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Matchmakers: The New Economics of Multisided Platforms by David S Evans, Richard Schmalensee
MULTISIDED platforms which the authors aptly refer to as ‘matchmakers' have created huge value for society, and enormous fortunes for their entrepreneurs and shareholders.
Of the five most valuable companies in the world last year, three are using the matchmaker business model: Apple, Google and Microsoft. Of the ten start-ups with the highest market values, seven are matchmaker platforms. These include Airbnb and Uber. Many more successful companies lower down the market capitalisation charts are using this model, too.
The matchmaker business model is hardly a new development. A mall is an example, attracting and enabling various buyers and sellers to interact. A magazine or newspaper attracts readers through its journalism, which attracts advertisers.
However, matchmaker business models are much more complicated than they appear, and have been misunderstood by business people and economists.
Conventional businesses buy inputs from suppliers, and transform them in some way into either goods or services that can be sold to customers. Here the key is to attract customers, and sell to them profitably. The tasks of matchmaker platforms are to attract two or more types of participants by enabling them to trade with each other on attractive terms. The inputs of matchmakers are primarily their participants.
Until recently, economists didn’t have models to show how these businesses worked. Most investors during the dotcom bubble, for example, lost astronomical amounts of money through the application of criteria that simply didn’t fit this category.
Traditional economics holds, for example, that it’s never profitable to sell products at less than cost; there is a first-user advantage; and critical mass is essential – ‘just find the eyeballs and we will find a way to monetize it’.
In 2014, Jean Tirole received the Nobel Memorial Prize in Economic Sciences for important contributions to economic understanding, including his insights into the new economics of multisided platforms. Understanding multisided platforms allows businesses to assess their viability, and then to structure the business model appropriately.
‘OpenTable’, a free mobile app, enables you to find and make restaurant bookings anytime, anywhere. You do not have to worry about opening hours, or phoning numerous restaurants to enquire about availability, or to view the menu. ‘Free’ wasn’t OpenTable’s temporary, opening promotion; it hasn’t ever charged. Diners are so valuable to the model that OpenTable finds and actually ‘pays’ them through rewards for using the service.
Chicken-and-egg problem
The matchmakers suffer from the chicken-and-egg problem. You can’t have chickens without eggs, but you need chickens to get eggs. A matchmaking platform can’t attract diners without restaurants, but no hungry consumer would use a reservation system that had no restaurants available.
As recent history has shown, most matchmaker start-ups don’t survive. “Now economists know why multisided platforms can create immense value, and how they do it, and also why most matchmaker start-ups sputter and die,” explain the authors, David Evans and Richard Schmalensee, both highly respected economists.
Once the complex network effects of these businesses are understood, economists started investigating the pricing models these firms should use to maximise their profits. In conventional businesses price is usually achieved through balancing volume and margin. The higher the price the lower the volume, and vice versa. Selling more, but earning ever less, would not make sense: but this doesn’t always apply to matchmakers.
Matchmakers sell connections, and they must balance their treatment of all the customer groups to ensure that they have enough of the right members of all groups on the platform. Pricing is a key element of this balancing act.
Consider the example of malls as Matchmakers. The mall owners make use of the insight that groups in any multisided platform have different levels of interest in meeting other groups, and therefore would pay different amounts for this. These groups range from the ‘desperate to meet’ (the supermarket in the mall) and the ‘would be nice to meet’ (the shopper). The supermarket pays to be in the mall, and may even subsidise the shopper’s parking so she can be in the mall completely free, even if the shopper shops elsewhere too.
The Uber example
The authors identify critical issues in designing and starting a multisided platform. Uber offers an accessible example.
The Matchmakers succeed when they identify difficulties that hinder the various parties from dealing with each other directly. If you need a taxi in a hurry, but your small taxi company doesn’t have cabs available in your area, Uber provides a solution. Its app automatically signals to the closest Uber driver who wants a ride and identifies your location, thereby removing the hindrance.
To achieve this, the Matchmakers have to secure critical mass in order to launch. If there aren’t many people needing rides, or there aren’t many people with cars willing to sell rides, you could not get a ride when you need one: the chicken-and-egg problem. Uber doesn’t have to own cars; only an enabling technology, to enable it to grow chickens and have eggs rapidly and simultaneously.
Low prices are always great for one side of the platform (the person needing a ride), but not for the other (the driver). Getting the pricing structure right is critical to launching a successful Matchmaker. This requires a balance between the interdependent demands of the multiple stakeholders: the driver who must cover his own operational costs and make a profit, and the people needing rides who could use their car or use a conventional taxi company. By keeping overheads low, all players in the multisided platform win.
Matchmaking is always part of broader ecosystems of competing providers, regulations and other institutions. Uber needs to navigate the problem of not being classified as either a taxi or an employer. Itr needs to fend off the antagonism of cab drivers who are seeing their clientele disappear. Uber is assisted by harsh drunk-driving laws, that encourage passengers to get a ride rather than drive intoxicated.
Matchmakers have to be concerned with the manner in which participants on the platform interact with each other. Many of these businesses have adopted governance systems, complete with ‘laws,’ ‘enforcers, and ‘penalties’. Uber passengers are encouraged to rate the drivers’ manners and driving ability. Poor driving will result in the driver being withdrawn from the system, and abusive passengers will be excluded from using the service.
It is the explosion of specific technologies that is behind the remarkable growth of multisided-platforms, the authors explain.
Uber’s costs of connecting to their various constituencies are negligible. The internet can connect some 3 billion people worldwide, which is over 40% of all people on earth. Rapid transmission of messages in all forms is now possible, through the ever-faster mobile internet connection. Drivers’ and passengers’ locations can be identified instantly through GPS systems and communication between all players in real time.
“When Uber decided to expand from San Francisco to Brussels, it didn’t have to build a physical distribution facility, or even hire a stable of dispatchers to handle calls and direct drivers,” Evans and Schmalensee report. All the participants using Uber hundreds of millions of times a year in 350 cities in 67 countries needed to do was to download the Uber app onto their smartphones.
Are you, or could you be a multisided platform? Whether you are technology-dependent or a physical multisided-platform, or interact with one, this is a valuable book.
Readability: Light --+-- Serious
Insights: High -+--- Low
Practical: High --+--- Low
* Ian Mann of Gateways consults internationally on leadership and strategy and is the author of Strategy that Works. Views expressed are his own.
