The annual Double Eleven is over, how much money have you spent? Have you grabbed your favorite baby?
I don't know when it started, an ordinary November 11th became a day that everyone was waiting for. Everyone's love for Double Eleven can be said to be as high as for the Spring Festival.
Without further ado, let’s take a look at a turnover on Double Eleven this year:
At just 26 seconds after midnight on November 11, Tmall double eleven orders peaked at 583,000 transactions per second.
From 00:00 on November 1st to 00:30 on November 11th, this year's Double Eleven has a turnover of 372.3 billion, and more than 300 brands have real-time turnover of over 100 million yuan.
Double Eleven came to an end. Tmall Double Eleven’s total turnover was 498.2 billion yuan, an increase of 26% over last year.
The technology behind Double Eleven
In fact, everyone will see such data every year, but every time they see it, they will be surprised. How can the transaction volume be so high! This amazing number must be closely related to our current quality of life. Everyone has solved the basic food and clothing problem, and will definitely want to improve their material quality of life. Many of the latest technologies are hidden behind these numbers. For example, cloud computing, distributed messaging engine, Docker technology, online transaction data real-time and offline computing capabilities, Ali artificial intelligence, VR technology, front-end technology, big data, monitoring technology, logistics technology, etc. Here is a brief introduction to big data and AI artificial intelligence technology.
I believe everyone has encountered this situation. I didn’t know what to buy, but when I saw that the products recommended on Taobao were all products I liked and needed, I couldn’t help but click in and take a look. Single out.
It feels like Taobao is like a roundworm in your stomach, knowing all your thoughts and knowing what you want to buy. First of all, please rest assured that Taobao will not eavesdrop on your phone. It is your own behavior data that makes Taobao aware of what products you need. When registering an account, you need to enter your name, phone number, gender, and sometimes your location, but these are only trivial basic data. More importantly, your consumption records, taxi frequency, public accounts you pay attention to, games you have played, financial habits, whether you have car loans, mortgages, insurance, and red envelopes. These behaviors will eventually become thousands of facts. Labels become part of your behavioral data. In fact, it is not difficult to collect these tags. The difficult thing is to build a model, find what you are really interested in from the cluttered tags, and then form a user portrait.
for example
Let me give you an example. When you browse an article labeled basketball, it may just be accidentally clicked by your hand. At this time, you need to judge the appeal of this article to you. For example, see if you have commented, liked, reposted, bookmarked and other operations. The longer you read, the higher your attention. In the end, short-term behavior cannot represent long-term interest, and the weight of a single reading behavior will continue to decay over time. In addition to content interest, this kind of thinking can build models in multiple dimensions such as consumption power, consumption interest, and social habits to calculate your preferences. So as to get your user portrait. In this way, you can recommend the products you need based on the calculation results. So every time you open Taobao, what you see is the result of intelligent calculations, which are the products you like and frequently browse, so this subtly increases your desire to buy.
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