Ivan Vasilev
Category: User research

Usability testing

Affinity diagram

In order to continue working on the “FlyUX” project I am going to use a tool called affinity diagram. It was created by Jiro Kawakita (also called K-J Method – after his name) revolutionising the industry of Japan in the 1970. It was used as a management tool for scientists and engineers. The method was really effective for major projects such as construction of a power […]

Note taking

After the usability test has been conducted and recorded it should be watched and notes should be taken. Users are asked about their travel experience and what they are usually do while booking a flight online. They are also asked about their last trip and which were their main problems and the communication channels they used. Afterwards they perform a test with particular goal to book […]

Online survey

Second major thing in the user research process is the so called Online survey. I used “survey monkey” because it is free and provides a good set of tools to create, collect and analyse surveys. With six usual questions I tried to save people’s time and in the same time to take the most of the date they have provided. Design survey 1. When was the […]

Competitive benchmark

To pick 4 top of the line airline websites/ mobile apps and benchmark them is an easy task to do 🇧🇬 Objectives Learn how best-in-class websites and apps solve the problem we are trying to solve Understand the conventions we should follow Highlight best practice that we should emulate and 1. Lufthansa Landing page Wysiwyg – what you see is what you get. This is the […]

Грешки тип 1 и 2 при A/B тестване

Реших да разгледам една доста интересна тема, а именно Error Type 1 and 2 в A/B testing. По подразбиране в статистическото хипотезно тестване нито един тест не е 100% точен: това е защото се разчита на вероятности в експеримента. Когато онлайн маркетолози и учени тестват хипотеза, и двете групи търсят статистически релевантни резултати. Достигнатите резултати трябва да бъдат в рамките на статистическата грешка : обикновено 95%. […]