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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 5, 2017.
Abstract: The predictable values that indicate the performance of any company and determine that how well they are performing in order to achieve their objective is referred by the term called as “key performance indicators”. The key performance indicator techniques and other methods that are similar to KPI are usually implemented in the businesses that are running online, but for an e-commerce business, it is always difficult to select the right KPI. As long as the KPIs are concerned, the biggest blunder that an online business can make is that they calculate everything along with the KPIs. But whatever they are calculating cannot be referred as the “key” because they are measuring each and everything, so this can immediately become devastating. The need is to only measure certain specific keys in order to calculate the performance of a business. The main aim of this research is to establish the set of standard rules that must be adopted in order to identify the best KPIs for an e-commerce business website based on google analytics and machine learning technique.
Haris Ahmed, Dr. Tahseen Ahmed Jilani, Waleej Haider, Mohammad Asad Abbasi, Shardha Nand and Saher Kamran, “Establishing Standard Rules for Choosing Best KPIs for an E-Commerce Business based on Google Analytics and Machine Learning Technique ” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080570
@article{Ahmed2017,
title = {Establishing Standard Rules for Choosing Best KPIs for an E-Commerce Business based on Google Analytics and Machine Learning Technique },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080570},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080570},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Haris Ahmed and Dr. Tahseen Ahmed Jilani and Waleej Haider and Mohammad Asad Abbasi and Shardha Nand and Saher Kamran}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.