Rebirth of the Soft Rice King

For e-commerce shopping sites, the recommendation system is really important. It can intimately guess what consumers need, and then recommend products to consumers, thereby increasing the sales of products.

In this day and age, intelligent personalized recommendations don't exist at all.

There are basically two forms of recommendation systems for all websites.

The first one is manually selected by website editors, and then the products are placed in the recommended position on the website.

The second is random recommendation.

Sort by time, and the latest products will be placed on the recommendation.

But no matter which one, it is not an intelligent personalized recommendation.

When consumers open the webpage, everyone sees the same recommended content.

For example, the product recommendation on the homepage that Fang Tian saw now.

The first is high heels.

The second is leather shoes.

The third is a children's toy car...

Whether you log in with your own account, Li Qiguang's account, or Lin Keqing's account, the recommendations you see are the same.

Such a recommendation is very unreasonable.

Lin Keqing said: "I also feel that such a recommendation is unreasonable. If the website can intimately guess what I need, it can increase my interest in buying."

Fang Tian ordered Li Qiguang to call Yang Fan, who was in charge of the website design.

Immediately, Li Qiguang called Yang Fan.

Not long after, a black-faced young man walked in. Yang Fan's skin was such a color, and I didn't know he thought he was from Africa.

"Brother Tian, ​​why did you ask me to come here?" Yang Fan pulled the chair over and sat down.

Fang Tian kept tapping on the desktop with his fingertips: "The website needs to be a recommendation system."

"Is it important?" Yang Fan asked.

"Very important." Fang Tian said affirmatively: "This can greatly increase the activity of users, and more importantly, it can increase the conversion rate of products."

The conversion rate, to put it bluntly, is the number of views and transactions. If 1000 people open the recommended product page to view it, and only one person buys it, the conversion rate is too low.

If the recommended products are of interest to consumers, the transaction volume can be greatly increased.

Yang Fan understood that the key to knowing the personalized needs of consumers lies in the recommendation algorithm.

"How to do this recommendation algorithm?"

Fang Tian stroked his chin and thought for a while. "The first is to recommend products to consumers based on their browsing and search records. This is the simplest and easiest way to guess consumer needs."

This is not difficult to understand. When a user goes shopping on an e-commerce website, he searches for something, browses some products, but does not place an order immediately, and the website can recommend it to the user.

Yang Fan nodded: "What about the second way?"

"The second is to recommend according to the consumer's purchase record. If he has bought it before, it has a high rating, and the product is not a durable product, so we can recommend it to him."

Yang Fan thought for a while, and he fully understood.Those who have bought and given good reviews have proved that consumers are satisfied with this product, and the website can recommend it to him.

However, it cannot be a durable product. For example, if a consumer bought a mobile phone in a mall half a month ago, it is impossible to recommend others to buy another one.

But if it’s a pack of Nescafe, well, this can be recommended to consumers again.

Fang Tian took a sip of coffee and said, "The third option is to recommend according to peripheral products. For example, three days ago, if a consumer bought a mobile phone in the mall, we can recommend mobile phone-related products, such as recommending a headset or a protective cover." set."

"For example, if a man buys diapers, we can recommend him to buy beer."

Yang Fan was puzzled: "Are diapers related to beer? Men who buy diapers will buy beer?"

"You have to ask Li Qiguang this question."

Li Qiguang's son was born not long ago, and he has the most right to speak.

Li Qiguang smiled helplessly: "Good recommendation, every time I buy diapers, I feel very depressed!"

"Haha!" Fang Tian and Yang Fan laughed loudly.

"The fourth recommendation method is to classify according to users. The website classifies consumers according to their age, purchasing power, hobbies, etc."

"Through such an intelligent algorithm, we find that a and b are the same type of consumers."

"If customer a bought a comic book and then bought an Ultraman toy, then when customer b buys the same comic, he can refer to user a and recommend him an Ultraman."

Yang Fan, Lin Keqing, and Li Qiguang listened to Fang Tian's recommendation algorithm and found it very interesting. Follow what he said, and the recommended products will be more considerate.

In the following time, Fang Tian talked a lot, and Yang Fan recorded it all.

This recommendation system is simple to say, but it involves a very complex intelligent algorithm behind it. Technical matters need to be optimized and explored by technicians.

With this powerful recommendation system, the shopping experience of the mall is far ahead of other similar websites.

Finally, Fang Tian said: "This set of recommendation systems is not only used in shopping websites, it can also be used in other applications of Soft Cloud."

Soft Cloud does not just own an e-commerce website.

If its subsidiary Soft Cloud News uses this set of algorithms, the recommended news will be closer to the interests of users.

There are also Ruanyun Video, Ruanyun Weibo, Jinyu, etc., which can all use this system.

Chapter 1400 1400 / Brick Phone

After everything was arranged, Yang Fan and Li Qiguang got up and walked out of the office immediately.

Yang Fan worked on the recommendation system, and Li Qiguang formed a team to develop Jinchengtong, a payment tool.

After these two functions are completed, the competitiveness of the mall will reach a new level.

Lin Keqing started to work with a pen in hand.

And Fang Tian sat across from her, turned on Ruanyun News, and watched the news while drinking tea.

In this world, there are always so many things happening every day. If there is no good recommendation mechanism, it is really not easy to find the content you are interested in.

After refreshing the page, a piece of news caught his attention.

The headline of the news read in a big way—Consumers buy a 5000 yuan mobile phone online, and they get bricks!