#034 - PM Lessons by Meituan Co-Founder - Pt 27: Meituan - The History and Its Technology DNA
6 mins read - Long-term driver for business growth is technology
This is the last chapter of the Meituan PM Course. Thank you all for tuning in and sharing this newsletter and everything. Some of you have been asking for an e-book version of this course. I assumed since I publish openly here there’s no need for that. But I guess you may want it to read offline or keep it for storage. I guess if there are enough people who want it, I’ll make one. If you’re interested in that, let me know below.
The History
In 2003, Dianping was founded in Shanghai to solve the problem of finding good restaurants by crowdsourcing reviews from fellow consumers.
In 2010, Meituan was founded in Beijing to work on group buying.
Dianping was benchmarked against Yelp in the United States, although it was founded earlier than Yelp. And Meituan copied from Groupon. However, both Yelp and Groupon are considered failures by conventional standards, with a market value of about 1-2 billion US dollars. (Note: at the time he gave the lectures in Sept 2020).
The Groupon idea led to what was called the “Thousand Groupons War” in China in 2011.
At the height of the movement, there were four to five thousand group buying websites in the country. Dianping also entered the group buying market, and so became a competitor to Meituan.
The Thousand Groupons War happened very fast.
Meituan was launched on March 4th, 2010 - the first of its kind in China. By the end of that year, there were already close to a thousand group buying websites.
In October 2011, Meituan became the number one group buying website in China.
In 2012, most of the group buying websites went bankrupt. By then, the competitive landscape was clear - Meituan, Dianping, (Baidu) Nuomi, Lashou, and 55tuan were the sole survivors of this gladiatorial fest.
In mid-2012, Meituan launched a new product called Maoyan, to serve the movie ticketing market.
In 2013, we launched hotel booking services.
In late 2013 and early 2014, we started food delivery.
In October 2015, Meituan and Dianping merged. At this point, Meituan had 4 major business lines - group buying, movie ticketing, food delivery, and hotel reservations (OTA).
Our main competitors in group buying were Dianping, which received backing from Tencent, and Nuomi, which was acquired by Baidu.
In movie ticketing, the competitors were Alibaba’s Tao Piao Piao, Tencent’s Weiying, and Baidu’s Nuomi.
In food delivery, they were Tencent and Dianping-backed Ele.me, Baidu Waimai, and Alibaba-incubated Koubei.
In OTA, we were competing against Ctrip, Baidu-backed Qunar, and Alibaba’s Fliggy.
In every business line, we were burning money. The industry at that time likened us to Germany during World War II, fighting wars on multiple fronts. But Germany only fought on two fronts, and we fought on four.
In 2016, we launched merchant-facing restaurant management products.
In 2017, we launched Kuailv, dedicated to solving supply chain issues for merchants, including supplying fresh goods and financial services. In the same year, we launched Hazelnut B&B (i.e. homestay) and ride-hailing services.
In 2018, we acquired Mobike and filed for IPO.
In 2019, we launched Meituan Maicai (i.e. grocery e-commerce).
In 2020, we launched electric scooters/bikes, power bank sharing, and Meituan Select (i.e. community group buying).
Basically, every year, we have new businesses being launched, and none of them doesn’t entail a fierce fight.
In the foreseeable future, we will have many more new business lines, such as drone delivery and autonomous vehicle delivery which are being tested right now.
The Technology DNA
Meituan is a company focused on food. Our strategy focus can be summarised as “Food+Platform(s)”. It also covers travel, shopping, entertainment, accommodation, and transportation, as well as various services on the merchant side. Meituan's mission is "We help people eat better, live better".
(Note: The strategic focus has been adjusted to “Retail + Technology” since September 2021.)
There are many reasons why Meituan can do so many businesses well, one of which is our technology DNA.
In the relatively short [modern] commercial development in China, we had the good fortune to benefit from many dividends (i.e. population, urbanization, globalization, etc). For a lot of businesses, if they could seize just one of them, they would do well.
In contrast, if we look at the United States, where the commercial development history is longer and such dividends have been tapped out, we’ll see that the long-term driver for business growth is technology. Technology also includes scientific management practices and operational know-how. (Note: in other words, productivity).
For example, Walmart is actually a technology company. It launched its own satellite network in the late 1980s, which demonstrates the company’s commitment to investing in technology.
If a company wants to be competitive over the long term, at the core it must be a technology company, no matter what the company looks like from the outside.
One of the reasons why Meituan can win in the Thousand Groupons War is that Meituan has better technological capabilities than its peers.
For merchants to agree to be on a group buying platform, they usually would require the ability to settle their receivables from the platform any time they choose. If the group buying platform skips town or goes bankrupt after they’ve taken the consumer’s money, it’d be disastrous to the merchants’ cash flows and even cause the merchants to go bankrupt.
Meituan provided a system that does the accounting properly and pays the merchants any time they choose. As such, it gave merchants a sense of security when partnering with Meituan. In turn, it gives Meituan an advantage on the supply side in acquiring merchants. This played no small part in Meituan eventually winning the Thousand Groupons War.
Food delivery is a business that has prominent peaks and troughs in terms of demand. As a result, the servers need to be able to support both the peak and trough loads in a cost-controllable manner, which requires rather strong technical capabilities.
If we only aim to be able to handle the peak loads by stacking up servers, it’d result in overall low utilization rates. On the other hand, if we don’t do this, we won’t be able to handle the peak loads and suffer crushes. This makes load balancing a critical challenge. At Meituan, we let the servers handle user requests during peak loads and then run big data operations during off-peaks.
Technology Helps A Company’s Operational Granularity
An important metric to measure a company's operational expertise is its operational granularity.
For example, supermarket chains are run on a store-by-store basis. The boss is in charge of choosing the location, as choosing the right location is a core competence in retail. (Note: covered in Pt 22: Demand and Supply)
Once the location is selected, a general manager is appointed to run the store. If the location doesn’t become profitable after six months, then change the general manager. If it still doesn’t turn profitable after another six months, then it means you’ve got the location wrong.
The operational granularity in this case is pretty coarse. Still, some of the most famous supermarket brands in China run their operations like this. The market was forgiving during their development. So long as their locations are roughly right where they need to be, they won’t encounter major issues.
A level of granularity lower than this is by categories - knowing which categories of goods are the attention-grabbers, which ones are the money-makers, which ones are necessities, etc.
Further still, is to operate like 7-11, on the SKU level. At this level, it requires more systematic management, better data, etc.
The finest level of granularity is on the order level. In the era when goods were mass-produced, a money-making SKU is your holy grail. However, when goods were not mass produced (i.e. either handmade or personalized), not every order can be profitable.
The finer your operational granularity, the more logical your operation will run. (i.e. relying less on guesses or intuition). In the pre-Internet age, having a fine operation is almost impossible. Technology improved businesses’ ability to granularise their operations.
Operational granularity is also involved in setting KPIs for teams.
For example, if we want a business line to grow by 10%, then how to reasonably allocate this 10% into the business line’s constituent regions requires a clear understanding of the business operations in every region. And this is just a one-dimensional goal.
I’ll give you another example in food delivery. We need to know which cities should operate at a loss and which cities need to be profitable, and how much the profits or losses should be. Then we need to think about in a single city how we break down the overall KPI for the city to the city’s various business centers.
As such, Meituan's performance evaluation system is highly personalized. It needs to align with the business functions specific to that person. You can’t achieve such a sophisticated appraisal system without robust management systems in place.
Technology Helps the Digitalization of the Offline Economy
Before Meituan, I worked on a second-hand property resale website (TaoFang). It wasn’t a success.
At that time, when I visited real estate agencies for partnership meetings, I noticed that most of them didn’t have computers. In 2004, there wasn’t enough digital infrastructure to support an online real estate business. Hence, I sold the company.
By 2009, I started to notice that all the real estate agencies have been using computers. But it was too late, the market was already getting saturated. If I were to enter then, the only reasonable play I could think of would require the company to self-operate a lot of real estate agencies on the ground. I felt that was too “heavy”, so I didn’t pursue the idea.
Now, the foremost Internet-enabled real estate company in China is Lianjia (HomeLink). They started offline as a real estate brokerage chain, so they didn’t know much about the Internet in their early days. I saw their website domain was homelink.com.cn, so I bought the domain lianjia.com. (Well, I didn’t make much from them. Any money I made at that time was thrown into Meituan.)
Technology Helps With Targeted Subsidies
There are a few prerequisites for doing subsidies well. The first is segmentation - STP (Pt 13 - Segmenting, Pt 14 - Targeting & Positioning); the second is data analytics.
Without good data analytics, it is impossible to do your accounting correctly. Data analytics provides the foundation to have detailed customer profiles on which you test various subsidy schemes. Every subsidy scheme may require complex calculations. However, if you do your subsidies well, it’s quite possible to multiply the top line of the business.
Technology Helps Combat Frauds and the Black Market
One reason why Uber failed to compete in China was that during the subsidy war, their subsidies didn’t reach authentic users. It was siphoned away by the black market.
The average price for a ride was ¥16. And Uber may give the passenger a ¥15 subsidy and ¥10 to the driver. The subsidies were even higher than the cost of a ride. Because of this, some drivers would cooperate with their friends or interested parties to book fake rides to earn subsidies from the platform.
When there is an economic incentive, the black market that’s formed can be quite “industrialized”. They would also have good engineers working for them looking to exploit the system. Therefore, it’s necessary to have robust systems to fight the black market.
Fraudulent actors usually can be identified by certain traits. For example, a normal person wouldn't be at ten discrete locations in the city in a single day. To separate such usage patterns from normal users require strong data capabilities.
Artificial Intelligence
Technology also affects your ability to understand the needs of merchants and consumers, provide personalized recommendations, improve the efficiency of the supply chain, and more by leveraging artificial intelligence.
I’ll give you some examples of the application of AI at Meituan.
One dimension of the segmentation strategy for food delivery is the delivery radius. And the delivery radius is affected by the weather. During bad weather, we need to reduce the delivery radius to make lives easier for the delivery riders. How much the radius should be reduced is handled by AI. Under different circumstances, the delivery radius varies. So the delivery map is highly irregular, as it’s dynamically adjusted according to weather conditions.
Customer service also requires the use of AI.
It’s technically challenging to have customer service chatbots that can handle sequential conversations. For Meituan, most of our business lines have low average order values and low gross margins, so we can’t afford large-scale customer service teams.
Additionally, our business is local services, which are highly unstandardized, and we’re a platform, which won’t have enough control over everyone in the value chain. This means our user may require customer support often. Therefore, we have to use customer service bots to provide help at scale cheaply.
Of course, AI will be used extensively in emerging fields such as drone delivery, unmanned vehicle delivery, and consumer intent detection.
In conclusion, Meituan is a high-tech company.
[End of Course]
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