Stuffing Keyword Regulation in Search Engine Optimization for Scientific Marketing Conferences IOANNIS C. DRIVAS1a) APOSTOLOS S. SARLIS2 ALEXANDROS VARVERIS3 1Computer Science & Information Technology, Linnaeus University, Växjö, Sweden 2Computer Science & Technology, University of Peloponnese, Tripolis, Greece 3School of Law, National & Kapodistrian University of Athens a)Corresponding
author:
[email protected]
Abstract: In this study the authors highlight the importance of Keywords in the process of Search Engine Optimization in an effort to increase the global ranking of websites in search engines. Through the usage of tools and indicators the authors proceed into the extraction of appropriate keywords that can be used in websites for the construction of text and content. In addition a dynamic simulation modeling process takes place in order to calculate and estimate the proper distribution of a company’s resources which intends to invest in the optimization of its website for the improvement of the current presence in the digital marketing world. Keywords: Search Engine Optimization, Keywords in SEO, Keywords Stuffing in SEO, Keywords overuse in SEO, Dynamic Simulation Modeling, Decision Making Tools
Introduction For the improvement of websites’ ranking in the global stage of 3w the process of Search Engine Optimization (SEO) constitutes one of the main key players. SEO is a necessary function for providing an easy for users access to the appropriate information (Rehman et al. 2013) as this statement refers to the benefits of SEO practices. SEO can be set under the overall framework of the effort to increase the ranking of a website in search results for given target keywords (Moreno and Martinez, 2013). In addition, Gandour and Regolini (2011) in their study describe SEO as the process of multiple techniques to increase one’s site content, making it more attractive to users as well as crawlers, by implementing changes within the site while focusing the effort on chosen themes and keywords. It can be seen in these two definitions that the presence of keywords have a crucial role in SEO practices. Moreover for Choudhari and Bhalla (2015) Keyword Analysis is the most important part of the optimization and in the same line Al-Ananbeh et al. (2015) point out that appropriate keywords are the first step to build high-rank websites. According to BlueCaribu Company there are more than 932 million websites that include SEO practices information, as 3.5 people per second look up on Google for SEO practices. As to these observations and findings, more and more enterprises adopt SEO processes to their websites for the augmentation of their rankings and therefore their constant presence into the internet digital world. In this paper the authors proceed in a keyword analysis via using specific tools and metrics which indicates the best possible keywords for websites that promote sci-
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entific events such as conferences in the field of marketing. Moreover, the authors proceed into the creation of a Dynamic Simulation Model (DMS) as a decision making tool which estimates an optimal way of distributing company’s resources in proportion with an upcoming total satisfaction regarding this investment. Using Tools and Indicators For the extraction of the appropriate keywords that need to be included onto websites that promote conferences on strategic innovative marketing, SEMrush Competitive Data Tool was used SEMrush gives the opportunity to observe which are the most commonly used keywords for the under examination websites while it indicates the current position of the website if users type specific keywords. Also, this application estimates keywords difficulty level as an indicator that evaluates if a keyword could be ranked well in organic search results in particular keywords as the higher is the percentage the harder is to achieve high rankings for the specific given keyword. Keywords in a webpage also related with the Metadata Description, with Alttags on Images, with the Headings or even with the URL paths of the website. In other words, appropriate usage with the right keywords in the right frequency enables crawlers to index easier the webpage. According to the SEMrush analysis keyword tool, there are more than seven recommended top keywords that websites are using for the promotion of strategic innovative marketing conferences. There are also other relevant keywords related with organizing a scientific conference process such as Proceedings, Registration, Publication Policy, Participants etc. However these relevant keywords can be characterized at least general or even incompatible within the webpage ranking improvement and for that reason they were estimated via SEMrush with high rates of Keyword Difficulty, in particularly more than 70%. Therefore the extracted keywords and the difficulty of them are: strategic marketing conference: Keyword Difficulty:66.98% marketing innovation conference: KD:56.52% strategic marketing international: KD:67.89% innovative marketing: KD:59.73% Anchor keyword (conference’s acronym + conference): KD:~45% conference marketing strategy: KD:53.49% Other relevant keywords: KD:>70% In continuation of the previous keyword analysis it is noteworthy to refer that this process was implemented into Google.com of US database as it has the highest number of URLs displayed in organic search results for the given keywords related with the strategic innovative marketing conferences. As it can be seen in KD remarks some keywords have low level of difficulty less than 55%. Rightly someone could think that using only these keywords in the website is a good way for improving rankings. However, stuffing or over-using keywords is not a process that evaluated positively by crawlers (Connolly and Hoar 2015; Khanna and
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Vivekanand, 2011). For this reason keywords density must be used with prudence by webmasters. Dynamic Simulation Modeling process In this study, a dynamic simulation modeling process via iThink 10.0.2 simulator of iSee Systems was used for estimating the proper way of distributing the resources of an enterprise for the construction of a webpage with the appropriate keywords. The utility of DMS process has already been implemented in other studies that related heavily with the coordination and promotion of scientific conferences for managing and distributing company’s resources (Sakas et al. 2016; Plikas et al. 2015). For the construction of the model iThink software uses stocks and flows, convertors and connectors as a graphical user interface representation. Stocks represent the conglomeration of physical or non-physical re-sources. Flows represent an activity that fills or reduces a stock. Convertors are responsible of keeping values stable or serve as an external input or converting in-puts into results, through user-defined algebraic relations or graphics functions. Lastly, Connectors provide connections and actions between the elements of the model.
Fig.1 Graphics & Elements of iThink Simulator
For the construction of a webpage with proper keywords in order to be ranked well by search engines, an enterprise proceeds to the optimal distribution of resources as they depended from the aforementioned Keywords Difficulty (KD) in global ranking and therefore the time for creating content-text and integrating all the keywords in the website. The model is running for 4 weeks since the keywords have specific lifetime value and due to that fact, after the first month, further research and modifications are necessary. Stuf f ing Flaw
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Fig. 2. Dynamic Simulation Model of the Keyword Investment and the Total Satisfaction Profit.
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In the model, the available resources of the company are being distributed between seven stocks. Each stock represents each relevant keyword among the keywords that the webmasters of the company’s conference website are going to invest (including “Other Keywords” as a stock). The ulterior goal is the raise of the satisfaction points (Total Keywords) of user/visitor increasing webpage visibility and the organic traffic driven to the website in order to have positive ROI. Each Controller, controls the percentage of the resources that company invests to each Keyword. Each Convertor, using a specific algorithm depended on the keywords. The algorithm is based on the KD and the estimate profit according to the available resources producing a unique profit indicator from each keyword investment (profit indicator). The Waste of each keyword is depended solely on the KD and the competitiveness of it. When each keyword fulfills its unique goal, transfers its unique profit to the Total Satisfaction stock. Total Satisfaction stock conglomerates the profit of each separate stock. On the other hand, Stuffing Satisfaction Checker Convertor which is the red convertor in fig.2, checks for any overflow use of any keyword with the proper algorithm depending the search engine. An overflow will cause the dramatic drop of the satisfaction points of all keywords (drop on ROI), since it will affect the total site visibility (Stuffing Flaw Convertor will affect the ROI). Stuffing Switch will put On/Off the Stuffing Satisfaction Flaw Convertor depending the phase of the model implementation. Stuffing switch starts as OFF until the content/keyword implementation is ready and when it is ON it can predict the potential outcome of the investment. Implementation of the model Figure 3 shows the main user interface of the simulation model. It presents the optimum percentage of the resources available in order to have a sustainable model. Company Resources Controllers CR2CMS Controller 0
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Fig 3. Interface of the Dynamic Simulation Model
The available company resources are 1000 credit point. Those credit points are distribute with specific percentage among each stock. This action represents the resources that company invests for each keyword in order to raise the organic traffic of the webpage (e.g. using keywords in metadata description, alt tags on imag-
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es and so on). The resources are being distributed dependently the KD and the goal of the conference’s webpage as the website needs specific and relevant ranking according to the conference action and topic. 1: Company Resources 1: 2: 3: 4: 5:
1000 350 135 135 1447000
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Figure 4. Graphs of Goals of the Dynamic Simulation Model
After the model implementation for 4 weeks, specific results are being presented. As fig. 4 presents, the Total Satisfaction curve (black curve) is rising every time that each keyword fulfills each unique goal. As being expected, Company Re-sources (blue curve) are falling over as the resources of the company are being in-vesting in each keyword. Anchor Keyword (red curve) seems to provide a great amount of Satisfaction points accordingly to the amount of resources that the decision maker invests regarding the KD and the aim of the conference in order to be ranked with this keyword. On the other hand, Strategic Marketing International keyword (orange curve) seems to be the keyword with the minimum profit and with a high rate of KD as well.
Figure 5. Table 1 of Goals of the Dynamic Simulation Model regarding the decision maker’s ROI
Figure 6. Table2 of Goals of the Dynamic Simulation Model regarding the decision maker’s ROI
Figure 7. Table3 of Goals of the Dynamic Simulation Model regarding the decision maker’s ROI
Figure 5, 6 and 7, indicate the amount of resources that are being invested every week and the amount of profit that each stock-keyword contributes to the ROI of rankings in the global ranks. At the end of the 4th week (from Initial=0 to 3), ROI points are 1.445) which translated into organic reach satisfaction. It is also noteworthy to refer that the low increase of results plus the non-varying situation of Satisfaction after 3.5 weeks is analogous to the minimal invest of resources.
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Conclusion and Future Implications In this paper the authors highlighted not only the importance of proper keywords in a conference website that a company has, but also suggested a way of distributing resources for the maximum outcome via using a dynamic simulation model. In addition, the authors implemented a convertor that prevents keywords use from stuffing-overuse as other studies indicate (Connolly & Hoar 2015; Khanna and Vivekanand, 2011). The proper usage of keywords for SEO purposes combined with a dynamic simulation model that predicts the potential outcome of the investment with a certain amount of resources must be placed as an integral part of the total On-site SEO. In conclusion, in this study there was an examination of a crucial point, the keywords utility on SEO. However a holistic implementation of other issues that probably a website has, constitutes a second decisive step that the authors had already start to implement for an overall modeling representation of SEO practices and the benefits of it, as the chaotic mantle of search engine results threatens. References Al-Ananbeh A. A., Ata B. A., Al-Kabi M. & Alsmadi I. (2012) “Website Usability Evaluation and Search Engine Optimization for Eighty Arab University Websites” Basic Science & Engineering.Vol. 21, No. 1, pp. 107-122 BlueCaribu. How big is the SEO Industry on the Internet? – Retrieved from: http://www.bluecaribu.com/seo-industry [Accessed Date: 10/9/2016] Choudharia K. & Bhallab V. K (2015) “Video Search Engine Optimization Using Keyword and Feature Analysis” Procedia Computer Science Vol. 58 691-697 Connolly R. & Hoar R. (2015). Fundamentals of web development. New York, NY: Pearson Education. Gandour A. & Regolini A., (2011),"Web site search engine optimization: a case study of Fragfornet", Library Hi Tech News, Vol. 28 Iss 6 pp. 6-13 Khana, S. & Vivekanand, O. (2011) "Concept of search engine optimization in web search engine" International Journal of Advanced Engineering Research and Studies Vol. 1 Iss. 1 pp. 235-237 Moreno, L. & Martinez, P. (2013), “Overlapping factors in search engine optimization and web accessibility”, Online Information Review, Vol. 37 No. 4, pp. 564-580 Nasiopoulos K.D., Sakas D. P., Vlachos D.S. (2014) “Modeling the Scientific Dimension of Academic Conferences” Procedia-Social and Behavioral Sciences Vol. 147 pp.576-585 Plikas J.H., Nasiopoulos K. D. & Plikas, H. (2015) “Academic conferences promotion process and social media. Modeling of the problem” International Journal of Strategic Innovative Marketing Vol.2 pp. 60-71 Rehman, K., Ahmed K., & Muhammad N. (2013) “The Foremost Guidelines for Achieving Higher Ranking in Search Results through Search Engine Optimization” International Journal of Advanced Science & Technology Vol. 52, p.101-110 Sakas D.P., Vlachos D. S., & Nasiopoulos D. K., (2016) "Modeling the development of the online conference’s services", Library Review, Vol. 65 Iss: 3, pp.160-184
