Everyone who does e-commerce knows that e-commerce products have three core modules: information flow, capital flow and logistics. Because I deal in virtual goods and do not involve logistics modules, I will not discuss logistics-related content. Information flow can be subdivided into commodity information flow and order information flow (order flow consists of information flow and capital flow). Therefore, I will explain it in three parts:
This paper first talks about commodity information flow.
"Commodity information flow" sounds very abstract. No matter how this term is defined, let's think about it first: what is the core of the product manager's concern in the whole process from the seller displaying them on the website to the buyer seeing these goods and then buying them? I think it should be the following two points:
To answer these questions, we should start with the design and construction of the whole commodity system.
When your product is very small in order of magnitude, all the goods are displayed directly without classification. For example, when Taobao was first launched in 2003, there was no classification, and all products were directly displayed.
When there are more and more goods and it is inconvenient for users to find them, it is necessary to have classification. In the field of e-commerce, we call this classification category, and the simplest category is the first-class category, such as Xiaomi Mall:/
As can be seen from the above figure, each commodity has only one category (first-class category) and no subcategories. Under this category, all the goods under this category are affiliated.
When the number of goods goes up again, reaching thousands, tens of thousands, or even more, the first-class category can't meet the demand. At this time, the concept of multi-category appeared, which is what we call "category tree". The category tree is generally about three levels, and try not to exceed five levels. Because e-commerce has a recognized iron law called "funnel model", that is, the deeper the level, the greater the loss, just like a funnel, the smaller the mouth, so the category level should not be too deep.
The picture above is an example of three-level classification. When sellers upload goods, they need to choose one grade at a time until the leaf category is determined.
When the magnitude of commodities reaches millions, tens of millions or even billions, new problems appear again. For example, clothing can be divided into men's wear and women's wear, and men's wear and women's wear can be divided into T-shirts and trousers. T-shirts are divided into many brands, and pants can be divided into cropped pants and cropped pants. According to the length, such a category tree is divided, overlapping and overlapping are inevitable, and it has become an unmanageable network.
Therefore, when there are more and more commodities, the classification is more and more detailed, and the user search is more and more personalized, relying solely on the category tree can no longer meet the needs of commodity management. At this time, another dimension classification method called "attribute" appeared.
How to understand "attribute"? Let's take a look at the following picture:
This is a description of the commodity "pants". We can use these adjectives on the left to describe them. This is what we usually call a label. But the classification of labels is too fine, and it is difficult to manage when there are too many labels. When we classify labels according to the way on the right, these category names become what we call "attributes", and the labels on the left are what we call "attribute values".
For a popular example, we usually use WeChat, and the contacts in the address book are sorted by 26 English letters, just like the kind we mentioned above. Then we classify the contacts according to their different characteristics, such as "family", "high school classmates" and "college classmates". If you like, you can also divide them into "ex-boyfriends" or "ex-girlfriends". These artificial classifications are labels, and classifying labels of the same nature into label groups is attributes (for example, classifying "high school classmates" and "college classmates" as "classmates"). This is just an example. Wechat only supports tags, not tag groups.
One thing to note is that when you enter goods in the background, you must attach attributes to the leaf category. For example, clothing-women's wear-miniskirt belongs to the category of leaves and can be linked with attributes, such as red, so that searching for red miniskirt can directly reach the goods. However, if you want to attach the attribute to clothing-women's clothing, there are many categories under women's clothing, so it is meaningless to attach women's clothing directly to red.
The "Finding Steel Mesh" (/) in the above figure is a typical example of "Category+Attribute". Steel products are classified by product name, material, specification, steel mill, etc. , and then classified by brand.
Does "category+attribute" solve the problem of all commodity classification?
The answer is no, of course. Let's look at a very common scene:
The essence here is a product and a set of logic, which can't satisfy two completely different user groups well. So what should we do?
The first person who thought of a solution was a product manager of Taobao in 2008. Once he went to Wal-Mart, he carefully observed the logic of commodity classification in traditional supermarkets:
Inspired by this, he came up with the architecture design scheme of "foreground category+background category"-dividing a product into two parts, one to satisfy the buyer and the other to satisfy the seller, namely:
The original category becomes a background category tree, and another foreground category tree is built, and then the leaf categories of the foreground category tree are associated with the background category through the mapping relationship. The leaf category of any foreground category can correspond to any one or more background categories, not necessarily the background leaf category. For example:
Let's take a look at an example of an actual scene, Taobao (/), which is commonly used by everyone:
The red circle in the above picture is a typical foreground category displayed by operators for operational needs, which maps specific products under a certain category or attribute in the background.
This design establishes the product classification system model of most of our current e-commerce products: foreground category+background category+foreground-background mapping management+attributes.
Looking back, to sum up, from the launch of Taobao, the first e-commerce website in China in 2003, to the blossoming of e-commerce websites today, the evolution path of commodity classification system can be summarized as five steps, as shown below:
At this point, the first knowledge point I want to share with you-commodity classification system is finished. In view of my limited experience, there may be many things I don't understand, or some things I don't know. Welcome to clap bricks ~
I look forward to your sincere communication with me, and I can collide with the spark of wisdom ~ _ ~