Newsweek declared 2007 to be “The Year of the Widget” but Lijit backed it up by giving us some metrics to understand the detail. They break down:
- What widgets are popular?
- What is the distribution within widget verticals?
Their spiders manage to look at a lot of blogs but here a shapshot of ten thousand blogs were included. Whilst the tip of a 55million + blogoshphere it is still a very useful insight in to how people are using widgets. The first graph shows the top 50 widgets, ordered by percentage of blogs which contain at least one widget from the provider. We see the classic power-curve (aka long tail) shape, with Google the clear leader.

Next, check out the widget popularity by the type of widget, the “vertical”. We see that bloggers clearly want to know about their readers, even more than they want to monetize those readers. They are also very interested in knowing what other people are linking to them. “Ecosystem” refers to widgets that identify a blog as being part of a group, for cross promotional purposes and such.Within each vertical we can examine the breakdown between the competing widget providers.
Note that each pie graph represents the percentage widget distribution among all widgets from the vertical. Contrast this with the numbers below each chart which show the percentage widget distribution among all blogs which contain a widget from the vertical. This distinction is important because many blogs will use use multiple widgets of the same type. This is especially clear for advertising widgets where 90% of all blogs with ads use AdWords, yet the AdWords widget accounts for only 75% of all advertising widgets. The degree of overlap can be estimated by how far the percentage totals go over 100%. For example, we can see that 47% of Analytics widgets do not appear alone.

Search
snap.com | 528 | 48.26% |

Trackbacks
technorati.com | 1690 | 92.00% |

Advertising
googlesyndication.com | 2431 | 90.14% |

Analytics
google-analytics.com | 3264 | 56.18% |

*The numbers for Lijit skew high as our search used Lijit users’ blogs as seeds to begin the crawl (Before we had to throw out most of the blog data as invalid.).


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