THE NEW GROWTH LANDSCAPE #4 — READ 1,2,3,5,6

Growth Engines in Marketplaces & Platforms

A Primer exploring ways to drive Growth in Network-Ecosystems based value propositions by Manfredi Sassoli de Bianchi and Simone Cicero

This fourth research update on the emerging landscape of growth in platforms and marketplaces is brought to you by the team at platformdesigntoolkit.com and is dispatched in our fortnightly newsletter.

This essay presents a compendium of the most important growth engines in platforms and marketplaces and provides the reader with a way to navigate an otherwise highly complex landscape of possibilities and choices. We have to thank all the great professionals that have been putting out so much great content on this topic during the years, especially Casey Winters, Kevin Kwok, Lenny Rachitsky, James Currier, Andy Johns and many more.

Stay tuned for the release of our full growth guide and course by subscribing here!

Catch up with the whole series here.

On March 30th attend our second New Landscape of Growth Webinar.

Generating growth through compounding effects

The story goes that an ancient prime minister by the name of Sissa ibn Dahir invented the game of chess. His king liked the game so much and that he was propelled to ask Sissa what he’d like as a reward. Sissa simply asked for some rice: one grain of rice on the first square of the chessboard, two on the second, four on the third, eight on the fourth, and doubling each square for all the 56 squares of the chessboard.

The king agreed, amused by the compensation scheme the minister had come up with. When he later found out that it would equate to 18,446,744,073,709,551,615 grains of rice, or 2,000 times the annual global production, he was somewhat dismayed. It is unclear what happened after, if the minister negotiated a partial compensation and became extremely wealthy, or if he was immediately sentenced to death.

While the story may never have happened, it does a good job of showcasing the concept of compounding interest.

Strategy for an established business may have similarities to the game of chess, platform strategy has in fact been described as three-dimensional chess. For a new venture, on the other hand, efforts should focus less on competitive strategy and more on creating a growth engine: a strategy that can leverage compound interest and create a virtuous cycle that reinforces itself.

In our previous post, we wrote about a series of tactics that can help a nascent marketplace get off the ground and deliver values to all parties involved with the aim of solving the initial chicken and egg problem. Once a marketplace reaches liquidity it will naturally aim to increase scale. There are 1,000 ways to grow for a business, but there are only a few ways a business can create a real growth engine that can deliver consistent sustainable results.

These engines of growth come in different shapes and sizes. There is some confusion over the naming convention used for these: growth loops, flywheels are also used. We will try and make some distinctions and share a general framework to help our practitioners to address those opportunities, by covering the following types of loops:

• Strategic Flywheels;
• Growth Loops;
• Spillover Loops;

Strategic Flywheels for Network Effects

A strategic flywheel is a growth generating loop that is part of the business model and integral to the overall business strategy, normally through the form of a so-called network effect or defensibility reinforcing loops. They increase defensibility by creating an advantage moat or, at least, a transient but substantial competitive advantage. For the framing of the strategic flywheels, we rely a lot on Max Olson’s “Advantage Flywheels” (see: Advantage Flywheels — FutureBlind). Max is a great writer so it will also be a great opportunity for you to catch up with his work.

Network effects are often considered the strongest source of competitive advantage a firm can have. In the case of marketplaces, network effects are of course always present, although vary in strength and nature. Broadly speaking network effects are connected to one basic idea: the value perceived by the participants to a network grows with the growth of the number of users. We quickly introduced this idea and the usual value perception growth curve shape in our recent “Understand the Network to Design for Growth and Defensibility”

Network Effects have an important role in ensuring Value perception grows in Markeplaces — check our insights here

Basic Strategic Flywheels (BSF)

There are essentially two types of essential/basic strategic flywheels related to the nature of networks: the Direct and the 2-sided Network effect flywheels. The type of flywheel that operates in your context varies through the fact that you’ve one or two (eg: buyers and sellers) different roles in your network, but they essentially express the same mechanism, the emergence of so-called “economies of scope”: the fact that depth of inventory makes the possibility of finding a perfect match for what you’re looking for, just more likely.

The BSF are taken from Max Olson’s original post on FutureBlind https://futureblind.com/2019/08/03/advantage-flywheels/

On top of the basic examples above, we can list five essential reinforcing flywheels that create additional defensibility we explain in more details below:

• Economies of scale;
• Brand/Bandwagon effect;
• Embedding or Lock-in;
• Proprietary Tech;
• Data capture and optimisation;

Self-Perpetuating Reinforcing Flywheels (SPRF)

The first and most common SPRF is Economies of Scale. Economies of scale have been the key driver of success for firms in the 20th century. It’s a natural consequence of the size of a firm increasing, and it’s what effectively gave birth to mega-corporations: scale essentially helps organizations to spread fixed costs across the user base making the cost-per-user lower over time/size. Note that this can be leveraged and is fed by any other flywheel as the scale goes up.

Another common SPRF is the Brand reinforcing flywheel: a strong brand can increase trust, desirability and recall. A brand is not just a logo but the ensemble of tangible and abstract characteristics that consumers associate with a product and to the experience of it. A brand can be shaped to serve the needs of the firm. In the case of Uber, it can create the trust people need to jump into a stranger’s car. In the case of Nike, it can be inspirational, in the case of Dove, (or any consumer packaged goods that compete on the shelves of supermarkets), it can create recall. While in some markets a strong brand is a key success factor, in others it’s secondary: for marketplaces, network effects are always the biggest value add and the brand reinforcement flywheels is often a result of wisely mastered growth. As the (product, service) inventory grows with more producers on the network, and the rate of conversion increases (I find, as a consumer the right option more often and more easily) the association of quality, and depth of choice, with the marketplace brand, grows and the searching cost decreases (there’s less need to search for opportunities).

The third recurring SRPF, the Lock-in flywheel (also called embedding) lends itself well to software products and it’s actioned when a product becomes critical for the execution of tasks within a third-party enterprise that has purchased the product. The more the software becomes indispensable, the less likely a company is to get rid of it. This flywheel is particularly essential in the business context where — if a product gets embedded in the workflow — changing it will require substantial investments and loss of productivity. This pattern works very well for SAAS first product that later transition to marketplaces.

A company leveraging such a lock-in flywheel not only can be confident about retaining its customers but also about gradually increasing fees.

A particular nuance of the lock-in flywheel is a variation on the above: we could call it Data Lock-in SPRF. This occurs when the data produced by users, (not just their presence), enhances the value of the product to other users by enhancing the underlying technology or the experience. This is particularly strong in Waze, where traffic data informs users on the best routes to take (enhancing the tech) or in Amazon or Uber where user reviews add value to customers and users in the form of better information to generate better experiences: in turn, the technological improvement on the product performance contributes to encouraging adoption and lock-in in a self-perpetuating improvement process

Capabilities Building Based Reinforcing Flywheels (CBRF)

This set of flywheels differs from the one above in the sense that to leverage on them the organization needs to build organizational capabilities and nurture them over time. Therefore these flywheels are not “self-perpetuating”: they need organizational effectiveness to really work.

The Proprietary Tech CBRF is effectively consisting of the development of a rare to acquire core competence on a specific technology that the organization masters. While mastering a capability will always be a benefit to any firm, being able to excel in high-value skills in technological differentiation, that is hard to acquire, will lead to a competitive advantage. A good example could be what Google is doing today with machine learning. The better they get in the field, the more people they can hire, the better the technology, the more talent they attract, the better they get. They are constantly building on an increasingly high knowledge base.

Similarly, Data capture and optimisation CBRF effect is a mixture of a scarce asset, (high volume of data), and scarce skillset (high tempo optimisation: operations, design, analytics and user psychology). Today companies like Amazon and Booking run hundreds of simultaneous experiments at any given time in the form of A/B tests. They can do this by leveraging the high traffic volume on their site, in-house built technology and a mixture of quantitative and qualitative skills. As this enables them to improve the product, even more users start using it, increasing the traffic volume further and allowing them to optimise faster. For more insight on testing and optimisation here.

The flywheels mentioned above are the most popular ones and can be applied in almost any scenarios. However, there are other combinations that can be equally powerful, company-specific ones and complex combinations of the above. In his great book Turning the flywheel, Jim Collins shares many great examples that he found analysing various companies. The one below — for example — applies to Giro, a sport manufacturing company.

Growth Loops (GL)

Differently from Flywheels, Growth loops can be defined as a set of marketing tactics that leverage positive feedback loops to deliver — over time — sustainable growth at scale. Generally, four key types of growth loops are recognized: Virality, Paid Marketing, Content and Sales. The beauty of these tactics is that the loops are closed — meaning they are measurable at each step with a high degree of accuracy and this is what ultimately facilitates optimisation and compounding. A clear example of a non-closed loop — on the contrary — is TV or Radio advertising, just to offer a counterpart.

We can’t stress enough that these are not just marketing tactics that will add 10% growth to the company. These need to be ongoing efforts that, if successful, can really project a company to high growth regimes.

Viral growth loops

Virality occurs when customers share your product with other customers: it’s the best type of marketing as it’s effective and free. Of course, it’s not easy. How do you get people to share your product?

There are viral tactics and viral loops. A viral tactic is a great piece of content that users will share. This is a high-risk high reward marketing strategy as rarely content becomes extremely viral and no one knows exactly why it happens. When it does happen however it’s unlikely to last forever. A viral tactic is a one-off trick. Even when it works it’s hard to replicate.

A viral loop on the other hand is intrinsic within the product and creates predictable and scalable growth. Linkedin historically has had strong growth loops based on virality.

This type of product dynamic can generally be baked into only a few categories of products:

1. Gaming: all multiplayer games have this feature;
2. Communication: including all types of communication networks, (Hotmail and zoom), and social network (e.g. Linkedin, as per the above example). Worth noting that only in these cases direct network effects are equal to virality;
3. Collaboration: for tools that facilitate work through collaboration (e.g. Figma);
4. Payments: sharing is a prerequisite of payments as money exchanges hands;

Outside these product categories it’s extremely difficult to build a full viral loop: your product will need to find other growth avenues — but it doesn’t mean that a certain level of virality/shareability can’t be achieved. This is the so-called K factor: which is the metric that quantifies how viral a product is. It is calculated with the following formula:

K = I x R

where:

• I = invites or the average number of shares your customers deliver
• R = conversion rate, or the % of invites that turn into new users

So if your customers share your product with 3 users and on average only 1 of these will start using the product, so conversion would be 0.33%) your K factor would be 0.33 (or 1 x 0.33). If customers shared with 5 other users and out of those 2 converted, your K factor would be 0.4. While this would not be sufficient to allow your product to grow your product organically, it would deliver a 40% boost, which is substantial.

For a product to be truly viral, the K factor needs to be greater than 1.

So how does one increase virality? How are users encouraged to share?

In some cases, (the ones listed above), it’s about a concrete user case. Outside of that it’s about the art of marketing and influencing consumer behaviour: making them share what they would otherwise not share. There is endless literature on the psychology of why people share: from the book “The tipping point” by Gladwell to this recent blogpost by NFX.

What everyone agrees on is that it has a lot to do with status, or how people want others to perceive them. People want to appear:

• in the know;
• part of an exclusive group;
• helpful;
• right (hold the right point of view).

Another proven strategy that is proven to deliver high virality is giving users tools to create great content. As every creator needs an audience, (and as human we all crave to unleash our creativity), then virality is almost guaranteed.

The key to achieving a high degree of virality for products that aren’t naturally viral, (e.g. a K factor of 0.3 for certain products is a great result), is understanding that achieving this isn’t about adding a share button to the page. Triggering and improving shareability will require significant investments in resources and testing to create a great value proposition, the right emotional (or financial), incentive and a clear and easy way of sharing.

Paid Marketing loop

On the surface a paid acquisition loop is straight forward:

There are three caveats to this working:

1. It must work on a major platform like Google, Facebook, Amazon, Youtube or the app-stores in order to scale (affiliates and display advertising are rare candidates);
2. Execution must be flawless;
3. A high LTV (Customer Lifetime Value) must characterize the product;

Performance marketing — particularly on Google and Facebook — is extremely competitive: as clicks become more expensive CAC (customer acquisition cost) goes up. In order for these channels to be viable then LTV needs to be high enough.

On platforms like Google and Facebook advertising space is bought through an auction-based system. This implies that one needs to be able to execute better than the competition: particularly on Google where competitors bid on the same keywords. A great example of this is the competition between two companies with an identical business model: Expedia and Booking.com. The chart below shows global search volume data on Google

A large portion of Booking’s success can be attributed to their better execution on paid search ads — search engines being the primary distribution channel for most travel products. As the chart shows the winner can reap huge benefits. Booking became Google’s biggest client, but their success was not just about having deep pockets; they had to create a powerful optimisation engine.

On a recent poll based on a group of 21 highly experienced digital marketing experts, all with above 10 years of experience in digital marketing, results show us how great execution is likely to deliver returns that are above 40% high vs average execution.

How does one create an optimisation engine?

This doesn’t happen overnight, but broadly following the steps below will help:

1. Find out if this is the right distribution channel: this can be done via a series of small tests without caring too much about margins. Find out if people are searching or clicking on your ads. As long as CAC is within 3X of your target profitability, it means there is potential. (We will not go into specific channel optimization tactics here). Looking at competitors can often give strong indications here.
2. Put in place good quality analytics: if you can’t measure accurately you won’t be able to evaluate performance, and ultimately you can’t improve what you can’t measure.
3. Invest in resources: find someone with deep channel expertise, a proven track record and enough time to manage your campaigns.
4. Invest in the experience: create high-quality ads and landing pages.
5. As the campaigns scales, hire more resources.
6. Invest in technology: bid automation, A/B testing, reporting and overall campaign automation.
7. Invest in expertise for conversion rate optimisation.
8. Invest further into analytics: understand multi-touch attribution and LTV by customer segment.
9. Design custom-built automation solutions to better integrate with company-specific processes and react in real-time to market conditions.

As the reader will note, the process above requires increasing levels of sophistication, which in turn require skills in development, data science and user psychology. Reaching step 7 will already deliver high value and volume — as long as the right resources are hired, and this is never easy. Reaching level 9 means becoming a world-beater, but very few companies can sustain that level of investment. Booking.com famously invested heavily in building in-house technology to deliver automation at scale. The chart below, courtesy of Lenny Rachitsky shows how for Booking the performance marketing growth loop and network effects were intertwined:

From https://www.lennysnewsletter.com/

Content loops

There are two major key types of content loops:

• Editorial: where content is built in-house
• UGC (User Generated Content): when content is built by third parties

In both cases the content loops sit on top of powerful distribution engines: these may be the Google search result pages, but could also be social media platforms, (via Youtube videos, Instagram posts, or Tweets).

Editorial content works in a similar dynamic to performance marketing, with the crucial exception that investment goes into the production of content rather than ad-spend.

Producing content that ranks well on search engines, is often harder and more expensive than expected, but a content loop of this sort is preferable to a performance marketing loop because it’s more sustainable. Money invested in Facebook ads one month will disappear the following month, while high ranking content is likely to continue delivering traffic for years ahead. Furthermore, a site that has produced many valuable pieces of content will gain a high authority making all pages of such site rank higher.

Performance marketing loops are fueled by data that powers efficiency; the efficiency uplift must offset the diminishing returns of the media channel. A content loop is simply fueled by volume, an uplift in efficiency is not required, (although of course, it can be by implementing website optimisation and increasing conversion rate).

How does one start an editorial content loop? Here is a summary of key steps:

1. Evaluate the volume of the channel: this is a long term investment, only worth it if it can bring substantial returns (Paid Google ads can give a good insight into this: how much volume is there for your business relevant keywords?).
2. Ensure website javascript is well optimised to facilitate search engine’s crawlers.
3. Define a content strategy: find out what are the relevant keywords, which match best with your core value proposition and where there is less competition.
4. Start small: start with a few pieces of content on a focused theme.
5. Evaluate results and if positive invest in full-time resources: these should be ideally inside the company and have deep SEO expertise and content production skills.
6. Optimise site architecture (for example by using URL structures that resonate and maximise speed.
7. Expand content strategy to social media to increase links and authority;
8. Explore opportunities for automated production of content (for example Thumbtack created pages through an algorithm — listen to the podcast linked below);
9. Increase investments in resources: if it includes video content this can easily become a team of 7+ people.

Creating an editorial content loop is a strategy that serves well only certain businesses. Media outlets of course have a great opportunity, as they naturally create content. English language publications that started to optimise for SEO and adapt to an online subscription model, have been extremely successful ten years ago. It is easy to see how a health-related brand can publish a large amount of content, but this would be much harder for a shoe manufacturer.

While ranking well on Google is a benefit to every business, the size of that opportunity and how reachable it is will vary significantly. When launching a new product, like Airbnb, search engines are not a strong channel, because people rarely search for a novel concept. On the other hand Thumbtack, a marketplace that connects homeowners with local plumbers, electricians and other home-related tradesmen, relied heavily on SEO. They created thousands of pages for location + profession e.g. “electrician in Brooklyn”. Serving well for these granular search enquiries at scale gave them an edge over many competitors ranking for similar terms.

The UGC (User Generated Content) loop

This is probably the most powerful growth loop, but also the hardest to achieve. The beauty of it is that it relies on content produced by third parties and distributed by third parties. Precisely because of this, a UGC content loop is also one of the hardest to create, but once in motion, it can perpetuate itself for years and continue to deliver growth with minimum investments. Driving cost-efficient growth at scale enables new business models, where revenue per user can be extremely low e.g. ad-funded, or freemium.

It’s important to point out that in order for content production to happen at such a scale, the act of content production must be central to the value proposition, and rarely that overlaps with marketplaces. This growth strategy requires the marketplace business model to be added at a later stage: Pinterest launched a marketplace only in 2019, 9 years after its inception.

UGC content loops can also differ slightly in shape, here are two examples (the ones re Pinterest is from Reforge):

Pinterest is a social and image sharing platform while Faceit is a gaming/e-sports platform. The two of course follow different dynamics and this would differ still for a pure social network where content is shared directly from user to non-user: this is virality, as covered in the above section.

Based on the two examples above, at the most basic level we can observe the same pattern:

1. New users are acquired
2. Users create new content
3. Content is curated (this step is not always necessary)
4. Content is distributed

Each step poses its challenges.

Content distribution and discovery: this requires understanding who your audience is, where do they hang out and what content do they look for. If it is about the long tail for an audience searching on google, then distribution the whole content, in a fashion that is SEO optimised, is probably the best option. If users will only be interested in “blockbuster-sensational” content, then curation and distribution through influencers is a better strategy: this will require creating strong ties with the right influencers, (that resonate with your audience). Curation itself can be challenging, in terms of scale and selection: investments in machine learning will facilitate this area at scale.

Acquiring and activating new users: following the content, users will come to discover the product. At this point there is a hierarchy of goals that should be pursued by the product owner:

1. Delivering the value proposition in terms of content value, so the user knows why it should come back.
2. Capturing users contact details, to remind users of the value (and lure them back).
3. Delivering the value proposition in terms of content production.

The three steps may not be in that order.

As a rule of thumb in online communities, 1% of users will add new content, 9% will contribute/comment and 90% will lurk. These numbers may vary significantly: potentially 5% of users could become creators, but only a portion of the people who discover a product will become users, and not all content will drive a high volume of traffic.

For a UGC growth loop to work, a significant volume of traffic is required, joint with a strong growth approach, that can unlock incremental gains at each step through ongoing experimentation, joining a rigorous data-driven approach with user insight. The speed at which the cycle perpetuates itself will also be critical. For more in-depth advice on the implementation of a UGC loop, we recommend this great post by Andy Johns.

Sales

Sales are definitely the most traditional of growth loops: creating high performing sales teams that will deliver growth with the profit later reinvested into growing the team itself can be a powerful growth loop especially if:

• LTV is high (justifying the investment needed in the first place) such as typically that of B2B marketplaces;
• the sales process is subject to optimization and refinement (some parts of the process are replicable, can be automated…);

Some interesting experiences such as that of Figma, described in depth by Kwok in this post, feature sales teams follow-ups following an organic customer acquisition: designers use the product and drive adoption across their teams, a sales team follow-up nurtures the corporate adoption opportunity.

Spillover Loops (SL)

With this newly coined definition of Spillover loops, we characterize the growth loops that can exist in a complex portfolio of platform strategies, or between platform experiences that a single organization — or an ecosystem of organizations like in the EEEO case — brings to the market.

Spillover loops are crucial to be understood especially if your organization is running multiple platform strategies simultaneously: this could for example be the case of large organizations managing a portfolio of initiatives or the case of a single organization launching additional platform experiences on top of existing ones.

As we’ve introduced in a previous essay, it’s a good idea to look at a platform strategy from a dual perspective of network AND product. Platforms-marketplaces are normally able to provide a dual value proposition:

• on one hand, they connect producers and consumers in a marketplace;
• on the other hand, they provide — normally to the producers — a product, usually in the form of a SaaS offering that can be extended through plug-ins, apps, templates, extensions etc…

Of course, not all platforms-marketplaces provide both, sometimes you only have one side of the strategy, but many times organizations provide both VPs and one VP is used to generate attraction on the other side. We covered already the paths of evolution from one side to another (product to network vs network to product) in our inaugural post: often when the evolution goes from the product (initial) to integrating the network value proposition is because generating demand is key. The latter instead, the network to product pattern, maybe a common way to differentiate, and — for example — to achieve an embedding flywheel. In any case, the product side of the strategy needs still to be seen as a “network”: the more third party developers (of “extenders” more generally) join the ecosystem, the more the product value proposition will be perceived so (check out this essay where we explained the idea thoroughly) by extending the number of jobs to be done that the suppliers in your network will be able to achieve with that.

If now we look at both sides as two networks, we should be able to understand how growth can be made to spill from one network to another (the red dot is used to characterize the “marketplace” side, while the cyan one is to indicate the “extension platform” side) :

It’s of course entirely possible to drive spillover growth from one experience to another in the same marketplace-platform strategy or even between two marketplace-platform strategies that are run by the same organization. A good example may be retrospectively analyzed how Airbnb introduced experiences on top of the liquidity generated around short term room rentals that are explained in this animated pic that we introduced in Jul y2019 in our “Demystfying Network Effects”

As the reader can see, Airbnb positively managed to piggyback on the liquidity generated on the room rental marketplace into the experience marketplace because the demand side of the network was actually — at least partially — shared across the two: the same traveller that rents the house is often the same that books experiences. Of course, such a dynamic can also play out across marketplace strategies that do not necessarily belong to the same brand, and if we generalize the idea to the context of a typical large scale organization that running a complex portfolio of multiple strategies we could end up with a picture that looks pretty much like the following, where we assume that the company first launches a certain marketplace strategy and reaches liquidity (first flywheel on the left), then complements with another strategy where the same suppliers are consumers of another marketplace strategy and subsequently creates an extension platform to extend the functionality that such professionals get from the SaaS (product) offering of the second marketplace.

Conclusions

The power of compounding interest is mighty. As one starts to realise its potential it’s easy to fall in love with the concept and use such virtuous cycles as a lens through which to see the world. These self-perpetuating dynamics are so powerful that implementing a single one will lead to massive gains, to the point that planning for it can easily replace the whole strategy process. We partly advocate for this, after all the Platform Design Toolkit is a tool developed to architect and nurture network effects. We need to highlight however two key points:

1. The design stage, particularly when it comes to “out-of-the-box” growth loops that have proven successful by many, is the easy part. The challenge comes in the execution. Building a single one of the flywheels and loops we have talked about can take years if done at scale and it requires multiple capabilities, some hard to acquire.
2. Not all loops are born equal. Some asymptotes quite early and lose power relatively quickly, others are just weak, (value created in one step only converts partially to the next step), or slow (the time a customer takes to deliver another customer might be over a year). When designing a loop, before investing significant resources, we must have a good understanding of its potential.

Finally, the loops and flywheels explained here are just archetypes and templates: understanding how growth unfolds in your business as a combination, evolution and integration of those is essential in achieving growth after the validation stage: don’t feel constrained by the examples given above; look at your business as a loop in itself and ensure that the wheel is spinning and is self-sustaining.

A new course

As said above, this new framework — that we are already partially teaching at our public bootcamps (next coming up in February) — will seamlessly integrate with our widespreadly adopted Platform Design Toolkit methodology and nicely fit into our existing toolset for the age of networks.

A new intensive course will be released before the summer: the course will be offered at premium discounted price for early registrants to this list of super-early-bird subscribers, provide your expression of interest here at this link: https://platformdesigntoolkit.com/growth-subscribe

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