Conversion Rate Optimization of E-Commerce using Web Analytics and Human-computer Interaction Principles : An in-depth Quantitative Approach to Optimization of Conversion Rates

Detta är en Kandidat-uppsats från KTH/Skolan för informations- och kommunikationsteknik (ICT); KTH/Skolan för informations- och kommunikationsteknik (ICT)

Sammanfattning: For an e-commerce business to grow, there are many ways one could try to improve the business in order to gain greater reach and increase sales. One of the main goals of such businesses is to convert as many visitors as possible into customers. Even though many e-commerce businesses already have web analytics tools installed, e-merchants find difficulty in identifying where to start optimizing, what data to extract from analysis reports, and how to make use of such data in order to produce a successful design that will increase the conversion rate. The purpose of this thesis is to (without spending resources on marketing-related factors) guide companies to find a low cost and efficient way to increase the conversion rate by creating well-thought-through designs based on analytic data, qualitative research, and human-computer interaction principles. Google Analytics, a web analytics tool, was used in identifying high-valued pages to optimize and to identify demographics/target groups, while qualitative e-commerce related research was used to shape design-proposal hypotheses. This, along with two A/B tests conducted using Optimizely, is the basis for the guidelines and conclusions. The results of both A/B tests showed an increase in conversions with designs highlighting: evidence of a secure shopping environment, incentives that will attract visitors to buy, and by removing auxiliary navigation elements at the check-out page. The evaluation of the results and its statistical significance was done using both Optimizely’s statistical engine and null hypothesis testing. The increases in conversions were not statistically significant per Optimizely; however, they were significant using traditional statistics. In conclusion, using metrics such as high exit-rates combined with many page views and high revenue-generating pages will allow e-merchants to identify where to start their optimization process. Furthermore, to know what valuable data needs to be extracted, one should seek the data that needs to be inserted into HCI concepts, such as personas and scenarios. This, along with qualitative research allows designers to create well-thought out design-proposals that will potentially lead to an increased conversion rate.

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