Amazon related traffic analysis

As we all know, Amazon's internal traffic consists of two important components: associated traffic and search traffic. Needless to say, search traffic is a big deal. Many buyers will search for related keywords to find the products they want when they buy something. Today, I will focus on Amazon's associated traffic.

The four major associated traffic entrances under the product details page: combined purchase, viewed again, purchased again and again, and advertising association have always been a battleground for sellers. In fact, the so-called associated marketing refers to associating one's own products with other product details pages in some way. Of course, the other products mentioned here not only refer to other people's products, but also include other products in your own store.

1. Frequently bought together (FBT)

If A and B are purchased together by buyers many times, they may appear here. They are usually some highly related and complementary products, as shown in the following figure, power banks and boxes for power banks:

2. Customers who bought this item also bought

This is the same as FTB, except that the number of products is greater than FBT and the position is lower than FBT, as shown in the figure below:

As long as consumers buy product A and product B, such repeated purchase actions will form a natural association after a period of time. Let me add here that A and B do not necessarily have to be purchased at the same time. If you buy A this month and B next month, for the association algorithm, it has the same weight as buying at the same time. So when there are relatively few repeated purchase combinations of A and B, it will appear in the "Bought again" column. When there are enough combinations, such as the largest number of all purchase combinations, it will appear in FBT, that is, under the "Bought together" column.

3. Customers who viewed this item also viewed

It is easy to understand from the literal meaning. According to Amazon's algorithm, the more times a product is viewed, the further to the left it is ranked, and the number of times it is viewed gradually decreases from left to right. The products on the left side, which are in line with visual habits, are more likely to be clicked.

4. Sponsored products related to this item

5. Compare to similar items

Note that this is not necessarily available in every category. In many categories, when your product is up for a week or so, there will be 5 positions below your product that will put your product and your competitors' products on a comparison screen with various colors, styles and prices. It is also possible to compare your product with your own. Amazon grabs recommendations based on product similarities and customer purchasing habits.

Customers can make comparisons very intuitively. If your product does not have an advantage, your competitors will emphasize most of the traffic, so you must pay attention to image quality and bidding to achieve absolute competitive leadership, otherwise the bounce rate will be very serious.

Summary: Amazon A9 algorithm makes related recommendations based on customers' browsing habits, purchasing habits, purchase frequency, and browsing frequency. These related traffic are beneficial to everyone: ① It increases the chances of sellers' product exposure; ② It gives buyers a variety of choices to avoid losing users to other platforms; ③ Amazon itself increases advertising revenue. Related traffic targets precise consumers, so the conversion rate is high. When your product is associated with a hot product, there will be a steady stream of traffic, so everyone wants to be associated with the hot product.

Through the above observations, we can find that for big sellers like Anker, the FBT under their product details pages are viewed again and again, purchased again and again, and even the in-site advertisements are mostly their own products.

By using powerful association techniques, the products in your store are linked to each other, perfectly building an exclusive traffic closed loop and keeping the traffic firmly in your hands. It is indeed a big seller!

Next, let’s take a look at the product details page of an ordinary seller:

Compared with Anker's all-in-one products, most small sellers' four major sections are more of other people's products. In this way, their own traffic is divided up by fellow sellers for nothing, and they use their own fertilizer to irrigate the land of others. Naturally, sellers don't want to see such a thing that harms themselves and benefits others.

It is difficult for ordinary small sellers to imitate the strict defense operations of the rich like Anker, so I will not say more here.

So is there any way to get as close as possible to popular products and get more traffic?

Of course there is. If you want to link your product to someone else's product to get traffic, it is actually very simple. Basically, you can adopt the following two ideas:

This method is relatively benevolent and has no risks. Sellers only need to place in-site advertisements for their products, and the system will automatically identify and match them to the relevant product pages, so that when buyers buy goods from other sellers, they can easily find your products in the Sponsored products related to this item column.

However, before placing automatic advertisements, sellers must accurately fill in the product details, otherwise it will easily be automatically identified by the system as other irrelevant products.

In addition, there is another great advantage of placing in-site advertisements: when buyers purchase more products in a group, the product will appear in the two natural association columns Frequently bought together and Customers who bought this item also bought, forming a free association system.

Advertising, especially automatic advertising, actually plays a very important role in association. Many people turn off automatic advertising or use a very small budget to ignore it, which is very unwise. Why?

First, let me solve a long-standing puzzle for everyone. When you are running ads, especially automatic ads, you will find a lot of garbled characters in the customer search term report. You don’t know what these garbled characters of numbers + letters are. In fact, these so-called garbled characters are the ASIN of the product. You can put it into the Amazon search box and search to see what corresponding products will come out. Generally, there will be products. What is the principle behind this?

For example, when you open any product page, such as product A, you will find that no matter you search or click on the product URL directly, this column: "Sponsored products related to this item" is always there. In other words, this column of sponsor ads follows product A instead of keywords. Then a consumer, while browsing product A, finds a favorite product B (B has already opened an ad) in the ad column below the product A details page. Clicking on product B to enter B's page, the ASIN of product A will be displayed in the customer search term in B's ad search term report. In the long run, if the number of combined purchases increases, this product B will also appear in the two natural association columns of Frequently bought together and Customers who bought this item also bought of product A. Then, if you click here, there will be no charge, which can be more natural. In order to form a stable association system, it is necessary to open more auto matches and increase the budget for automatic advertising. The more ASINs are associated, the larger your associated external link network will be, and the overall sales will also soar. Let me add one more thing here, ASIN cannot be used as an advertising word, nor can it be negative. It is a relatively unique existence.

So, nowadays, with the increasing cost of PPC advertising, everyone is questioning whether it is necessary to run advertisements. Of course, there are advertisements, even if it means losing money. On the one hand, successful advertisements greatly promote and stabilize natural rankings, especially the exact matching mode. On the other hand, auto matching greatly promotes natural associations. You can use advertising associations as an introduction, and continuously purchase enough advertising associations to promote natural associations. In the long run, it will definitely be of great benefit. Short-term losses are to prepare for long-term profits. We still need to have a long-term mindset when doing things.

There are also many sellers who will list their products under some Best Sellers by brushing browsing and purchase records.

When a buyer purchases product A and then product B, Amazon will automatically record the buyer's purchase behavior. When multiple buyers have the same purchase record, product A and product B will automatically have a "bought and bought" association. Similarly, the Customers who viewed this item also viewed page can be operated in this way, just refresh the browsing and purchase records.

But for ordinary small sellers, it is difficult to find a safe channel to carry out this operation. In addition, Amazon has been in the spotlight recently, and any carelessness will lead to trouble.

I recommend a website for viewing related traffic: www.yasiv.com. This website can display the entire related network system in the form of a network. You can see the picture below. The products with the most arrows are generally the ones that sell well because they have large enough related traffic. You can study this website carefully. On the one hand, it can help us deeply understand the related traffic situation and related traffic proportion of the product. On the other hand, it can be used for in-depth category mining, which is convenient for everyone to do vertical product selection.

(Compiled from: Moss's Spiritual Home, Meiou.com )