An accurate and effective keyword database is the basis for the construction of Listing. Whether it is the early listing of the Listing, or the subsequent advertising optimization, it needs to focus on keywords. Therefore, it can be said that the keyword database of a product is the core resource throughout the entire Amazon operation process.

The keyword mining function of Seller Wizard has been fully upgraded, and it is newly launched~ By locating the products under the keywords, and then mining the keywords associated with these products , digging down layer by layer, from 1 to 10, 10 to 100, 100 to 1000. …..Finally build a huge keyword database associated with the query keywords, add more keyword search traffic entrances for the product, and occupy more keyword pits.

The following is an introduction to the specific use of this function in the following four scenarios.

1. Using words to expand words – quickly build a precise keyword database,

2. High-frequency words – batch analysis of keyword attributes

3. Advertising – keyword competition analysis,

Fourth, big words expand small words – dig deep and subdivide long tail words

1. Using words to expand words – quickly build accurate keyword database

Expand relevant keywords through the core subject of the product, screen for relevance and eliminate irrelevant keywords, and finally obtain an accurate keyword database.

Taking the phone stand as an example, suppose our product is a mobile phone stand with adjustable height and angle, the appearance is as shown in the figure below.

After entering the keyword phone stand in keyword mining, click on the query immediately, and we get an initial thesaurus with 2396 keywords:

Then, through the following steps to determine the relevance of keywords and products, and filter out accurate keywords.

1. Judgment based on keyword relevance

Relevance represents the proportion of ASINs of the same competing product in the natural ranking of the first page of Amazon search results for the keyword and the query keyword.

The higher the correlation, the more ASINs of the same product that the keyword and the query keyword point to, and the higher the correlation between the word and our query keyword.

Here we filter out keywords with a correlation greater than 5 and traffic by setting the correlation > 5 and the monthly search volume > 100. There are a total of 296 keywords:

(The value filled in the filter condition is for reference only, and the actual operation needs to take into account factors such as the word size of the initial keyword database)

2. Judgment based on product appearance

Hover the mouse over the corresponding keyword, you can see the top 10 product images (natural search results) of the keyword under the Amazon front-end search results, and quickly determine whether there is our same product through the product image.

If there is the same product, it means that our product or the same competing product can be searched on Amazon through this keyword.

If none of our top 10 products have the same product, it can be determined that the keyword is less relevant to the product we want to make and is unlikely to bring us exposure.

Click the number in front of a keyword to delete the keyword.

After the above series of screening, we have obtained an accurate keyword library that is highly related to the product, which can be exported to an Excel table for secondary analysis:

Of course, when using the keyword database for listing, the validity of the keywords should also be considered. According to the weight of the keywords in Title>Five-Point Description>Product Description>Search Terms>Others, the key with greater possibility of ordering is preferred. word.

The reference indicators are: AC recommended word. After selecting the keyword with the AC logo, it can be determined that the word has an order, and the order performance is better than other keywords.

There are also indicators such as keyword purchase volume and purchase rate:

In addition, the weight of keywords can also be judged in combination with the title density.

Title density refers to the number of product titles that use that keyword on page 1 of Amazon's search results.

The higher the title density value, the more competing products with the keyword embedded in the title on the first page of the search results, which means that the weight of the word on the product is higher, but it also means that the keyword competition will be greater. .

2. High-frequency words – batch analysis of keyword attributes

After obtaining the accurate keyword database, the keyword frequency analysis is helpful to understand the product attributes and search habits that buyers are most concerned about.

Copy the 182 precise keywords we got directly in the Excel table and paste them into Keyword Mining-Batch Analysis Keywords:

Click to query immediately and expand high-frequency words. The number after the root represents the frequency of the root. The higher the frequency, the higher the weight of the keyword.

According to the different attributes of keywords, we can classify keywords and understand the user's interest tendency to give priority to burying words:

Product noun: stand / holder

Scenario words: desk/phone/cell/iphone/ipad/mobile/tablet/bed/desktop

Function words: adjustable / cute / foldable / portable

In addition, the word frequency analysis of the keywords expanded through the product core main word phone stand can be used to expand the subdivision scene of this type of product as a reference for the selection of vertical categories:

Such as tripod (tripod type), mount (mount type), ring (ring type), shower (shower), gooseneck (gooseneck type) and so on.

3. Advertising – keyword competition analysis

When advertising for keywords, we need to focus on whether we can push the keywords to the target ranking with the fastest efficiency and bring target traffic and orders.

The core influencing factors of keyword ranking are the number of orders and conversion rate, so each keyword ranking has a corresponding target number of orders . The SPR indicator in keyword mining is to estimate how many orders each keyword needs to reach the homepage. .

Arrange the acquired precise keywords in ascending order of SPR value, and you can get the keywords that require the least amount of orders on the home page:

In addition, it is necessary to examine the maturity of product listings under keywords, that is, the comprehensive operational strength of competing products. These factors determine the difficulty of keyword competition.

The market analysis indicator in keyword mining shows the average product price/number of ratings/score value of the keyword in the first 3 pages of Amazon search results (natural search results), which can help us preliminarily judge the difficulty of entering the market .

For example, the average score is low, indicating that the barriers to entry for new products are not high, and the difficulty of creating new products in this market is relatively low.

There are other indicators that can be used to measure the competition intensity of keywords, such as click concentration, PPC bidding, number of competing products, etc. Everyone can sort keywords according to an indicator that they care about most, and filter out the most cost-effective ones. keywords to obtain more accurate advertising traffic at a lower cost.

Fourth, big words expand small words – dig deep into long-tail words

Keywords can generally be divided into core words and long tail words. Although the core big word traffic is large, it often means more intense competition.

Expanding the segmented long-tail words through the confirmed core big words can quickly lock in the buying crowd. Although long-tail keywords have less traffic, they are more accurate, have a relatively higher conversion rate, and are more friendly to new products.

Take yoga mat as an example, enter a keyword in keyword mining and check the root match (that is, keyword static mining in the old version), and keyword expansion can be performed based on the keyword yoga mat.

The results obtained all contain the word yoga mat:

Product features such as yoga mat thick (thick yoga mat), large yoga mat (large yoga mat), and yoga mat non slip (non-slip yoga mat) can be excavated.

The monthly search volume of such words is medium, but the purchase rate is high; and the SPR value is low, that is, only a low sales volume can make the keywords appear on the homepage, which can be used as the main keyword candidates in the early stage.

Or superimpose the word count indicator (the number of words in the keyword phrase) to dig out long-tail words that are easier to cut into:

In addition, according to root matching, it is also possible to mine product segmentation scenarios, expand market segments under vertical categories, and serve as a reference for product selection.

For example, yoga mat bag (yoga mat bag), yoga mat strap (yoga mat strap), yoga mat towel (yoga mat towel), foldable yoga mat (foldable yoga mat) and other market segments excavated by yoga mat: