A/B Testing: Optimizing Website Performance

Introduction to A/B Testing

As more and more websites are developed, the competition for internet users is becoming more intense. It has, therefore, become extremely difficult for website developers to get people to a site and direct them to do what is best for the business on the website. Despite the fact that there is massive data on the internet about everything done by all internet users, the data can be harnessed to satisfy the needs of an organization. A/B testing constitute a method of comparing two or more different variations and optimizing a website’s performance using the data. The primary focus of this article will be on how the performance of a website can be improved by A/B testing.

As the thesis will explore the stated objective, it will attempt to solve the following problems that have become common in internet marketing:

1. Monetization is not optimized to for its maximum potential.
2. Users visit wrong places on the internet while browsing.

The A/B testing has become one of the most prominent testing methods as it enables website administrators to find direct data about the actions of its users. A/B can help to improve a website’s performance in various aspects.

Various aspects will be tested in the A/B test, the major aspect that must get tested is the value proposition (Zhu et al., 2013, pp. 320-323).  Many people often think of value proportion as one statement on a website, however, it is beyond that as it should be conveyed the copy, image and various web page elements inclusive of landing pages.

A unique value proposition is a key element to the google search engine. Due to the fact that google process trillions of searches every year equating to billions of searches a day, there is no guarantee that an organization’s web page can be displayed on a topmost section of the page (Kang, Liu, Rexford, and Walker, 2013, pp. 13-24). As the google does not consider what to display on top of its page, the value proposition will be of great significance since it will ensure that an organization’s page appears at the top most of the screen to attract more customers.

The hypothesis is an essential procedure in the A/B test. Therefore it cannot be left out in the study. Hypothesis test help in evaluating the two statements that are mutually exclusive, it is all about determining which statement is best supported by a sample data.  

Pages will be compared by running the experiments on the server and redirect visitors using HTTP 302 redirects as an example. However, if running the experiment is impossible redirects will be performed in JavaScript.

Aspects of A/B Testing

Due to the fact that A/B testing analyses the estimated number of customers of the particular website getting optimized to make a statistical prediction about the group as a whole, the test should be more accurate. The larger the number the more the accurate the test is, it is therefore imperative that the largest number possible to be used in order to enhance accuracy which is the main goal of the test.

Implementation of the A/B testing needs the commitment of internal resources and at a minimum, in some sense, building a team which helps in running and reporting a test. However, while building a team, the following must be taken into consideration. Everyone is on the team, the active team is kept focused (Dulloor, et al., 2014, p. 15).

Like everything else, A/B also has its advantages and disadvantages. The advantages include: it gives early feedback, and low barrier entry (Bao, 2007, pp. 501-510). The limiting factors, on the other hand, are that A/B test bust be subject to the same variables to give feedbacks which are reliable, also, its accuracy diminishes with an increase in the number of variables.

Multivariable refer to a testing hypothesis where multiple variables are modified (Saccenti, Hoefsloot, Smilde, Westerhuis, and Hendriks, 2014, pp.361-374).

Examples of the specific comparisons I could make from the Kaplan Business School webpage and the intention behind them.

Case 1: Having an increase of leads after optimizing the Kaplan Business School webpage

In that case, my hypothesis would be creating a user-friendly website with a click-through menu will improve the conversation between the organization and the website users. The result would be: conversation increased after a new user-friendly website is created.

Case 2: Kaplan Business School webpage wants to increase its CRT by adding text in their call to action button

My hypothesis, in this case, would be: making a text i.e. “Add to Cart” in the call to action button will lead to an increase in people adding items to shopping carts. The result should show an increase in percentage was recorded in CRT by adding the text instead of using image alone.

Maxymiser is one of the software that aids in A/B test. The software is a powerful tool for optimizing customer experience as well as the creation of the sophisticated campaigns. Another powerful A/B testing tool is Adobe Target (Poppendieck, and Cusumano, 2012, pp.26-32). This software offers an intuitive user interface to develop personalized web experience quickly, create the A/B test as well as confidentiality target content.

• Awareness:the main goal at this stage is to show the value of the product or service to consumers (Bagherjeiran, Hatch, and Ratnaparkhi, 2010, pp. 146-153). Educational content is also built at this stage as the merchant build a relationship with the client. The seller should not send content that is not applicable to the client at this stage.  
• Consideration:at this point, the merchant had grabbed the attention of a prospective client and now build a deeper relationship with the customer as the customer get introduced to the products and services as he nurtures them with targeted or contextual content.
• Conversion:this a stage where a merchant convinces subscriber to purchase its products or services. It is characterized with talks about the benefits of products or services.
• Loyalty:here, the merchant retains customers (Koch, 2017). Through loyalty, customers are delighted and with awesome product or service and helpful content. The seller should give meaningful information to the client.

At a glance, According to the study, it can be deduced that websites can be manipulated to suit the needs of an individual or an organization. Besides, addressing the aforementioned problems faced by internet users, this article has described a conversion funnel demonstrating how consumer access and buy products or services.

Reference list

Bagherjeiran, A., Hatch, A.O. and Ratnaparkhi, A., 2010, July. Ranking for the conversion funnel. In Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval (pp. 146-153). ACM.

Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B. and Su, Z., 2007, May. Optimizing web search using social annotations. In Proceedings of the 16th international conference on World Wide Web pp. 501-510. ACM.

Dulloor, S.R., Kumar, S., Keshavamurthy, A., Lantz, P., Reddy, D., Sankaran, R. and Jackson, J., 2014, April. System software for persistent memory. In Proceedings of the Ninth European Conference on Computer Systems (p. 15). ACM.

Kang, N., Liu, Z., Rexford, J. and Walker, D., 2013, December. Optimizing the one big switch abstraction in software-defined networks. In Proceedings of the ninth ACM conference on Emerging networking experiments and technologies (pp. 13-24). ACM.

Koch, O.F., 2017. Nudges as Conversion Funnel Enhancers in Digital Business Models (Doctoral dissertation, Technische Universität).

Poppendieck, M. and Cusumano, M.A., 2012. Lean software development: A tutorial. IEEE software, 29(5), pp.26-32.

Zhu, J., Chan, D.S., Prabhu, M.S., Natarajan, P., Hu, H. and Bonomi, F., 2013, March. Improving web sites performance using edge servers in fog computing architecture. In 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering (pp. 320-323). IEEE.