My Fintech Empire

Qiu Guangcheng and Wu Cheng couldn't help but nodded. They remained silent and listened to Fang Hong's discussion: "These three ways are from the perspective of the information receiver. So think about it from the perspective of the information creator. When we look at the three information distribution methods from this perspective, what will it look like?”

Fang Hong continued: "The first attention model is like if you want to create a public account, the most important thing is to increase your fans. If you enter the game late, it will be difficult for you to create a big hit. This model is very difficult for creators who are late entrants, and this is also the dilemma that public accounts will have to face in the future.”

Qiu Guangcheng was surprised when he heard this. The current WeChat public account is very popular, and its success is being studied by various colleagues. He didn't expect the big boss to see it so clearly. If he thinks about it carefully, it is true. The words are clear, concise and concise, and get to the point.

Fang Hong looked around the two people and said: "The same is true for search. When you are an information creator and you want your target audience to search for your content, you have to guess what users are searching for? What will users search for? ? You need to do a lot of search engine optimization. The same logic applies. If you have not been a webmaster in the early days and have not entered the search engine news source, your content can only be on the back of the site. This is also true for late entrants. It’s very unfavorable, so even if you cross hundreds of schools, you won’t be able to achieve success.”

“As for the third algorithm recommendation model, after you publish content, as long as your target audience is accurate, the algorithm will automatically identify your content and recommend your content to people who may like it. To put it simply, you only need to Just post the content and wait for it to become a hit."

At this time, Wu Cheng immediately said: "Then the question is, after Douyin is launched, a large number of short videos will be uploaded every day, maybe tens of thousands. How can you make your video become recommended by the algorithm? What about one ten thousandth or even one hundred thousandth?”

Fang Hong couldn't help but smile when he heard this. After a moment, he said with a smile: "You don't have to worry about algorithm recommendations. When you led the delegation to acquire Toutiao, I already said hello to Chen Yu and will provide you with algorithm recommendations." Technical support, this guy’s technical development capabilities are stronger than his ability to invest in stocks, maybe it’s all ready by now, just waiting for you to get it.”

"In general, it means 'identifying people by cutting off things'. Cutting things means that the algorithm needs to identify what your piece of content is. Identifying people means that the algorithm needs to identify the person who is streaming content on the platform and what he has. What kind of preferences do you have, that is, how much user portrait do you have? In the entire domestic Internet system, who else would you rather have?"

It can be said that Qunxing Capital has the most complete user portrait, because the data of its major subsidiaries are under the coordination of the parent company, and all data links are open.

It is no exaggeration to say that based on the big data we have, Stars Capital understands a certain user better than the user himself.

This is the power of big data and the unparalleled value contained in big data. It has super strong monetization capabilities.

Based on the algorithm technical support provided by Chen Yu, it is known that a person likes to play basketball. The algorithm determines that there is an article about basketball, and then it will recommend this basketball article to people who like to play basketball.

The logic of algorithm recommendation is actually that simple.

Fang Hong said methodically: "The algorithm I asked Chen Yu to develop mainly has two methods for recommendation. The first is a content-based recommendation algorithm. What is a content-based recommendation algorithm? For example, after a person enters Douyin, He liked an article A about playing basketball, and after identification, the algorithm found that article B was also related to playing basketball, so the algorithm recommended article B to him, which is content-based recommendation."

"The second is algorithm recommendation based on collaborative filtering. The term collaborative filtering may be a bit obscure. In other words, it is algorithm recommendation based on user behavior. This algorithm recommendation based on user behavior can be subdivided into two categories. One is One is an algorithmic recommendation based on user behavior of items, and the other is an algorithmic recommendation based on user behavior.”

Fang Hong further developed the algorithm recommendation for Wu Cheng that deconstructs these two types of subdivisions: "Item-based user behavior algorithm recommendation. For example, you are user A and you like item 1 in the system. The system identifies users who like item 1 as well. User B, User C and User D, and then the system also recognizes that User B, User C and User D also like Item 3. Based on the behavior of users liking items, can we guess that Item 1 and Item 3 are similar? Woolen cloth?"

"So the system recommended item 3 to user A. This set of logic is based on the recommendation based on the user's liking for the item, so it is called an item-based user behavior algorithm recommendation, because its recommendation logic is that the user likes it The act of objects.”

"The second user behavior algorithm recommendation based on users has the same logic as the first one, but the difference is that people and items are reversed. In this user behavior recommendation method, the target of system identification is no longer Items are people, and users are divided into different categories based on user behavior to make similar recommendations to them."

At the end, Wu Cheng nodded involuntarily: "I understand. This algorithm recommendation model is really powerful. With the support of the big data user portraits owned by the parent company, I have a hunch that Douyin will definitely become a phenomenon in this track." A hit.”

Wu Cheng immediately saved the recordings on his mobile phone and encrypted them. These are the essence of the development of Douyin. It can be said that the big BOSS has given a set of "nanny-level" development strategies. All you need to do is follow this idea. Just do it, and at most you can optimize the details. It’s not an exaggeration to say that you can win without hesitation.

Fang Hong said simply: "Just follow this idea, and Douyin will become a hit."

After a while, Qiu Guangcheng, who was basically silent, said: "By the way, after the founder of Toutiao and his team left, what did Mr. Zhang do? He took away a lot of money, and there was no restriction from the non-competition agreement. .”

Wu Cheng listened thoughtfully, then looked at Fang Hong and said puzzledly: "This is also a doubt in my mind. When you went to acquire Toutiao, why did you specifically ask that if Mr. Zhang's team leaves, not to sign a competition agreement with him? ?”

Neither of the two people present quite understood this. After all, Mr. Zhang is the founder of Toutiao, and he also understands the potential of this track, and he definitely knows how to play it. It stands to reason that he should sign a non-competition agreement or something to restrict him. Enter this track for a period of time to prevent him from getting money and becoming a potential threat again.

Hearing this, Fang Hong said with a half-smile: "For two reasons, Mr. Zhang will be able to sell more quickly if he doesn't sign a professional agreement. The other reason is that I want him to re-enter the game. If he signs a non-competition agreement, he will How can you get involved in this track again?”

Qiu Guangcheng and Wu Cheng looked at each other. It was even more difficult to understand when they heard the big boss's words. However, from these words, they both heard that the big boss obviously had a deeper back-up plan, and they both immediately Curious.

…