Original Title
Jones New York Compact & Foldable Travel Umbrella – Perfect Size for Small Car Umbrella w/ Automatic Open/Close Feature – Heavy Duty, Lightweight, Weatherproof, Wind Resistant – 2 Pack (Magenta/Teal)
Optimized Title:
Jones New York Elegant and Fashionable Women’s Folding Umbrella – Portable, Weatherproof, and Spacious – Professional Style Gear for Today’s Modern Women – 42” in Coverage – 2 Pack Set (Magenta/Teal)
When optimizing your Amazon product listing, it’s important to identify and eliminate low-value search terms. These are keywords or phrases that are unlikely to improve your search ranking or attract potential customers to your product.
Here are some examples of low-value search terms:
- Words that are already indexed: If a word is already used in your product’s title, bullet points, or description, it’s likely that Amazon has already indexed it for search. Adding the same word to your search terms field won’t improve your search ranking, so it’s a low-value term.
- Superfluous words: Words like “and,” “for,” “amazing,” and “new” may not be recognized by Amazon’s search engine and won’t improve your search ranking. They are also considered low-value search terms.
- Repeated keywords: If you’ve already included a keyword in your title, bullet points, or description, there’s no need to repeat it in your search terms field. Amazon doesn’t need duplicate keywords, and they won’t improve your search ranking.
To eliminate these low-value search terms, you can safely remove them from your search terms field and replace them with other relevant keywords. This will ensure that your product listing is optimized for search and improve your chances of attracting potential customers.
It’s important to note that eliminating low-value search terms is just one part of a comprehensive search term optimization strategy. To improve your search ranking and increase sales on Amazon, it’s essential to conduct thorough keyword research, identify relevant search terms, and regularly monitor and update your search terms field.