User recommendation-"Dress Up Temptation Law"

"User Recommendation" of the opportunity from a shopping site, "http://www.aliyun.com/zixun/aggregation/7998.html" > Guess you Like ", the recommendation of the disguise of precision high accuracy is really staggering, think about it, Must be my loyalty to the product of the high result of the database of my operation traces silently "record", this is the procedure to see through the likes of a vector.

From the recommended effect, the full spread of advertising recommendations, specific users will be aware that the information is not the point of interest users will often ignore or hold a suspicion, and the recommendation for personal preference-based on the recommended accuracy, the rate of acceptance of the information in turn increased. Recommended, stand in the market point of view, nothing more than to sell products, especially unsalable possible products, so a variety of recommendations, advertising offensive, hope that users know, but the user ungrateful. What users need to know is the information that really relates to me.

Then the user recommended in the end by the business or in accordance with user preferences to push, is the arrangement of blind Date or laissez-faire free love? As a user, the choice of relying on their own wisdom is far more reliable than the colorful recommendation ads, but interestingly, the results may be the same.

From this perspective, individuals are more likely to encourage targeted user referrals, although this user recommendation is all over the world, but not much has been done well. Some of the beautiful name of the user recommended is not accurate, this is a bit embarrassing, neither pull off and hard to recommend the distance of advertising, and did not do considerate private customized services, these recommendations almost equal to the chicken.

To achieve accurate and effective user recommendations, first of all, must master the user interest point and its behavior habits:
Refer to the following points: The behavior of the user browsing the document, such as performing a click to jump to a link, users focus on the page information, such as the user has performed a save, printing and other actions related information, the user has marked the type of information and user access to repeat the high, the number of operations, browsing time long function or information, The most important thing to ignore is of course the user has entered the information manually, including search keywords.
After you have collected this information, you can use the Dress up Temptation method to specify the appropriate recommendation guide. First think about how people usually go shopping when they choose to buy the right clothing accessories.

Step 1 price comparison for target items

For the identified target users, timely introduction of the best price recommendation of similar products

Step 2 in the purchase of the same time will be concerned about the trend of the same products

To give the same kind of the latest product recommendations, seize the user's eyes and search desire

Step 3 after purchase to the right one product extension psychology easy to buy

With the series of products recommended, such as the user bought shampoo, that is not the way to recommend a hair conditioner?

Step 4 Other clothing accessories that focus on one of your favorite brand tones

Fuzzy category of the same keyword recommended (such as the user purchased a large number of red clothing, whether it can be ' red ' as a recommended keyword, corresponding to other non-clothing products)

SETP 5 have a desire to pay attention to the product of their favorite style which accords with their aesthetic taste

Extension recommendations (such as user preferences suspense books, whether you can recommend similar movies or plays?) Even activities with logical analysis factors, related to the theme of the site of the travel of virtual people? ）

This way of filtering out the user's recommendation can not only increase the user site adhesion, but also quickly get the use of high-value data, more intimate. Carefully try to figure out the needs of users, take the "dress temptation" ideas to provide user-friendly user recommendations in the user has a good user experience at the same time harvest to the satisfaction of the sales effect.
This article is from: http://www.365ucd.com/archives/1633.html