Data Mining in Digital Marketing

2018 ◽  
pp. 44-61 ◽  
Author(s):  
Mahmut Tekin ◽  
Mehmet Etlioğlu ◽  
Özdal Koyuncuoğlu ◽  
Ertuğrul Tekin
Keyword(s):  
Data Mining ◽  
Digital Marketing

scholarly journals Does SEO Matter for Startups? Identifying Insights from UGC Twitter Communities

Informatics ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 47
Author(s):  
José Ramón Saura ◽  
Ana Reyes-Menendez ◽  
Chris Van Nostrand
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Search Engine ◽  
Latent Dirichlet Allocation ◽  
Clustering Algorithms ◽  
User Generated Content ◽  
Digital Marketing ◽  
Analysis Process ◽  
User Communities ◽  
Technique Optimization

In the present study, we analyzed User Generated Content (UGC) to measure the importance of Search Engine Optimization (SEO) for startups. For this purpose, we used several clustering algorithms to identify user communities on Twitter. The dataset contained a total of 67,126 tweets. A three-step UGC analysis process was applied to the data. First, a Latent Dirichlet allocation (LDA) was developed to divide the UGC-sample into topics. Next, a sentiment analysis (SA) with machine-learning was applied to divide the sample of topics into negative, positive, and neutral feelings. Finally, a textual analysis (TA) process with data mining techniques was used to extract indicators related to the SEO technique optimization in startups. The results helped us identify UGC communities in Twitter about SEO for startups and the main optimization indicators according to the feelings expressed in tweets. Our results also demonstrated that Black Hack SEO is not the most relevant strategy of positioning of digital marketing for startups and that, although this strategy is used by the startups, it is predominantly negatively perceived by SEO UGC communities.

Investigating the Factors for Predictive Marketing Implementation in Algerian Organizations

2019 ◽  
pp. 82-115
Author(s):  
Soraya Sedkaoui
Keyword(s):  
Data Mining ◽  
Analytical Methods ◽  
Point Of View ◽  
Digital Marketing ◽  
Adoption And Implementation ◽  
Start Up ◽  
Marketing Implementation ◽  
Structured Questionnaire

This chapter examines and identifies the factors that influence the implementation of predictive marketing in Algeria enterprises. A structured questionnaire was used to collect data from 30 respondents comprised of CEOs of selected enterprises. Some analytical methods were applied to analyze the data and evaluate the point of view of the enterprises with regard to the adoption and implementation of predictive marketing techniques. The major findings of the study indicated that the adoption of predictive marketing requires the relevant tools and software to extract knowledge “data mining.” In addition, the existence of start-up (for analytics) and the level of development of e-commerce and digital marketing in Algeria will undoubtedly encourage the use of these techniques. This chapter also provides some suggestions for further research.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining
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