Total-experience testing, or experience testing, is a type of experiment-based testing in which the entire website experience of the visitor is examined using technical capabilities of the website platform (e.g., ATG, Blue Martini Software, etc.). Rather than creating multiple websites, total-experience testing uses the website platform to create several persistent experiences, and monitors which one is preferred by the customers.
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A/B testing, or A/B split testing, is a method for testing two versions of a webpage: version "A" and version "B". The goal is to test multiple versions of webpages (e.g., home page vs. product page) or one specific element that changes between variation A and variation B (such as having a lead form on the left hand side or having it placed on the right hand side), FAQ to determine which version is most appealing/effective. This testing method may also be known as A/B/n split testing; the n denoting more than 2 tests being measured and compared. The data for A/B testing is usually measured via click-through rate or an alternative conversion tracking method.
Nauto, a data platform for self-driving cars, helps make autonomous driving safer for companies who manage fleets of self-driving vehicles. Naturally, its customers would need all kinds of information to sell them on this platform. Nauto has it, packaged into a super-simple ebook whose landing page gives you both a brief contact form and some preview statistics to prove why this resource is so important.
The first helps direct attention to the goal of the page -- for you to fill out the form -- in a way that's unobtrusive and feels less like a chore. The second gives this page an SEO boost (search engines will have more content to crawl) and assuages any worry from folks who need to know more about a piece of content before handing over their information, all while not distracting people from the chat window.