On the design of e-commerce website Sales List

When you buy a book, buy the book you want, and then choose a few other areas (such as Bank accounting Principles) of the classic books to see. For their familiar areas of the book selection is relatively easy, basically through friends recommended, Blog, Twitter, SNS, professional forums, such as Word-of-mouth is easier to learn that those books are recommended. But for oneself is not familiar with the field of books of the pros and cons can not be judged. Through watercress, http://www.aliyun.com/zixun/aggregation/8699.html "> related recommendations, keyword search and other ways to find a long time also did not find the right book, wandering when the direction when the" when the list ", using a bit, The effect is not bad, found a few good books.

Generally speaking, I have to buy books through the following methods:

1, tags/keyword search method: If you know the content of the label/keyword, then when, Amazon, watercress on the keyword search, and then in the search results of a traversal, according to the score, evaluation content, etc. to determine whether it is worth buying.

2), association Recommendation method: through the watercress/when, Amazon books on the relevant recommendations to find

3, Classification Traversal browsing method: If do not know the clear label or keyword, then through when, Amazon classification browsing way to traverse view, and then combined with scoring, comments content to decide whether it is worth buying.

4, Web2.0 New media law: Through search engines, Twitter, professional forums, SNS community and business professionals blog and other ways to see those books are highly recommended.

5), Sales list method: see the major sites of the Sales list list, see those books are hot, high ratings and so on

Of course, these methods are not completely independent, and various methods are often used in combination.

Compared to the advantages and disadvantages of other methods there are many professionals in the proving to discuss the design of the sales list few people talk about, it is worth in-depth thinking and discussion, so record the thinking of the system.

1, to show the quality of the site to help users make decisions

2), reflect the popular trend, guide users to consume

3, as operational indicators, optimize operational efficiency

In several major e-commerce sites, only when the list is placed alone in the first level of navigation menu, and in the rankings are also more levels of classification, multi-dimensional, and other sites are basically a simple list of classified sales rankings or no ranking concept. Perhaps these sites feel that the sales list is worthless and there is no need to devote a lot of effort to optimizing this part of the user experience.

For me, "When the list" is very useful, through the "When the list" I discovered a few good books. This "original" approach is commendable compared with the previous copying of Amazon.

The following figure is a rough "when list" structure.

How to design a good list is not what I am concerned about, I am more interested in: A good list of the standard design should be what?

Personally feel that a good list of standards should be: multidimensional, multi-level display of product quality site products, to help users quickly dig out valuable products

The so-called multi-dimensional refers to the list should be from a number of dimensions to describe the contents of the list of products, to meet the user's multiple perspective comparison needs, including:

1, Time series: The form of different time to show the list content, or the time period (cumulative list) Form to show

2, Web2.0 elements: including user ratings, collections, search, number of clicks, tags (tag), user groups, share number, comments, etc.

3), Sales

4), Product category

5), Trends

6), Product mix

7), Special

8), geographical

Wait a minute

The so-called multi-level refers to the list of the display should be hierarchical form of refinement, in line with the user from coarse to thin, from the total to the point of browsing habits.

For example, "When the list" of the five-star book List-> history class-> cumulative list->top50

Overall speaking, according to my standards when the list is still good.

Only in product design and user experience, "when the list" There are many areas worth improving, such as:

1, the list content is only in "when the list" only have the entrance, in fact, if the product details on the left side of the recommendation bar can be placed when the content of the list, to facilitate the user decision is still very helpful.

2, "When the list" If you can with such as major publishing houses jointly published book rankings, and then become the industry authority of the list, for when it is also a valuable brand resources.

3, in the current EDM in the "when the list" link, but for most people do not feel too much, you can in the EDM in accordance with the interests of users to highlight the "when the list" corresponding to the recommended content

4, "When the list" can be appropriate to use a number of graphical forms to show the relevant trends, this is more intuitive than the number of clear.

At present, "when the list" of the list should be through the system of OLAP, according to the model summarized statistics, this way called "System list." The system list is better at reacting systems in the past and the current sales of hot products, in the user interaction is not very strong.

Because E-commerce and community integration is a trend, therefore, if the community activities can be integrated into the form of topics, votes, groups and other forms of user-defined list, such as "product manager must read the top ten books", "The architect must read ten books", for the active community atmosphere, enhance interaction with users, It is meaningful to promote user purchase. This can be learned from the Twitter lists design concept.

The list is not contradictory to the recommendation system itself, both of which aim to help users discover valuable resources. Originally in the study recommended engine time has been concerned about the Recommendation Engine Association algorithm, collaborative filtering algorithm, such as machine algorithms, in fact, the list content can be used as a recommended data source, but also to some extent to alleviate the recommendation of the "cold start" and other issues.