Welcome to the US-China Platform Wars (Part 1)

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We are seeing increasing collisions between leading Chinese and Western platform businesses. For example:

  • Since buying Uber China, Didi has continued its international moves – such as its investments in Indian Ola, American Lyft and SE Asian Grab.
  • Jack Ma has repeatedly said that 50% of Alibaba’s revenue will be international by 2025. This, plus cross-border e-commerce, is increasingly bringing them into competition with Western marketplace platforms, including Amazon.
  • Mastercard and Visa are continuing their fight with UnionPay in both China and internationally. UnionPay has announced that its card is now usable at 80% of US merchants and at all US atms.
  • Taikang Insurance became the largest investor in Sotheby’s. There is increasing competition between Chinese and Western art auction platforms (Poly and Guardian vs. Sotheby’s and Christies).
  • Everyone from Apple and UnionPay to Huawei and Xiaomi is jumping into e-payments, which are expanding internationally. Plus Ant Financial (i.e., AliPay) has been going international at a rapid pace.

Powerful Chinese platform businesses are going international, usually following their Chinese customers. At the same time, powerful Western platform businesses are looking for entry points into China. So we are seeing collisions between these unique, multi-sided platform businesses. Uber vs. Didi. Airbnb vs. Tujia. Ctrip vs. Expedia. UnionPay vs. Mastercard. Alibaba vs. Amazon. We are at the beginning of what I am calling the “US-China platform wars”.

This article is theory-heavy on how these types of businesses compete. It lays the foundation for the next articles. If theory is not your thing, you can skip to the next article if you want.

Point 1: Multi-sided platforms can have big advantages against traditional companies.

Multi-sided platforms (MSPs) are different than traditional vertical merchant businesses (VIs) because they have to serve more than one user group at the same time. Instead of having a set of customers (e.g., people buying lattes or smartphones), multi-sided platforms (MSPs) serve several groups simultaneously. For example, Alibaba must serve both online buyers and sellers. Dating clubs must serve both men and women. MSPs are common in software and we can see them in operating systems, social networks, video game development, and online marketplaces. But they are also common offline. For example, credit cards, shopping malls, auction houses, and dating clubs are all MSPs.

Having multiple user groups on your platform can create certain advantages. For example:

  • An MSP can use revenue from one group of users to subsidize the prices to another group. For example, Didi can use revenues from its drivers to decrease the prices paid by its riders. Traditional taxi companies, without the ability to subsidize, must then compete against these lower prices to consumers. Google, Amazon, and Alibaba have all been particularly effective at horizontally entering more traditional industries with this type of subsidy approach. For example, the map industry, which relied on map sales to customers, has been devastated by Baidu and Google Maps, both of which subsidize mapping to the point of being free.
  • Two-sided platforms (a MSP with two groups of users) can often wreak havoc on traditional merchant businesses (VIs). For example, eBay versus traditional retailers. However, three-sided platforms (e.g., Facebook and Google) can also often wreak havoc on two-sided platforms. For example, Facebook (which has +3 sides) can devastate advertising-supported media platforms like Yahoo and print journalism (two-sided platforms). And so on. Generally, the more user groups you have the more options you have for pricing, offered features and bundling of features. I’ve lost track of how many sides Tencent has on its platform.
  • Another advantage some MSPs have is the “network effect”, also called demand economies of scale. Basically, each new user makes the platform more valuable to other users. This effect can be direct. For example, every person who signs up for Wechat makes the service more valuable to everyone using it because there are more people you can connect with. The effect can also be indirect. For example, every new Didi driver makes the service more valuable to every rider, but not to other drivers. And every new rider makes it more valuable to every driver, but not to other riders. But the point is that bigger platforms with a network effect offer tangibly better services than smaller ones. So these types of markets tend to collapse to the larger players quickly (does Wechat have a competitor in China anymore?). However, not all MSPs have a network effect. Some do and some don’t. And some have but are weak and easily broken.
  • Finally, MSPs can have competitive advantages even without a network effect. You can often get economies of scale because these types of platforms often have significant upfront and ongoing fixed costs. You have to maintain the platform regardless of how many people use it. You can also get scale in marketing expenditures.

Point 2: Two-sided networks often struggle at the beginning with pricing, features and a “chicken-and-egg” problem

Two-sided networks (and other MSPs) can be difficult to launch. As mentioned, you have to serve two (or more) groups of users at the same time: both drivers and riders of private cars; both travelers and homeowners; both online sellers and buyers; both men and women (for dating platforms and local bars), and so on. And if you don’t have enough of each group, the whole platform collapses to zero.

Figuring out how to get the services, features and pricing right for both sides of your platform can be difficult. Usually you charge one side more than the other. For example, bars don’t charge women on ladies night. Then the men follow and you charge them more. Sony charges video game players but subsidizes video game developers. Pricing is tricky and most of the money typically comes from one side. And pricing rarely follows incremental costs.

Additionally, each group wants different things. You need to figure out what services and features to offer to each side. For example, eBay is offering its sellers decreased transaction costs, easy payment services, and a greater likelihood of finding a buyer. Providing each of these services costs money. And if you give sellers everything they want, you will likely lose or alienate buyers. And vice versa. Figuring out the right equation in services, features and pricing for both sides simultaneously can be very difficult.

This is one of the reasons why first movers in two-sided platforms are rarely the big winners. For example, Mastercard and Visa were actually late entrants into credit cards (a two sided network). The first mover was actually the Diners Club. American Express was third. MasterCard and Visa entered quite a bit later, when the equation for pricing and services was clearer. We will see this is a big factor in the home-sharing in China today. The equation for services and pricing in that still hasn’t been figured out.

Finally, there is also a “chicken and egg” problem at the beginning. When Uber launched, it had to get drivers to initially sign-up. But to get them it needed to offer them lots of riders. But to get the first riders, it needed to offer them lots of drivers (and short-wait times).

It is the same for credit cards. To get merchants to initially accept your new credit card (and pay 1-3%), you need to already have lots of cardholders to offer them. But to get cardholders, you need to say the card is already accepted by lots of merchants.

This is the chicken-and-egg problem. And there are lots of approaches to solving it. Usually it is by subsidizing one side and then doing a sort of zig-zag where you add some users and then some merchants and then repeat. It took Airbnb many years of struggle to get around this problem.

Point 3: Complementary and inter-connected platforms can be particularly powerful.

A single platform is good. As mentioned, it can have lots of strengths, particularly when competing against a traditional vertically integrated merchant (VI). Especially, if you can get a network effect and some economies of scale going.

But complementary networks can be even better. This is when you actually have two different MSPs serving a common set of users. The two MSPs can sort of amplify each other. For example, Microsoft Word (an MSP) is helped by being on the Microsoft operating system (another MSP). They both have a user group in common and amplify each other. A mapping application (sometimes an MSP) linked into Wechat (another MSP) is another example. Complementary networks are very common in China, where much of the mobile world has collapsed to a few powerful ecosystems (Alibaba, Tencent, Baidu).

However, inter-connected platforms are arguably even better. This is when a platform (or set of features) is actually integrated within another platform – to the point that the whole thing becomes inseparable within a service. The feature the user group sees and uses is actually being delivered by several interconnected platforms. For example, advertising-based media (e.g., Yahoo, broadcast TV) is increasingly inter-connected with advertising networks (i.e,. platforms that match advertising buyers with available inventory in real-time). That’s how the ads on Yahoo, Baidu and Google get placed in real-time based on who you are or what you are looking at. There are actually +2 interconnected MSPs delivering this service.

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Ok, that was quite a bit theory. But I think it was necessary to explain how these types of platforms compete. I will cite a lot of this in the following articles.

Thanks for reading, jeff

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I write, speak and consult about how to win (and not lose) in digital strategy and transformation.

I am the founder of TechMoat Consulting, a boutique consulting firm that helps retailers, brands, and technology companies exploit digital change to grow faster, innovate better and build digital moats. Get in touch here.

My book series Moats and Marathons is one-of-a-kind framework for building and measuring competitive advantages in digital businesses.

Note: This content (articles, podcasts, website info) is not investment advice. The information and opinions from me and any guests may be incorrect. The numbers and information may be wrong. The views expressed may no longer be relevant or accurate. Investing is risky. Do your own research.

Photo by Ming Jun Tan on Unsplash

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