Researchers predict click-through behavior in Web searches

March 11, 2009

In the world of search engines, clicks mean cash, and in a sluggish economy, companies can benefit by maximizing click-throughs to their Web sites from search engines.

Jim Jansen, associate professor of information sciences and technology, Penn State, and colleagues, developed a measurement to gauge with results. They hope this metric will aid companies in optimization and marketing.

"In some sense, this study is a first step in using in the analysis of user-system interactions for Web search data," Jansen said. "This research explores the online behaviors of users so that commercial search engine companies can utilize the data to improve click-through rates by designing more efficient retrieval and ranking algorithms."

Jansen, along with Ying Zhang, industrial and manufacturing engineering, Penn State and Amanda Spink, Queensland University of Technology, used search logs from to find the factors that predicted increased or decreased user click-throughs. They reported their results in the March issue of the Journal of the American Society for Information Science and Technology.

Based on neural network data, the researchers were able to identify nine factors that can help predict future click-through rates, with five having positive effects, four having negative effects and one having no effect. The positive factors were: number of records in a search, sum of listing ranks, mean , browser type and . Negative factors were: number of organic links clicked, rate of vertical type, time of first query and log in time. User intent, whether they were looking for information, to make a transaction or to navigate somewhere, did not have a significant impact on predicting future click-throughs.

"From a practical point of view, the more that a user reformulates the initial query, the click-through will increase, although there may be individual queries where the user clicks on no links," Jansen said.

The researchers used neural networks because they are modeling tools that can capture relationships between input and output. They took results from a Dogpile search engine transaction log and crated input and output values for the neural network.

"Because click-through is based on each user, we grouped the records according to each unique IP address and cookie to determine a single user," Jansen said. "A huge data set was not necessary to train the neural networks because the principle of training is about how to use insufficient data to get necessary relationships between inputs and outputs."

The researchers found that more searchers clicked through early in the day and more searchers using Internet Explorer clicked through. They also found that searchers who clicked through more often, used longer than average queries, modified their queries more than the average searcher and searched for a longer period of time than average. They also noted that those searching on the Web clicked through more than those searching Audio, Video or Images.

Source: Pennsylvania State University (news : web)

Explore further: Ad click-through rate lower than previously thought

Related Stories

Researchers classify Web searches

April 10, 2008

Although millions of people use Web search engines, researchers show that – by using relatively simple methods – most queries submitted can be classified into one of three categories.

US struggles to pinpoint cyber attacks: Top official

March 10, 2009

The United States often cannot quickly or reliably trace a cyber attack back to its source, even as rival nations and extremists may be looking to wage virtual war, a top official warned Tuesday.

Recommended for you

Volvo to supply Uber with self-driving cars (Update)

November 20, 2017

Swedish carmaker Volvo Cars said Monday it has signed an agreement to supply "tens of thousands" of self-driving cars to Uber, as the ride-sharing company battles a number of different controversies.


Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.