Reborn Soft Rice King

You can search for “Rebirth of Soft Rice Wang Miao Bi Ge Novel Network (imiaobige.com)” in 100 degrees to find the latest chapter!

Li Qiguang touched his thin-headed hair, then got up and went out to work.

“Uncle Guang, I found that you have recently lost your hair badly.” Fang Tian looked at his head, his hair became thinner and thinner, and it would soon become a desert.

Li Qiguang said with a smile: “Yeah, I’m going to be very smart soon!”

Fang Tian drinking coffee said with a smile: “Is the work pressure too great, I will give you a vacation.”

“No, hereditary, I lost my hair when I was 50 years old.” Li Qiguang said helplessly with a smile.

Lin Keqing said: “You can wear a wig.”

Li Qiguang asked: “Any recommendations?”

Speaking of recommendations, Fang Tian really remembered a very critical thing, opened the 1000 Gold Mall and browsed the website.

I found that the website’s product recommendations are really not ideal.

Looking at what Fang Tian frowns looked like, Li Qiguang was puzzled: “What’s wrong, do you have hair loss?”

Fang Tian pointed his finger at the computer screen, and the focus was on the product recommendations on the webpage. “Have you found the website’s recommendations very problematic.”

Li Qiguang walked over and looked at it: “What’s the problem? These are the products recommended by the website to consumers.”

“But I’m a man. The webpage recommended me high heels. Don’t you think it’s silly to recommend such a website?”

Li Qiguang said: “It must be like this, and the website does not know if you are a man or a woman.”

Fang Tian shook his head: “This kind of recommendation is not what consumers want at all, what I need is personalized recommendation!”

For E-Commerce Shopping Network, the recommendation system is too important. It can intimately guess what consumers need, and then recommend products to consumers, thereby increasing product sales.

In this year, there is no intelligent personalized recommendation.

The recommended system for all websites is basically in two forms.

first, the website editor manually selects, and then puts the product on the website recommendation position.

second is a random recommendation.

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

But no matter which kind, it is not a smart personalized recommendation.

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

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

The first is high heels.

The second is leather shoes.

The third one is a children’s toy car …

Regardless of your account, Li Qiguang account, or Lin Keqing account login, the recommendations you see are the same.

This recommendation is very unreasonable.

Lin Keqing said: “I also feel that this recommendation is unreasonable. If the website can guess what I need intimately, this can increase my interest in buying.”

Fang Tian instructed Li Qiguang to make a call to Yang Fan, and the website design was the responsibility of Yang Fan.

Immediately, Li Qiguang dialed Yang Fan’s phone.

It did n’t take long for a black-faced youngster to walk in. Yang Fan ’s skin was such a color. I did n’t know that he came from Africa.

“Brother Tian, ​​why did you ask me to come here?” Yang Fan took the chair and sat down.

Fang Tian kept tapping the desktop with his fingertips: “The website is going to be a recommendation system.”

“Is it important?” Yang Fan asked.

“Very important.” Fang Tian tone affirmed: “This can greatly increase the user’s activity, and more importantly, can increase the conversion rate of goods.”

The conversion rate, to put it bluntly, is the number of views and transactions. 1000 people open the recommended product page to view, and only 1 person buys it. This conversion rate is too low.

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

Yang Fan understands that the key to knowing the personalized needs of consumers is the recommendation algorithm.

“How to do this recommendation algorithm?”

Fang Tian touch the chin thought for a while. “First, according to the consumer’s browsing records and search records, recommend products to consumers, this is the simplest and easiest way to guess consumer recommendations.”

This is not difficult to understand. The user went to the E-Commerce website to shop, what he searched for, what products he browsed, but not at all immediately placed an order, the website can be recommended to the user.

Yang Fan nodded: “What about the second way?”

“Second, it is recommended according to the consumer’s purchase record. He has bought it before, and the praise is relatively high, and this product is not durable, we can recommend it to him.

Yang Fan thought about it for a while, and understood it completely. Once you have bought a good review and proved that the consumer is satisfied with the product, the website can recommend it to him.

However, it can’t be durable goods. For example, consumers bought a mobile phone in the mall half a month ago. Impossible recommends another one.

But if a bag of Nescafé coffee, um, this can be recommended to consumers again.

Fang Tian took a sip of coffee and said, “Third, it is recommended according to surrounding products. For example, 3 days ago, when a consumer bought a mobile phone in the mall, we can recommend mobile phone related products, such as recommending a headset or a protective sleeve. “

“For example, if a man bought diapers, we can recommend him to buy beer.”

Yang Fan wondered: “Is diapers related to beer? Will men who buy diapers buy beer?”

“This question, you have to ask Li Qiguang.”

Li Qiguang’s son had the right to speak shortly after he was born.

Li Qiguang said with a smile: “Good recommendation, every time I buy a diaper, I feel a very depressed thing!”

“Haha!” Fang Tian and Yang Fan 2 laughed.

“The fourth recommendation method is classified according to users. The website classifies consumers according to their age, purchasing power, and hobby et cetera.”

“Through this intelligent algorithm, we found that A and B are the same type of consumer.”

“If customer A buys a comic book and then buys 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. Doing what he said would make the recommended products more intimate.

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

This set of recommended system speaking of which is simple, but behind it involves very complex intelligent algorithms, technical aspects of things, it is necessary for technicians to optimize exploration.

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

Finally, Fang Tian said: “This recommended system is not only used in the Shopping Network, it can also be used in other SoftCloud applications.”

SoftCloud doesn’t just own the E-Commerce website.

If SoftCloud News uses this algorithm, the recommended news will be closer to the user’s interest.

There are also SoftCloud NetVid, SoftCloud Weibo, Jin Yu Novel Network et cetera, which can all use this system.