DATA ANALYTICS 4
Data Analytics
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Discussion 4
The company can pursue several segmenting strategies when using Google Analytics. One of them is using specific reports, ensuring every report accessed identifies with the information one is looking for. This process is easy but challenging to uphold because it requires the company to ensure the campaigns are tagged correctly. The second segmentation approach can be used as a dimension drop-down where the reports allow for segmentation in the report. It is a handy way of ensuring that data can be drilled easily (Lin et al., 2018). The advantage of this method is that it is quick for one segmentation. However, each can resort to sampling and produce a limited number of dimensions with no metrics. It is also challenging to segment several thin, making it a longer process.
The company can also use the report filters to ensure that the data is presented in a tabular way and filter tools are at the bottom. This makes it easier to view data that matches or does not match with each other. The advantage of this approach is that it is quick and easy and can be used even in cases of historical data. However, it is an approach restricted to using one report and cannot be easily shared. The company can also use advanced segments whereby it applies it in cases where there has been a lot of conversion within the company in the previous month (Müller et al., 2018). It helps to enhance the slicing of data differently and using different metrics. The advantages of this approach are that it can be applied to historical data and is flexible. However, it is not all reports that can be segmented. The last segmentation approach is the custom report, whereby different levels of segmentation in a report can be created. This approach’s advantages are that it allows different levels of segmentation and can be shared using the automatic email feature. However, it is also limited in the number of dimension combinations and can only segment using dimensions as opposed to Matrix.
References
Lin, W., Li, X., Yang, Z., Lin, L., Xiong, S., Wang, Z., … & Xiao, Q. (2018). A new improved threshold segmentation method for scanning images of reservoir rocks considering pore fractal characteristics. Fractals, 26(02), 1840003. https://www.worldscientific.com/doi/abs/10.1142/S0218348X18400030
Müller, J. M., Pommeranz, B., Weisser, J., & Voigt, K. I. (2018). Digital, Social Media, and Mobile Marketing in industrial buying: Still in need of customer segmentation? Empirical evidence from Poland and Germany. Industrial Marketing Management, 73, 70-83. https://www.sciencedirect.com/science/article/abs/pii/S0019850117303851