Sometimes a marketplace is flawed and headed for a tough time before it even begins. But it’s not unlikely that this does not become evident until £20m has been invested. So, it begs the question: how can you know if that is the case and what can you do about it?
Network effects, liquidity, TAM, are some of the many things that a marketplace needs to get right. All very aptly described by Bill Gurley here. The list in the post is informative, concise and certainly correct. But if we were to put these in a timeline, gap related to the execution in the middle emerges. For instance, you can know if you have a big market from the get-go and by the time you experience network effects it all gets easier however, everything in the middle is murky, complicated and multivariate.
In a 2018 post, Eli Chait published a very insightful piece where he correlates the fragmentation of buyers to marketplace success.
Effectively, his research reduces the complexity of the first list to one metric that’s a bit meta; he’s positing that for a marketplace to be successful there is an inherent characteristic the market needs to possess and that is a very large amount of buyers (1 million buyers for one business) and for those buyers to also be fragmented.
This is a useful point because it identifies the principal component of success amongst many other variables and thus simplifies the problem. Can you get a million buyers? If not, then the cards are stacked against you.
Once more, if you have 400,000 buyers already this is a meaningful insight. You can approximate the value per added buyer in the network and roughly calculate if you can escape velocity through network effects.
But what if you’re just starting? What if you have 100, 1000 or even 10,000 buyers? Are the above enough to ensure that a marketplace is the right model for a given industry? How can you tell if your unit economics can mature to reflect a £1bn marketplace?
Perhaps there is a way to know what will NOT work. And there if there’s one thing to steer clear from is services with inherent repeatability of transactions between the same supplier and buyer. If that is the case, then scaling a marketplace to the 1 million buyers, 1 billion GMV will be tough.
And there is both an intuitive and analytical approach to explain why. But first, why is the lack of repeatability a benefit? Uber is a good example.
From the perspective of the supplier (driver), Ubers works like this. A driver can reach clients previously unreachable and get access to a set of value-adding services to make the job easier. In exchange Uber takes a fee per ride. Every time a new rider connects with a driver, Uber has taken care of: finding the client, navigation, safety measures and, seamless payment in the end. But since the whole CLV is (most likely) equal to the value of the ride, the next time the driver picks up a new rider, (s)he will reap the same exact benefits from Uber and Uber will receive the same fee.
In other words, supply and demand see each other as a commodity. Therefore a platform facilitates the transaction. Uber is there to ensure that a code of conduct is enforced (safety, trust, politeness etc) and enables transactions that would not be possible before (eBay, AirBnB are also good examples). This is an example of Bill Gurley’s point on “technology expanding the addressable market”.

However, there are industries where the above hold true and still have fundamental issues in their economics, because of the loyalty repeat transactions create. Take therapy for example. The more therapists, the better the matching. A marketplace can expand the market via remote therapy, matching and also by creating the necessary privacy and trust for clients to make the first step. It’d be closer to how eBay grows the market (remove friction) than how AirBnB, Fiver or Uber do it (without them it’d be impossible).
But still, in the UK alone there are at least 2,500,000 people that will receive privately funded therapy per year. Trust is necessary initially. Structural and attitudinal barriers can both be addressed by marketplaces and therapists have a constant need for new clients as some come and some go. Yet, a therapy marketplace won’t work. Why? Because of the repeatability of transactions. A therapist is not able to see more than 25 clients (max) per week (50-75 uniques per year) and a client will only see one therapist.
That would not be a problem if the marketplace could capture a chunk of the value across the lifetime of therapy. However, the value-add of a marketplace declines after the first session because the client forges a trust relationship with their therapist. By definition, therapy is about the trusted relationship.

In fact, from the perspective of the therapist, the marketplace doesn’t only stop adding value but can detract value. After the first session, a therapist will start adding notes for a client, have constant communication with them via their preferred medium (e.g. WhatsApp), receive the payment in a centralized way (e.g. PayPal) and agree on a fixed schedule which on a per-client basis at least, is simple.
Consequently, after the referral is done, the marketplace introduces a cognitive cost to use its add-on services (e.g. automated payment collection). If the therapist wants to use the marketplace they have to do extra admin on another space to keep their operations centralized.
Therefore, taking the client away from the platform is natural. Disintermediation is inevitable and thus, CLV real < CLV expected, which leads to unsustainable economics and does not allow the marketplace to scale.

Enter SaaS enabled marketplaces, or SEM
So, repeat transactions present a structural barrier for the marketplace to achieve strong unit economics and scale. Still, suppliers do need services to grow and manage a practice.
This is where a SaaS-enabled marketplace can provide a solution for a few reasons.
- The positioning of the product is not necessarily around lead generation
- Consequently, pricing is not pegged on “getting more clients”
- Finally, the supplier might bring the clients onto the platform voluntarily which alleviates the platform from the burden of CAC but also positions it to capture value across the lifetime of the client.
From a cash flow perspective, this allows for a direct reinvestment of revenue per supplier to acquire new suppliers. Eventually, when there is a critical mass, then the platform can aggregate them and introduce a new service on lead generation but without the pressure of that being a promise. Shopify’s Shop app is a good example of that.
So, are repeat transactions intrinsic between supply and demand in a market? If so, it will erode the marketplace unit economics and pose challenges in scaling to network effects. Looking at the “come for the tool, stay for the network” approach is the more appropriate strategy for these kinds of markets and can still take to the same end point but in a more sustainable way.