Knowledge for Founders

Marketplaces: Comparing macro metrics across investment rounds

After the success of our publication “7 Lessons on Marketplaces”, here we begin the series of posts in which we will go into more detail on some of the concepts, and insights in each ‘lesson’.Since our life is not linear ... we have decided to start with Lesson 5:How can we compare the macro metrics (investment, traction, pre-money valuation) with the investment rounds of marketplaces?
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Marketplaces: Comparing macro metrics across investment rounds
Marketplaces: Comparing macro metrics across investment rounds

Photo by Caleb Stokes on Unsplash

 “Great marketplace execution is more nuanced and less systematic than other venture backed categories, and for every successful marketplace, you will find an amazing entrepreneur that out-executed the many others that had chosen to attack the same market. In addition to great marketplace characteristics, you also need a world-class entrepreneur to make the dream come true.” 

 All Markets Are Not Created Equal: 10 Factors To Consider When Evaluating Digital Marketplaces.  – Above the Crowd, by Bill Gurley.

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After the success of our publication “7 Lessons on Marketplaces”, here we begin the series of posts in which we will go into more detail on some of the concepts, and insights in each ‘lesson’.

Since our life is not linear ... we have decided to start with Lesson 5:

How can we compare the macro metrics (investment, traction, pre-money valuation) with the investment rounds of marketplaces?

Investments, by round:

Comments / insights:

  • Our database does not show substantial differences in the need for investments in the first rounds, during the early stage.
  • However, in the interviews we held, it caught our attention that the ‘job to be done’ – the objective of early-stage rounds – is different for marketplaces than for SaaS enterprises. For marketplaces, PMF – traditionally the objective for the Seed round – is reached in Series A rounds. Hence, we believe we can consider that marketplaces need more investments, and more time, to reach PMF, and thus represent a higher risk during the early stage. We go into this more deeply in Lesson 2. 
  • Thus at the same time it seems to us that the size difference between rounds in the late stage derives from a lower perception of risk and/or a higher potential for premium or gain. When we talk about this premium, we are going further than the cases that we are currently familiar with – such as, for example, Amazon and Mercado Livre.
  • We will be going into detail on this point more deeply, but we can say now that network effect and economy of scale are very important for the success of marketplaces, and it takes time to build NfX. It takes time for the volume of alternatives that enables aggregation of supply and demand on the same platform – and the new experience that is proposed – to become important for a group of people. This is why Andrew Chen, when describing his concept of the ‘Atomic Network’, suggests that entrepreneurs need to understand what would be the smallest possible network of people that is able to survive and maintain itself as a working unit. Reaching this Atomic Network is an extremely important objective, because it provides the team with (a) confidence of the possibility of scale; and (b) predictability.

Traction, by round:

Maturity of GMV (Gross Merchandise Volume) -– Monthly

Comments / insights:

  • We use our database, with addition of Point Nine’s B2B Marketplace Napkin  for comparison.
  • Note on the limitations of the Napkin: survivorship bias, data limited to 51 rounds, focus only on B2B, base: Europe.  But we include it due to the wide usage of its figures as a reference.
  • The chart above is basically a snapshot of the market in 2022 – we have used the monthly basis to accompany the evolution of the metrics.
  • As a measure of traction, GMV is worth more than revenue, because it is the key practical orientation metric of almost all marketplaces (Lesson 3). In looking at revenue, there are various different strategies for monetizing the aggregated value of the platform, hence the great variety of strategies that are used for pricing and charging through take rates – which in our view makes the debate too complex (Lesson 4).

Speed of growth

  • Here, it is more difficult to get an overall view of the differences in growth rates between marketplaces in the initial phases. But theory indicates that the few enterprises that succeed in evolving in these rounds succeed in speeding up their growth rate afterwards, and overcoming the natural limitation of the Mendoza line, due to network effects. And would this be why there is a premium for marketplaces of the elite quartile? We believe the answer is yes, and we will be going into this subject more deeply in our next posts.

Pre-money valuation, by round:

Comments / insights:

  • Here we can see that when a marketplace has established itself as elite (– in the top quartile), it has a strong chance of  taking off from the market in terms of pricing by each of the rounds. As we have said before, premium is probably derived from the network effect, when it establishes a valuable competitive advantage. 
  • Note that, even with the need for more time and investment to reach PMF, investors pay a premium for marketplaces, from as early as Series B! 
  • This underlines the importance of the treasure-hunt for marketplaces as a source of Alpha for the portfolios of VC funds. 
  • Our hypothesis is that when they achieve network effect, marketplace platform begin to improve their unit economics – in the form of: 

(i) reduction of client acquisition cost (efficiency, over the long term); 

(ii) acceleration of growth; 

(iii) multiple adjacency possibilities for monetization of a single base in the platform; and

(iv) entry barriers to keep out competitors. Thus, once established and proven, improvement in unit economics can command a premium.

Trying to look at all marketplaces in aggregate, or as all in the same category, is a challenge. In spite of the limitations of all the models, we believe we succeed in providing data that help in better understanding contexts and making better decisions – working with the others out there who are crazy enough to be entrepreneurs!

If you would like to go into this subject more deeply, here are some reading suggestions: 

Cassio Azevedo (EN)

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