A detailed technical comparison of the search engine result pages of any three English search engines. [0158] (original) (raw)

What Users See Structures in Search Engine Results Pages

This paper investigates the composition of search engine results pages. We define what elements the most popular web search engines use on their results pages (e.g., organic results, advertisements, shortcuts) and to which degree they are used for popular vs. rare queries. Therefore, we send 500 queries of both types to the major search engines Google, Yahoo, Live.com and Ask. We count how often the different elements are used by the individual engines. In total, our study is based on 42,758 elements. Findings include that search engines use quite different approaches to results pages composition and therefore, the user gets to see quite different results sets depending on the search engine and search query used. Organic results still play the major role in the results pages, but different shortcuts are of some importance, too. Regarding the frequency of certain host within the results sets, we find that all search engines show Wikipedia results quite often, while other hosts shown depend on the search engine used. Both Google and Yahoo prefer results from their own offerings (such as YouTube or Yahoo Answers). Since we used the .com interfaces of the search engines, results may not be valid for other country-specific interfaces.

Evaluating the retrieval effectiveness of Web search engines using a representative query sample

Search engine retrieval effectiveness studies are usually small-scale, using only limited query samples. Furthermore, queries are selected by the researchers. We address these issues by taking a random representative sample of 1,000 informational and 1,000 navigational queries from a major German search engine and comparing Google’s and Bing’s results based on this sample. Jurors were found through crowdsourcing, data was collected using specialised software, the Relevance Assessment Tool (RAT). We found that while Google outperforms Bing in both query types, the difference in the performance for informational queries was rather low. However, for navigational queries, Google found the correct answer in 95.3% of cases whereas Bing only found the correct answer 76.6% of the time. We conclude that search engine performance on navigational queries is of great importance, as users in this case can clearly identify queries that have returned correct results. So, performance on this query type may contribute to explaining user satisfaction with search engines.

New perspectives on Web search engine research

Purpose – The purpose of this chapter is to give an overview of the context of Web search and search engine-­‐related research, as well as to introduce the reader to the sections and chapters of the book. Methodology/approach – We review literature dealing with various aspects of search engines, with special emphasis on emerging areas of Web searching, search engine evaluation going beyond traditional methods, and new perspectives on Web searching.

Web Search Results Visualization: Evaluation of Two Semantic Search Engines

Semantic search engines improve the accuracy of search results by understanding the meaning and context of terms as they appear in web documents. But do they also improve the presentation of search results? We discuss this research question and attempt to address it by evaluating two semantic search engines: Sig.ma and Kngine. Our analysis is based on the theory and methods of explorative evaluation studies, the inspection evaluation approach in information visualization, user-oriented evaluation studies, and on quantitative data analysis. Our main conclusion is that visualization used in semantic search engines improves the understanding of search results and the overall search experience by exploiting the semantics of web data.

Credibility in Web Search Engines

Web search engines apply a variety of ranking signals to achieve user satisfaction, i.e., results pages that provide the best-possible results to the user. While these ranking signals implicitly consider credibility (e.g., by measuring popularity), explicit measures of credibility are not applied. In this chapter, credibility in Web search engines is discussed in a broad context: credibility as a measure for including documents in a search engine’s index, credibility as a ranking signal, credibility in the context of universal search results, and the possibility of using credibility as an explicit measure for ranking purposes. It is found that while search engines—at least to a certain extent—show credible results to their users, there is no fully integrated credibility framework for Web search engines.

Development of a search engine marketing model using the application of a dual strategy. [0182]

Background: Any e-commerce venture using a website as main shop-front should invest in marketing their website. Previous empirical evidence shows that most Search Engine Marketing (SEM) spending (approximately 82%) is allocated to Pay Per Click (PPC) campaigns while only 12% was spent on Search Engine Optimisation (SEO). The remaining 6% of the total spending was allocated to other SEM strategies. No empirical work was found on how marketing expenses compare when used solely for either the one or the other of the two main types of SEM. In this study, a model will be designed to guide the development of a dual SEM strategy. Objectives: This research set out to determine how the results of the implementation of a PPC campaign compared to those of a SEO campaign, given the same websites and environments. At the same time, the expenses incurred through both these marketing methods were recorded and compared. Method: Article one was based on an empirical field experimental approach. The authors considered the implementation of both SEO and PPC, and compared the results. Data was gathered from Google search results after performing both fat head and long tail key-phrase searches based in various categories. The websites that were listed in the top 10 of the sponsored section of the search results were recorded. These websites were then checked to see if they also had an SEO ranking within the top 100 for both the fat head and long tail key-phrases. The author then researched and produced article two where the active website of an existing, successful e-commerce concern was used as platform. The company has been using PPC only for a period, while traffic was monitored. This system was de-commissioned at a given point, and SEO was implemented at the same time. Again, both traffic and expenses were monitored. Finally, the author proceeded with article three where various successful e-commerce websites, utilising both SEO and PPC, were evaluated on their Cost Per Acquisition (CPA). The CPA for the e-commerce websites was calculated over a set period. Also, the cost over that period for both SEO and PPC was divided by the number of acquisitions achieved by each, and compared. Results: It was found in article one that website owners seldom invest in SEO as part of a SEM campaign. This seemed to confirm some of the findings of other authors. Only SEO and PPC were evaluated, as they are the most used SEM techniques. Possible future research could include investigating other search engines’ PPC systems - Bing and Yahoo!, for example. Article two's results indicate that the PPC system did produce favourable results, but on the condition that a monthly fee must be set aside to guarantee consistent traffic. The implementation of SEO required a relatively large investment at the outset, but it was once-off. After a decrease in traffic due to crawler visitation delays, the website traffic bypassed the average figure achieved during the PPC period after a little over three months, while the expenditure crossed over after just over six months. It was found in article three that the cost per acquisition (CPA) for SEO, for each of the e-commerce websites, was significantly lower than that of the CPA for the PPC campaigns. Conclusion: While considering the specific parameters of this study, an investment in SEO rather than a PPC campaign appears to produce better results at a lower cost, after a given period. This research has important implications for SEO and PPC practitioners, and for website owners. It should influence the way budgets for SEM are applied. Finally, it could be used by marketing managers in better utilising their limited SEM budgets. No evidence could be found that this kind of empirical research has been done before, hence the results are considered to be unique and contributing in a major way to the body of knowledge. Model: As a conclusion, a dual strategy model was proposed. This model should be used in designing a cost-effective SEM strategy, tailored to a specific business. It involves choosing between one or both of SEO and PPC as marketing platforms. The results of the three research articles have been combined and articulated to design this model, which should allow any digital marketer to plan a marketing strategy in a way that will, for a specific situation, reduce costs and increase yield.

The implementation and perception of paid placement schemes in the top three search engines. [0032]

The purpose of this research was to analyse the current top three search engines in order to find a correlation between the implementation of their paid placement or sponsored search result schemes, and user’s perception thereof. An analysis of current literature was done, finding similar work surrounding these topics and also more specific work done regarding the implementation of paid placement results and user perception. Empirical work was then planned and executed in the form of two pilot studies. In the first, the top three search engine result pages were analysed to find how each search engine implemented its paid placement schemes. Some search queries were created and each of these was used and the results noted. The second study took the form of personal interviews - 10 participants were interviewed. Each one was shown the same results page from a search conducted on Google and questions were based on that page. Results from both studies combined with previous work confirmed that users are not satisfied with the level of separation between organic and paid results. Users would prefer more separation between the two sets of results. There is some evidence that search engines are trying to accomplish the opposite as this would benefit the income potential of their paid placement results.