Google Feud and Autocompletion

When you search using Google, you can't help but notice that Google autocompletes your queries. For example, if you type DRAGON FRUIT and then click in the search box, you'll see suggested queries like these:

• dragon fruit how to eat
• dragon fruit tree
• dragon fruit side effects 
• dragon fruit origin
• dragon fruit recipes
• dragon fruit calories
• dragon fruit taste
• red dragon fruit

Sometimes these guide your search, cluing you into things about dragon fruit you weren't aware of or the right words to use. Supposedly, the results are due to the popularity of terms used when searching for dragon fruit. For more information read this article.

This feature has been around a long time and Google wasn't the first to use it.

There's even a game that uses autocompleted queries: Google Feud

The game is instructive and aligns nicely with an Information Fluency observation: the "One in Five Rule." 

When creating queries your goal is to find a combination of keywords that are an exact match for the wording in the documents you seek. Different authors use different words to describe the same thing. There isn't strong evidence for the 1:5 ratio, but there are, on average, 13 synonyms per word, (see InfoWorld Dec 15, 1986). Considering that Web pages employ a limited range of language, it seems reasonable one's chances of searching for exactly the same keyword as a Web page author may be closer to 1 in 5. If an author uses a highly technical term, the ratio increases and you may never match it. In that case you have to search using contextual clues. The 1 in 5 "rule of thumb" means you should expect to revise your query more than once before matching keywords with an author. [Source]

Play Google Feud. How often do you match with any of the suggested queries?  There are four categories: CULTURE, PEOPLE, NAMES, QUESTIONS. I did poorly, matching the suggested keywords 7 times in 31 tries across the different categories. Interestingly, that's not much better than 1:5.

This experience opens a searcher's eyes to the possibilities that there are other words to use in queries than one person can think of. Finding the most relevant results depends on keywords another person has used. How you find those is a combination of trial and error, trying to think like the author whose words you are looking for and searching snippet results for clues to related words.