USE OF WAVELET TECHNIQUES IN THE STUDY OF INTERNET MARKETING METRICS

Year 2019, Volume: 20 , 157 - 163, 16.12.2019

Murad Omarov , Tetiana Tykha , Vyacheslav Lyashenko

https://doi.org/10.18038/estubtda.656034

Abstract

Generalized set of classic metrics for evaluating internet marketing. Existing approaches to analyzing Internet marketing metrics have been noted. The application of the wavelet analysis technique for the study of Internet marketing metrics is proposed. Wavelet coherence was chosen to unveil the ideology of using wavelet analysis techniques to study Internet marketing metrics. A comparative analysis of Internet marketing metrics on different queries based on wavelet coherence is revealed. The merits of using a coherence wavelet are exemplified by an example of a basic internet marketing metric - clicks per request. The possibility of visual analysis of Internet marketing metrics using wavelet analysis technique was noted. Specific examples of the use of coherence wavelet for analyzing Internet marketing on specific queries are given

Keywords

Wavelet coherence, Internet marketing, , Click

References

• [1] Omarov М, Tikhaya T, Lyashenko V. Internet marketing technologies in civil engineering. Int J Civil Eng Tech 2018; 9: 1233-1240.
• [2] Tsai YC, Cheng YT. Analyzing key performance indicators (KPIs) for E-commerce and Internet marketing of elderly products: A review. Arch Gero Geri 2012; 55(1): 126-132.
• [3] Saura JR, Palos-Sanchez P, Cerda Suarez LM. Understanding the Digital Marketing Environment with KPIs and Web Analytics. Fut Int 2017; 9,76.
• [4] Gregory GD, Ngo LV, Karavdic M. Developing e-commerce marketing capabilities and efficiencies for enhanced performance in business-to-business export ventures. Ind Market Managem 2017.
• [5] Chen YYK, Jaw YL, Wu BL. Effect of digital transformation on organisational performance of SMEs: Evidence from the Taiwanese textile industry’s web portal. Int Res 2016; 26(1): 186-212.
• [6] Järvinen J, Karjaluoto H. The use of Web analytics for digital marketing performance measurement. Ind Market Manag 2015; 50, 117-127.
• [7] Yang Z, Shi Y, Wang B. Search engine marketing, financing ability and firm performance in E-commerce. Procedia Comput Sci 2015; 55, 1106-1112.
• [8] Ainin S, Parveen F, Moghavvemi S, Jaafar NI, Mohd Shuib NL. Factors influencing the use of social media by SMEs and its performance outcomes. Ind Manag Data Syst 2015; 115(3), 570-588.
• [9] Anand N, Grover N. Measuring retail supply chain performance: Theoretical model using key performance indicators (KPIs). Benchmark Int J 2015; 22(1): 135-166.
• [10] Katsikeas CS, Morgan NA, Leonidou LC, Hult GTM. Assessing performance outcomes in marketing. J Mark 2016; 80(2): 1-20.
• [11] Farris P, Bendle N, Pfeifer P, Reibstein D. Marketing metrics: The manager's guide to measuring marketing performance. FT Press 2015.
• [12] Phillips P, Zigan K, Silva MMS, Schegg R. The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis. Tourism Man 2015; 50, 130-141.
• [13] Tomás R, Li Z, Lopez-Sanchez JM, Liu P, Singleton A. Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide. Lands 2016; 13, 437-450
• [14] De Georgia MA, Kaffashi F, Jacono FJ, Loparo KA. Information technology in critical care: review of monitoring and data acquisition systems for patient care and research. Sci World J 2015.
• [15] Dadkhah M, Lyashenko VV, Deineko ZV, Shamshirband S, Jazi MD. Methodology of wavelet analysis in research of dynamics of phishing attacks. Int J Advan Int Paradim 2019; 12(3-4): 220-238.
• [16] Torrence C, Webster PJ. Interdecadal changes in the ENSO-monsoon system. J Clim 1999; 12(8): 2679-2690.
• [17] Grinsted A, Moore JC, Jevrejeva S. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geo 2004; 11(5/6): 561-566.