The effect of search engine optimization on the search results of web search engines (SEO Effect)
The overall goal of the project is to describe and explain the role of search engine optimization from the perspective of the participating stakeholder groups by analysing search results/search result pages for optimized content as well as quantitative and qualitative surveys of search engine users, search engine optimizers and content providers. Thus the external influence on the results of commercial search engines can be described and quantified for the first time. The project contributes to theory building in information science by extending existing information-seeking models by a component of external influence on the search results.
The project focuses on informative content; it examines how documents that play a role in answering information-oriented search queries can be influenced externally.
We combine methods from computer science (screen scraping, data analysis, machine learning) and the social sciences (experiments, surveys, qualitative interviews).
In the documents, we identified more than 40 indicators for search engine optimization (SEO) that we use in our analyses, resulting in a reliable classification.
Software and datasets
We develop open source software for collecting and analysing results from commercial search engines. We make different datasets with SEO results available.
The project focuses on informative content; it examines how documents that play a role in answering information-oriented search queries can be influenced externally. This sets the project apart from pure questions of online marketing, where the focus is on the optimization itself and not on the consequences for the compilation of result sets.
To measure the effect of search engine optimization, we develop software that can automatically query search engines and analyze the returned results. The results from these analyses are combined with findings from the survey and further investigations of search engine users, search engine optimisers and content providers in order to obtain a comprehensive picture of the influence of search engine optimisation. Methodologically, the project is characterized by a triangulation of methods of data analysis from computer science and social science methods. The interdisciplinary basis of the analysis is unique and will significantly advance the understanding of search engines in general and the influence search engine optimization has in particular.
As a basis for the online survey and the software development we conducted 15 interviews with stakeholders involved in search engine rankings: Search engine optimizers, content managers, and online journalists (Schultheiß & Lewandowski, 2020).
- The interviewees assumed that SEO is hardly known to the users and that the user opinions of SEO strongly depend on their SEO knowledge. We used these assumptions to form hypotheses for the representative online survey.
- The interviews also provided us with valuable clues on how SEO can be identified on websites. We have transferred these SEO indicators into software development.
Representative online survey
We conducted a representative online survey with 2,012 German Internet users to find out how familiar they are with SEO and what attitudes they have towards it (Schultheiß & Lewandowski, 2021a, 2021b). The results widely confirm the assumptions from the interviews:
- Less than half (43%) of Internet users know that ranking improvement is possible outside of ads.
- Only 8% of users are familiar with the term “SEO,” while 13% can correctly name one or more SEO techniques.
- Organic results are associated with SEO by only a small fraction of users.
- With increasing knowledge of SEO, a more positive opinion could be observed.
In a laboratory study with 61 subjects, we investigated how the quality of optimized as well as non-optimized health-related websites is evaluated. We have also classified the website types, looking in particular at commercial or non-commercial motivations. The key results are as follows:
SEO is more often performed by commercially motivated websites, for example pharmaceutical companies, than by non-commercial providers, such as ministries.
Non-optimized websites are attributed the higher expertise by the subjects.
- The subjects justify these ratings in particular with the assumed competence or seriousness of the website operators.
- We developed a multidimensional method for measuring SEO effectiveness and a software tool that detects whether SEO measures have been taken on the URL ( Lewandowski, D., Sünkler, S., Yagci, N., 2021 & Sünkler S., Lewandowski D., 2021a, 2021b).
- For our method, we use a model with n = 48 indicators based on an extensive literature review and the aforementioned interviews with SEO experts (Schultheiß & Lewandowski, 2020).
- An initial analysis of Google search results on three datasets (a total of 1,914 queries and 256,853 results) shows that most of the pages found in Google are likely to be at least optimized, which is consistent with the statements of SEO experts, i.e., it is difficult to become visible in search engines that do not use SEO technology (Lewandowski, D., Sünkler, S., Yagci, N., 2021).
Lewandowski, D.; Sünkler, S.; Yagci, N. (2021). The Influence of search engine optimization on Google’s results: A multidimensional approach for detecting SEO. 13th ACM Web Science Conference, 2021. https://doi.org/10.1145/3447535.3462479
Schultheiß, S.; Lewandowski, D. (2021a): Misplaced trust? The relationship between trust, ability to identify commercially influenced results, and search engine preference. Journal of Information Science. https://doi.org/10.1177/01655515211014157
Schultheiß, S., & Lewandowski, D. (2021b). (Un)bekannte Akteure auf der Suchergebnisseite? Ein Vergleich zwischen selbst eingeschätzter und tatsächlich vorhandener Suchmaschinenkompetenz deutscher InternetnutzerInnen. In T. Schmidt & C. Wolff (Eds.), Information between Data and Knowledge. Information Science and Its Neighbors from Data Science to Digital Humanities. Proceedings of the 16th International Symposium of Information Science (ISI 2021), Regensburg, Germany, 8th—10th March 2021, 218–246. https://doi.org/10.5283/epub.44946
Sünkler, S., & Lewandowski, D. (2021a). Den Einfluss der Suchmaschinenoptimierung messbar machen: Ein halb-automatisierter Ansatz zur Bestimmung von optimierten Ergebnissen auf Googles Suchergebnisseiten. In T. Schmidt & C. Wolff (Eds.), Information between Data and Knowledge. Information Science and Its Neighbors from Data Science to Digital Humanities. Proceedings of the 16th International Symposium of Information Science (ISI 2021), Regensburg, Germany, 8th—10th March 2021, 273–298. https://doi.org/10.5283/epub.44946
Sünkler, S., & Lewandowski, D. (2021b). Ist die Webseite suchmaschinenoptimiert? Vorstellung eines Online-Tools zur Analyse der Wahrscheinlichkeit der Suchmaschinenoptimierung auf einer Webseite. In T. Schmidt & C. Wolff (Eds.), Information between Data and Knowledge. Information Science and Its Neighbors from Data Science to Digital Humanities. Proceedings of the 16th International Symposium of Information Science (ISI 2021), Regensburg, Germany, 8th—10th March 2021, 299–306. https://doi.org/10.5283/epub.44949
Schultheiß, S., & Lewandowski, D. (2020). “Outside the industry, nobody knows what we do” SEO as seen by search engine optimizers and content providers. Journal of Documentation 77(2), 542-557. https://dx.doi.org/10.1108/JD-07-2020-0127
Research data and software
All research data, software and the working papers detailing methods and implementation can be found in the OSF repository, https://doi.org/10.17605/OSF.IO/JYV9Ra. A demo tool is available at http://184.108.40.206:5000.
Funded by the German Research Foundation (DFG – Deutsche Forschungsgemeinschaft), grant number 417552432.
Funding period: 05/2019 - 07/2021