Implementation and Dynamic Simulation Modeling of ...

Implementation and Dynamic Simulation Modeling of Search Engine Optimization Processes. Improvement of Website Ranking. APOSTOLOS S. SARLIS1, a, IOANNIS C. DRIVAS2. DAMIANOS P. SAKAS3 1,3 Computer Science and Technology, University of Peloponnese, Tripolis, Greece 2 Computer Science & Information Technology, Linnaeus University, Växjö, Sweden a)Corresponding

author: [email protected]

Abstract: In this research paper the authors highlight the importance of Search Engine Optimization of a company’s website in order to improve its visibility in the global ranking of websites. Firstly the authors implement a SEO analyzing tool for the identification of rectifications that need to be done for the augmentation of website’s visibility. In the next step the recommendations that SEO analyzer indicated implemented and completed improving in this way the overall SEO rating. Thereafter, a Dynamic Simulation Modeling process takes place for the estimation of the proper time and way of spending company’s resources for the augmentation of website’s visibility. The model predicted and estimated that the total satisfaction of a decision maker regarding this return on investment is gradually increased as each one of these recommendations implemented in a specific way of resources’ distribution, strengthening the final decision in order to adopt such a digital marketing tool in decision maker’s quiver. Keywords: Search Engine Optimization, SEO, Dynamic Simulation Models, DMS, Website Ranking, Decision Making Tools, Digital Marketing

Introduction The global entrepreneurial environment has already begun to deeply understand that one of the first dynamic steps for introducing the new era of marketing and advertising is taking part on top of the lists in search engines (Yalçın and Köse, 2010). In simplicity, Search Engine Optimization is the process which enables a page to appear in top of the lists of search engines while users typing specific keywords. Alternatively, SEO is a set of techniques and strategies used by web developers to get better indexed by search engines (Gandour and Regolini 2011). In other words, it can be said that even if a website has high quality and quantity of content, SEO process increases its recognition and legibility in the global stage of rankings in a plurality of search engines, otherwise the chaotic mantle of searching results will cover the website. Mutually, the global reduced financial flexibility arises the pressure for companies spending their resources in the right time, with the right quantity, hence with the appropriate return on investment regarding their website ranking. In this paper, the authors proceed in a plurality of sequential processes that embraces SEO techniques and strategies with a dynamic simulation modeling method applied in a website operated in global conference organizing and more specifically in the scientific field of Strategic Marketing. The dynamic actuarial modeling process not only reduced the risk of uncertainty regarding the upcoming resources expenses, but also highlights the percentage of improvement in website’s global rankings after SEO indicated implementa-

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tions. More specifically, at first glance, the authors submitted the aforementioned website to the SEO SiteCkeckUp, a basic free SEO analyzing tool and the results of it indicated several recommendations for augmenting website’s rankings. The analyzing tool indicated six recommended programming changes that increase website’s visibility in the global stage ranking and accordingly these recommendations implemented. After the implementations, simulation modeling process takes place via iThinkTM system software as a model builder on instinctive icons-based and graphical interfaces. Recommendations of SEO Analyzer To begin with, the analyzer indicated an overall SEO score of 52/100, including categories of common SEO issues, speed optimizations, server and security recommendations and mobile usability efficacy. The first error that analyzer indicated has to do with the rectification of Metadata Description that was missing as a tag that provides an brief description of the page that can be used by search engines. The second error related with the Keywords usage as a crucial point that influence the indexing process of crawlers and therefore the identification of the topic of the website by search engines. The third error has to do with the Headings Status as Headings help search engines and crawlers to describe the sub-topic of webpage. Missing Alt Tags-Attributes on Images as the fourth error was indicated. Alt title tags on images strengthen the message towards search engine crawlers augmenting website’s potential accessibility and visibility. The fifth error related with unfriendly URL paths of the website which mostly affect the indexing process of the crawlers. Lastly the final sixth error related with the missing addition of Google Analytics in the website as an important factor that detects the circulation of users on it. Systems Dynamics Modeling for SEO The multidimensional utility of Dynamic Simulation Modeling (DMS) covers not only simulations in the IT and digital marketing sector that SEO is part of. DMS processes also indicate their importance and efficacy to the handling of resources in other topics such as strategic management and leadership (Sakas et al, 2014; Nasiopoulos et al, 2013), or even in business environment in an effort to highlighted the organizational cultural change (Trivellas et al. 2007). In an overall framework, according to Ball (2011) modeling refers in an action of generating a process as an abstract representation of some real world entity or system. To implement the model that encapsulates the expenses of resources regarding the SEO Analyzer recommendations, the modeling software tool iThink 9.0.2, from iSee Systems, was used as a commonly accepted simulator in other studies (Sakas, et al, 2016; Tan et al, 2013). iThink software uses diagrams of tanks and flows to model and simulate in a graphical way all the processes and scenarios, and also represents the outcomes of certain inputs that can be defined by the user of the application. In specific:

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: A Tank represents the conglomeration of physical or either-non physical quantities. For example in this model the Total Satisfaction ROI or Company Resources are some of them. : A Flow represents an activity which fills up or evacuates the Tank. Also the arrow indicates the direction of positive flow into or out of a Tank. : A Converter is responsible for holding the values of constants. The Convertor also serves as an external input to the model or converts inputs into outputs through user-defined graphical functions or algebraic relationships. : The Connectors provide the links-associations between models elements. On the one hand the solid wire is an action Connector, on the other hand the dashed wire is an information Connector. Total Satisf action ROI

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Fig. 1. Modeling the SEO process for the augmentation of search engines rankings

In fig. 1 the dynamic simulation model takes place and enrolls all its functions. To begin with, the blue tank Company Resources and the black Tank Total Satisfaction - ROI constitutes the core values of the modeling process. The first one controls and distributes the available resources and the second one estimates the final satisfaction of a decision maker regarding this investment and the return of it. The other tanks represent the missing points or the errors that the SEO Analyzer tool was recommended and therefore the upcoming spending of company’s resources for the rectification of them. However the important key point of this model related with the Converters which are responsible for the final reckoning of the Total Satisfaction of ROI as they algebraically calculate the possibility to augment the satisfaction. Implementing the Recommendations of SEO Analyzer Figure 2 shows the main user interface of the simulation model. There are two sections on this user interface. Every section represents the % of the resources that provided through sliders in every action.

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Company Resources Controllers

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Fig. 2. Interface of the Dynamic Simulation Model

In the Company Resources Controllers section, the amount of company resources distribution percentage is presented. The available resources are 100 credit points for the improvement of search engine rankings at the website. 20% of credits are distributed for fixing of Headings (CR2FH) and other 20% credits are distributed to the prosthesis of Google Analytics (CR2GA). For the selection of keywords and other suggested rectifications 60% of credit points are spent. The last one distribution is higher than the other two fixings CR2FH and CR2GA and this happened due to the fact that is a process that it needs much more working hours from the SEO specialist. In the Pick Keywords Controllers section, the amount of Pick Keywords Tank distribution percentage is presented. A total of 40% of the available resources need to be invested into fixing the metadata deception Tank, 30% into fixing URLs (into a more user friendly form) and the rest 30% need to be invested into fixing the Alternative Tag of Images. As it can be seen in fig. 3, the implementation of this dynamic simulation model runs for 8 hours. During of 8 hours, all the suggested rectifications that SEO SiteCkeckUp indicated were fixed from the SEO specialist and each recommendation gave a surcharge of the Total Satisfaction of ROI. Therefore during of 8 hours, the blue line (Company Resources) gradually starts to be decreased as more and more resources are invested. However the diagram shows that the black line (Total Satisfaction of ROI) has a gradual and steady augmentation compared with the inversely proportional reduction of Company Resources. 1: Com pany Res ources 2: Fix KP Satis faction 1: 2: 3: 4: 5:

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Fig. 3. Graph of Goals of the Dynamic Simulation Model

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In other words, the decision maker is fully satisfied regarding the way he spent his resources as the total satisfaction for the return on investment has finally highly increased. Conversely if the simulation model predicted and therefore extracted a lower Total Satisfaction of ROI than this one, then the decision maker should be very cautious and mindful for this investment as it can be characterized as a perilous one.

Fig. 4. Table of Goals of the Dynamic Simulation Model regarding the decision maker’s Total Satisfaction of this Return on Investment.

Having always in mind the consistent augmentation of Total Satisfaction of ROI, Figure 4 represents numerically the gradual increase of ROI while resources are spent for each implementation strengthening in this way decision maker’s movements and decisions. As it can be seen, in a period of 8 hours, (from Initial=0 to 7) Company Resources reasonably reduced (8th hour 0.10) while Keywords Satisfaction, Google Analytics and Headings have an augmenting improvement (138.71, 37.31 and 64.52). It is also noteworthy to refer that the low increase of results plus the non-varying situation of ROI in the last 3 hours (5,6,7) is analogous with the minimal spent of resources, as minimum spend of resources indicates low changes and increases. Conclusion and Future Implications In this study the authors firstly ran a SEO analyzing tool for the identification of issues and problems that a website probably has. The analyzer not only ranked the webpage with 52/100 overall SEO rating but also indicated some recommendations for rectification. Secondly, the authors started to rectify each of the recommendation in order to estimate a)the time spent to complete each one b)to estimate the difficulty of each one which is related with the spending time, in order to distribute in a proper way company’s resources while implementing the DMS. After the completion of all the recommendations the authors re-ran the analyzer and SEO SiteCkeckUp ranked this time the website with 62/100 overall SEO rating achieving a growth of 10 points. The third step of this paper related with the construction of a DMS which supports a decision maker’s choice to invest resources for the improvement of company’s website in order to increase its visibility with SEO digital marketing strategies and techniques. The model highlighted not only a proper way to spent company’s resources in the right time with the right distribution of them, but also that total satisfaction of decision maker regarding the return of this investment has increased. One the one hand, the completed recommendations improved website’s

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visibility giving and increment of 10 point in the overall SEO rating. On the other hand the model predicted that if company’s resources will be spent in that way, then the expected result will be the augmentation of satisfaction regarding the investment at SEO ranking improvement plus the minimization of proclivity to take wrong decisions that leads to risky and probably negative outcomes for company. This prototype as a useful decision making tool, provides to decision maker various forms of support such as Switchers and Sliders that facilitate him through the decision making process. In conclusion, this study depicted that the modeling process contributes maximally to manage complexity, making substantiated decisions based on the well-understood and explicitly formulated essentials of the modeled situation. A modeling process which studies and manages the overall framework of on-site SEO improvement needs to be examined as it constitutes a crucial factor for decision makers’ digital marketing promotional success. References Ball, P., (2011) “Dynamic Modelling for Supply Chain Management: dealing with frontend, back-end and integration issues,” by Adolfo Crespo Marquez, in Production Planning & Control. 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. Nasiopoulos D., Sakas D., & Vlachos D., (2013) “Analysis of Strategic Leadership Simulation Models in Non-profit Organizations” Procedia - Social and Behavioral Sciences, Volume 73, pp. 276-284. Sakas D., Vlachos D., & Nasiopoulos D. (2014). “Modeling strategic management for the development of competitive advantage, based on technology”. Journal of Systems and InformationTechnology (pp. 187 - 209) Sakas D., Vlachos D., & Nasiopoulos D. (2016) "Modeling the development of the online conference’s services", Library Review, Vol. 65 Iss: 3, pp.160 – 184. Tan, K.S.,Daud AhmedM., & Sundaram, D. (2010) "Sustainable enterprise modeling and simulation in a warehousing context", Business Process Management Journal, 16, pp.871886. Trivellas, P., Reklitis P. & Konstantopoulos N., (2007) “A Dynamic Simulation Model of Organizational Culture and Business Strategy Effects on Performance”, American Institute of Physics (AIP), Vol.963 Iss.2, pp. 1074-1078. Yalçın N. & Köse U., (2010) “What is search engine optimization: SEO?”, World Conference on Learning, Teaching and Administration Papers Procedia - Social and Behavioral Sciences, Vol. 9, pp. 487-493.