“Link Popularity” versus “Search Engine Saturation” Indexes

“Link Popularity” (LP) and “Search Engine Saturation” (SES) indexes are two different and complementary ways of measuring your web site’s ranking and relative importance on the web.

LP indicates the number of web sites with links to your domain.

SES, on the other hand, indicates the number of pages on your web site indexed by various search engine robots.

In general, the higher these numbers are the better it is.

However, there are caveats as in everything else in life.

High LP numbers, for example, can be generated by links coming in from web sites that nobody is visiting anyhow. All links are not created equal. A link from yahoo.com is perhaps worth a million links from nobodyvisitsme.com (just an example).

In the infancy of the Internet, “Directory Farms” were created to drive up the LP numbers. These were web sites with nothing in them but a bunch of web links. But these days you will be penalized by most search engines if your link is included in such “farms.” So you have to be as concerned about the quality of your links as their quantity.

SES has its own issues too. You can create thousands of pages, for example, to generate a higher SES index but…

Are those new pages related to the main topic of your web site?

And do they make it easier or more confusing to navigate around your web site? When visitors get confused by your inconsistent navigation and unrelated content, they may leave forever.

There is a point where “abundance” tips over into “confusion” and to know when to add things and when to stop is at the heart of search engine “optimization” process.

(If more was simply better under ANY conditions, the process would be called “Search Engine Maximization” and not “Optimization.”)

There are many sites out there that generate both LP and SES reports; some even provide comparative data on competing web sites. One such site that I use and like is www.marketleap.com.

Check the LP and SES numbers of your web site regularly since they change frequently. The best practice is to take regular measurements and then take their average for a reliable benchmark.

If the numbers are good, try to understand what you did right and replicate it.

If, on the other hand, the numbers are falling, analyze the reasons why and take appropriate measures to counter the trend.