platform characteristics, even if it may appear to be a Pipe. Platform Thinking is an approach to creating internet businesses with platform characteristics.

The question above was raised by one of the readers as a comment to the previous post and I felt it needed a post in itself as an answer.

Let’s start with a framework in mind. There are three broad properties of a platform:

Magnet: A platform needs to get both producers and consumers on board

Toolbox: A platform needs to provide the tools required for producers and consumers to interact (and transact)

Matchmaker: A platform needs to match producers and consumers, leveraging data

Let’s take a quick look at Amazon with this lens. I will deliberately be taking an over-simplified view of some of Amazon’s business lines here as this is meant to be purely illustrative.

Amazon, the Pipe…

Amazon started out as a Pipe. Establishing the online store model, it managed the producer role itself by sourcing products, managing inventory and selling them down the pipe, Amazon.com. A very linear model, it simply brought the offline store model online and users continued to be customers, except for one small difference.

Verdict: Store = Pipe

… with elements of a platform…

Amazon did set out building its main business (of selling books etc.) on a pipe model. However, Amazon first dabbled with a platform model on its reviews ‘feature’. Reviews could be created by users and consumed by other users, and in that sense, Amazon allowed creation of value by producers (review creators) on a platform (Amazon.com). The main business continued to be a pipe but it showed platform characteristics with its reviews. A business using Pipe Thinking would just have sourced expert reviews but Amazon used Platform Thinking to create an entirely new source of product reviews.

Verdict: Reviews = Magnet (+ Toolbox)

… and data-driven efficiencies…

Unlike pipes, platforms are intelligent. Also, platforms exhibit network effects of data. The more the number of users using a system, the more valuable the system becomes for every individual user because of the usage data that it collects.

The second way in which Amazon used Platform Thinking was to enable the “Users who liked this also liked this…” feature. This was an instance of the Matchmaker role where Amazon used data about consumer usage to match them with the right products. This collaborative filtering model became more accurate and, hence useful, as more users used it.

Network effects of data are absolutely non-existent in traditional pipes in the offline world. A TV program doesn’t get more interesting as more people watch it. (In today’s world it does, on a second screen: a mobile app, again working on Platform Thinking).

Verdict: Collaborative Filtering = ~Matchmaker

…transitions from a pipe structure to a platform structure…

Amazon’s main business eventually moved away from a Pipe model to a Platform model when Amazon launched Amazon Marketplace allowing external merchants to sell their goods via Amazon. Amazon continued to be a producer, but allowed other producers to also create and transact on the platform. This was the key transformation that moved Amazon’s business model completely to a Platform model.

Verdict: Amazon Marketplace = Magnet + Toolbox + Matchmaker

…and allows extenders to extend the platform…

Another hallmark of Platform Thinking is the fact that external parties can extend the properties of the Platform. Referencing the three-part framework mentioned above, Amazon extended its platform in the following ways:

Affiliate Program and Widgets: This allowed users to play the Magnet role and get other users to Amazon, by peppering links to Amazon across the internet. Given that users played the Magnet role, Amazon compensated them as well.

API: API developers could extend the functionality of the platform.

Verdict: Amazon = Extend(Magnet) + Extend(Toolbox)

…creates the device-as-a-platform…

Finally, with the launch of Kindle publishing and the Kindle hardware, Amazon applied Platform Thinking to the publishing world. The publishing world has long existed on a Pipe model where editors control access to the Pipe. With Kindle Direct Publishing, Amazon has created the largest publishing platform allowing authors (producers) to directly publish and access a market of readers (consumers).

Verdict: KDP = Magnet + Toolbox + Matchmaker

…and allows extenders to extend the device-as-a-platform…

Kindle started as a reading device but, with the launch of Kindle fire, has been reinvented as a full-featured tablet. Amazon now allows app developers (platform extenders) to create applications specifically for the Kindle Fire App Store.

Verdict: App Store = Extend(Magnet) + Extend(Toolbox) + Extend(Matchmaker)

… and decides on extending its infrastructure as a toolbox for all…  

Finally, with AWS, Amazon realized that the infrastructure that it had set up to power its own operations, could be offered on a subscription model to developers externally. A Toolbox of sorts, AWS provides the underlying tools and technology for developers to create their respective applications on top of it.

Verdict: AWS = ~Toolbox 

Takeaways

Amazon is a great case study to illustrate several facts:

1. Even while acting as a Pipe, an internet business can show Platform properties (e.g. user-generated reviews).

2. Any system that uses data can leverage network effects and become more useful as more users use it. Traditionally, we associate network effects only with full-fledged Platform models. However, Amazon’s collaborative filtering feature shows that network effects can exist even on a linear model if it uses aggregate data to create value.

3. Pipes often transition to Platforms. Amazon opening up, first its marketplace, and then its publishing platform, demonstrates a great way of building a platform without having to worry about the chicken and egg problem. Start as a Pipe, get consumers hooked, and use that traction to attract producers and open up the Platform.

4. Many internet businesses may exhibit only one or two of the three platform properties. AWS only acts as a Toolbox. TripAdvisor (an independent business similar to Amazon’s review feature) plays more of a Magnet role only.

Why are marketplaces such difficult businesses?

Why do startups with the best technology fail so often?

There are two broad business models: pipes and platforms. You could be running your startup the wrong way if you’re building a platform, but using pipe strategies.

More on that soon, but first a few definitions.

Pipes

Pipes have been around us for the last 400 years. They’ve been the dominant model of business. Firms create stuff, push them out and sell them to customers. Value is produced upstream and consumed downstream. There is a linear flow, much like water flowing through a pipe.

We see pipes everywhere. Every consumer good that we use essentially comes to us via a pipe. All of manufacturing runs on a pipe model.  Television and Radio are pipes spewing out content at us. Our education system is a pipe where teachers push out their ‘knowledge’ to children. Prior to the internet, much of the services industry ran on the pipe model as well.

This model was brought over to the internet as well. Blogs run on a pipe model. An ecommerce store like Zappos works as a pipe as well. Single-user SAAS runs on pipe model where the software is created by the business and delivered on a pay-as-you-use model to the consumer.

Platforms

Had the internet not come up, we would never have seen the emergence of platform business models. Unlike pipes, platforms do not just create and push stuff out. They allow users to create and consume value. At the technology layer, external developers can extend platform functionality using APIs. At the business layer, users (producers) can create value on the platform for other users (consumers) to consume. This is a massive shift from any form of business we have ever known in our industrial hangover.

TV Channels work on a Pipe model but YouTube works on a Platform model. Encyclopaedia Britannica worked on a Pipe model but Wikipedia has flipped it and built value on a Platform model. Our classrooms still work on a Pipe model but Udemy and Skillshare are turning on the Platform model for education.

Business Model Failure

So why is the distinction important?

Platforms are a fundamentally different business model. If you go about building a platform the way you would build a pipe, you are probably setting yourself up for failure.

We’ve been building pipes for the last few centuries and we often tend to bring over that execution model to building platforms. The media industry is struggling to come to terms with the fact that the model has shifted. Traditional retail, a pipe, is being disrupted by the rise of marketplaces and in-store technology, which work on the platform model.

Pipe Thinking vs. Platform Thinking

So how do you avoid this as an entrepreneur?

Here’s a quick summary of the ways that these two models of building businesses are different from each other.

User acquisition

User acquisition is fairly straightforward for pipes. You get users in and convert them to transact. Much like driving footfalls into a retail store and converting them, online stores also focus on getting users in and converting them.

Many platforms launch and follow pipe-tactics like the above. Getting users in, and trying to convert them to certain actions. However, platforms often have no value when the first few users come in. They suffer from a chicken and egg problem, which I talk extensively about on this blog. Users (as producers) typically produce value for other users (consumers). Producers upload photos on Flickr and product listings on eBay, which consumers consume. Hence, without producers there is no value for consumers and without consumers, there is no value for producers.

Platforms have two key challenges:

1. Solving the chicken and egg problem to get both producers and consumers on board

2. Ensuring that producers produce, and create value

Without solving for these two challenges, driving site traffic or app downloads will not help with user acquisition.

Startups often fail when they are actually building platforms but use Pipe Thinking for user acquisition.

Pipe Thinking: Optimize conversion funnels to grow. 

Platform Thinking: Build network effects before you optimize conversions. 

Product Design and Management

Creating a pipe is very different from creating a platform.

Creating a pipe requires us to build with the consumer in mind. An online travel agent like Kayak.com is a pipe that allows users to consume air lie tickets. All features are built with a view to enable consumers to find and consume airline tickets.

In contrast, a platform requires us to build with both producers and consumers in mind. Building YouTube, Dribbble or AirBnB requires us to build tools for producers (e.g. video hosting on YouTube) as well as for consumers (e.g. video viewing, voting etc.). Keeping two separate lenses helps us build out the right features.

The use cases for pipes are usually well established. The use cases for platforms, sometimes, emerge through usage. E.g. Twitter developed many use cases over time. It started off as something which allowed you to express yourself within the constraints of 140 characters (hardly useful?), moved to a platform for sharing and consuming news and content and ultimately created an entirely new model for consuming trending topics. Users often take platforms in surprisingly new directions. There’s only so much that customer development helps your with.

Pipe Thinking: Our users interact with software we create. Our product is valuable of itself.

Platform Thinking: Our users interact with each other, using software we create. Our product has no value unless users use it.

Monetization

Monetization for a pipe, again, is straightforward. You calculate all the costs of running a unit through a pipe all the way to the end consumer and you ensure that Price = Cost + Desired Margin. This is an over-simplification of the intricate art of pricing, but it captures the fact that the customer is typically the one consuming value created by the business.

On a platform business, monetization isn’t quite as straightforward. When producers and consumers transact (e.g. AirBnB, SitterCity, Etsy), one or both sides pays the platform a transaction cut. When producers create content to engage consumers  (YouTube), the platform may monetize consumer attention (through advertising). In some cases, platforms may license API usage.

Platform economics isn’t quite as straightforward either. At least one side is usually subsidized to participate on the platform. Producers may even be incentivized to participate. For pipes, a simple formula helps understand monetization:

Customer Acquisition Cost (CAC) < Life TIme Value (LTV)

This formula works extremely well for ecommerce shops or subscription plays. On platforms, more of a systems view is needed to balance out subsidies and prices, and determine the traction needed on either side for the business model to work.

Pipe Thinking: We charge consumers for value we create. 

Platform Thinking: We’ve got to figure who creates value and who we charge for that.

But… Platform Thinking applies to all internet businesses

If the internet hadn’t happened, we would still be in a world dominated by pipes. The internet, being a participatory network, is a platform itself and allows any business, building on top of it, to leverage these platform properties.

Every business on the internet has some Platform properties.

I did mention earlier that blogs, ecommerce stores and single-user SAAS work on pipe models. However, by virtue of the fact that they are internet-enabled, even they have elements that make them platform-like.  Blogs allow comments and discussions. The main interaction involves the blogger pushing content to the reader, but secondary interactions (like comments) lend a blog some of the characteristics of platforms. Readers co-create value.

Ecommerce sites have reviews created by users, again an ‘intelligent’ platform model.

The end of pipes

In the future, every company will be a tech company. We already see this change around us as companies move to restructure their business models in a way that uses data to create value.

We are moving from linear to networked business models, from dumb pipes to intelligent platforms. All businesses will need to move to this new model at some point, or risk being disrupted by platforms that do.

 Note: I intend to use some/all of the ideas here as part of an introductory chapter to the book I’m working on and would love to have your feedback and comments.

Nir Eyal and I have collaborated in the past and we got together again to make this post happen. Bill Gurley had written an interesting post on marketplaces a few months back with tons of wisdom packed into a page. Nir and I wanted to make this more digestible for entrepreneurs. Going through a post with ten different points sometimes leaves one overwhelmed. We wanted to distill the essential points into a checklist for makers and builders of marketplaces.

Hope you find this useful, feel free to leave your comments and enrich the discussion around this.

If you’re having problems viewing this slideshow, please visit the original link.

If you’d like to explore this topic further, the following is a list of posts on this topic:

Challenges of starting Platforms and Marketplaces

Seeding Marketplaces with a Demand-first model

Seeding marketplaces with a Supply-first model

The proverbial chicken and egg problem of building a new social product is well understood among tech startups, and it’s been commonplace to follow two contrasting mechanisms for getting traction.

Traditionally, startups have solved this problem by racing to connect users with each other, essentially providing them the pipes to interact with each other. Twitter, Facebook and LinkedIn have grown big with this connection-first model.

However, a new breed of networks is gaining ground with the content-first model. They provide users with tools to create a corpus of content, and then enable conversations around that content. Behance, Pinterest, Instagram, Dribble, Scoop.It have all gained traction by building a corpus of content before building a social network.

The two contrasting approaches are summarized below:

The rules of building a social product are changing. It’s important to understand this shift to build social products that can effectively gain traction on the internet today.The connection-first model is no longer as effective as it used to be. As the social web grows, and a larger number of social products compete for our attention, we are seeing a dramatic shift towards the content-first model. If you’re still getting users to send out Facebook invites, you’re adding to the noise, instead of standing out and getting noticed.

The Connections-first Social Product

Traditionally, the playbook for building network effects has been the following: Get users on board, connect them to each other and have them create content and conversations.

Social networks like Bebo, Facebook and Twitter used this playbook to create their respective networks leveraging address-book integrations and other hacks to rapidly build a large number of network connections.

The importance of building connections, in this model, cannot be emphasized enough. In fact, the growth teams at Facebook, Twitter and LinkedIn specifically aim for ‘X connections for a user within Y days of sign-up’ to activate the user.

Since a critical mass of connections is required before users experience value, the key to building a successful network is minimizing the friction in creating connections. Contact-list integration helped social networks like Facebook and LinkedIn gain initial traction through the removal of sign-up friction.

In spite of growth hacks like contact-list integration, there is always a lead time in getting users on board and reaching critical mass. This is the ‘gap’ where it becomes very difficult to demonstrate value in using the product.

Frictionless sign-up + Virality = Network Effects? Or not!
Startups often believe that removing friction in sign-up and creating some form of viral acquisition are the two key elements to reaching critical mass. In fact, with the rise of Facebook Connect and the social graph, a large number of social products have sprung up on the promise of frictionless sign-up and viral growth. However, users on the internet have limited time and attention. As more startups leverage the social graph and flood users with invitations to join their networks, users have started to develop invite fatigue.

Clearly, frictionless sign-up and virality are not the one-stop solutions we were hoping they would be.

The secret to network value
Startups often fail to appreciate the gap between technology and value proposition. For products like Evernote, technology serves the entire value proposition. However, for social products, the value proposition is a combination of technology and the content that users create on top of it. YouTube’s value lies in its hosting and streaming capability, but more importantly in its vast repository of videos.

The secret to creating a social product that demonstrates immediate value is to enable content before creating the network.

Content created on the network is the new source of competitive advantage. The videos on YouTube, the pictures on Instagram, the answers on Quora are the primary source of value for users and the key driver of competitive advantage for these platforms.

The Content-first Social Product

Today’s social startups don’t start off as networks. They start off as standalone apps. These products enable users to create a corpus of content first. They then connect the users with each other as a consequence of sharing that content.

Instagram started out as a photo-taking tool and built itself out into a social network subsequently. The initial focus was entirely on the creation of content and the connections were formed over time leveraging other social networks. It is unlikely that Facebook would have considered Instagram a direct competitor in its early days, largely owing to its model of deferring network creation.

How to create a network in stealth mode
Instagram started off as a standalone tool. In doing so, the product provides ‘single-user’ utilityto the user even when other users aren’t around on the network. There are two aspects to building single-user utility:

1. The single-user utility should allow creation of content that will ultimately form the core of the network. The core of Instagram is pictures. Discussions are centered around pictures. Hence, the single-user tool needs to allow creation of pictures. This is an extension of the OpenTable model, where a restaurant first manages its real-time seating inventory on a single-user tool, before that very inventory is exposed to consumers on a network, to allow them to reserve tables. Curation-as-creation products like ScoopIt and Storify also use this model to curate content which will serve as the core for network interactions.

2. The product should deliver greater value when users share their content with their friends. The product builds out the network at the backend as more content is shared. Hence, the social network gets created, effectively solving the chicken and egg problem. A new breed of curation-as-creation startups (Scoop.It, Paper.Li etc.) is gaining traction on a similar model.

The new playbook for creating social products is essentially the following:

1. Have a vision for creating the network but do not start executing on network creation
2. Enable a single-user tool that creates content that is core to social interactions
3. Share this content on external networks (social networks, email, blogosphere)
4. Capture interactions around the content to build network linkages at the backend
5. Open out the network once a critical mass of linkages have been built

The rise of the content portfolio
Instagram demonstrates how a network is created around a portfolio of user-generated content. Behance and Dribbble have followed similar strategies by providing a portfolio for hosting designs, before adding value through the creation of a peer-review community. Initially, Pinterest appealed to the designer community as a tool to ‘bookmark’ their favorite designs, before it built out the network. Early adopters found enough value in the ability to store designs and pictures, to use the product before the network became active.

The new success factors
Frictionless sign-up and virality are important but they are no longer the key to building social products. The following are key to building content-first social products:

1. Removal of barriers to the creation of content: Startups like Instagram, which succeeded in simplifying the creation process and in enabling users to spread the word, succeeded in eventually building the connections between users.
2. Growing the creator base, not just the user base: Since value for the overall networks is scaled by scaling content creation, the platform needs to focus on incentivizing and increasing the percentage of users who create content.
3. Strong curation models: Content-first social products scale well only when there is a strong curation model in place to separate the signal from the noise. Without strong curation, greater content can actually lead to a poorer user experience leading to reverse network effects.
4. Incentives: The platform needs to encourage users to build out the connections. This works best when the platform encourages an innate motivation (self-expression or self-promotion) in the user to spread the word about her content. In doing so, the users build the necessary connections that set up the network.

The new growth hacks
In the connections-first model, the one hack that minimized friction in building connections was the contact list integration. In the content-first model, the hack that minimizes friction in creating content is the creation widget. Creation widgets have grown in popularity in recent times, spreading across the internet in the form of browser add-ons and one-click buttons. Several curation-as-creation startups like Pinterest and Scoop.it have used widgets to enable users to create content easily.

The future
This new model of building networks allows a social product to gain traction while value is being created by users. Once enough content is created, the users are connected and the network builds out. Social products that win will focus on enabling users to create content first and generate conversations around it. The creation of the actual social network will be a final step, as a consequence.