Some ideas for building an Amazon keyword database

1. Perform word frequency analysis on product titles through SellerSprite

2. Classify the keywords of frequency analysis into core words, selling point words, attribute words, location words, and irrelevant words.

3. Use Amazon ABA tool to find the search term ranking

Search Frequency Rank: The frequency ranking of each consumer search term in the entire site; if the scope is limited to women dress, only search terms containing women dress and their rankings will be displayed

Click Share: After searching, if there are 10,000 ASINs clicked, 0.53% of the clicks are contributed to ASIN1, and ASIN1 has 53 clicks.

Conversion Share: If the search for women dress resulted in 10,000 orders, 0.73% of the conversions were contributed to ASIN1, which had 73 orders.

4. Use the feature words to continuously search for relevant search words. Suppose the feature words of the product are deep v, long. Then you need to use deep v dress and long dress to search respectively.

5. Perform a frequency analysis on the search terms downloaded by aba again, compare the frequency of the titles, and find out the missing attribute words.

Only in this way can a more complete vocabulary be created.