Similar Databases
Suppose you are a web developer. How do you find all keywords in your niche?
Create a keyword list.
1) Run the program and open a new file: tab "File" - New File. 2) Create a keyword list: tab "Document" - New Document - Keyword List. 3) Add words to the list: Tab "Keywords"- Add - web development (all of the letters lower-case).
Find out what else were looking for those who are looking for "web development".
1) Select the search term "web development", click: tab "Keywords" - Get Similar Keywords - from the English 115 mln. Cloud Database.
2) Enter a search depth=1 (the depth= 2 would mean that each time a tip will be found more clues).
3) Get a list of relevant keywords (what else were looking for people who are looking for "web development").
4) Sort the list by popularity: click on the column headings and choose: Add column - Keyword Databases - English 245-mln. Keyword Database - Google Searches. Click the right mouse button and select: Sort Descending. Most commonly keywords (such us "product development") would be on top of the list.
5) Remove all the requests that are not related to your niche (for example "www", "graphics"). You can also delete all the words that are searched less than, say, 1000 times a month: Tab "Keywords" - Filter - Google Searches less than 1000.
You will get a list of high-frequency queries:
Expand the keyword list: add low-frequency queries.
1) Copy all niche keywords, select: tab "Document" - New Document - Find More Specific Keywords - From English 245-mln. Keyword Database - and insert keywords in the form:
You will receive a list of low-frequency searches containing those phrases.
You will get a list of all keywords in your niche:
* Sometimes it's inconvenient to put all the words in a single list (for example, if they are thematically different or if the list is very large). You can find a long tail keywords for each phrase separately: tab "Document" - New Document - Find More Specific Keywords - From English 245-mln. Keyword Database - - and type a first phrase (eg "silverlight"). Doing the same thing with all the phrases.
You will obtain separate keyword lists:
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