Analysis of web traffic reveals a great deal about the online behaviour of users. The data however does not explain why they do what they do, which is crucially important if marketers wish to act on the information.
Understanding “why people do what they do” typically involves a two stage process — constructing hypothesis or scenarios, and testing those hypothesis. To construct hypothesis, and explore issues and scenarios, marketers often conduct qualitative research, or use techniques akin to qualitative research. To test hypothesis and alternatives, they rely on quantitative research methods, and their website is often the ideal platform for data collection.
A/B testing and multivariate testing allow marketers to test elements (headlines, paragraph text, images, call-to-action buttons, testimonials etc.) on a web page. A/B Testing is used when marketers want to choose between one of two or more versions of a web page. If they are seeking to optimize the elements on the page, multivariate testing will reveal the elements they need to focus on.
Multivariate testing is conducted in a live, controlled environment. The web page is dynamically generated and rotated among incoming visitors so that each gets to see one of the different combinations of elements. Visitors are tracked and their behaviours recorded as they navigate the site, to determine which elements (i.e. independent variables) on a web page make the biggest impact on the site’s performance.
Site performance is measured in terms of a specific objective metric (i.e. dependent variable) such as conversion rate.
A/B Testing (or A/B/C or A/B/C/D testing) is used when the marketer or web designer wants to choose between one of two or more versions of a webpage.
For instance, evaluating different versions of an advertisement or a marketing campaign. Marketers can pre-test campaigns (A/B testing) before they are launched, and continue to evaluate them in real time after they are launched.
It is not only easier to manage, control and execute test programmes on the net; it is also much less expensive. For these reasons, consumer marketing companies may evaluate campaigns on the net before airing them on TV.
Testing can be outsourced easily to analytics service providers such as Google Analytics, by inserting the appropriate code in the test pages.
Google Optimize is a feature-rich A/B Testing facility supported within Google Analytics. As depicted in Exhibit 20.15, this facility, accessed via Behavior and Experiments on the side-menu, is a 4-step process:
Note: To find content on MarketingMind type the acronym ‘MM’ followed by your query into the search bar. For example, if you enter ‘mm consumer analytics’ into Chrome’s search bar, relevant pages from MarketingMind will appear in Google’s result pages.
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