As a Interactive designer, I always think about how to make a good product( website or software) that people want to use it for their life. The first thing we should think about why people want to use your product. It seems you need to know the state of most users’ mind. So we need to collect a lot of data so that we can get the points for users’ needs. Then, the second thing is how to use this data effectively. If you want to create a excellent product, you need to find out user’s insight from the data you collect and understand it so that you can use it in you design.
In the past, many people think the design is a perceptual work. It is totally wrong for the designer. Because the product you design need to be satisfied with most users, the designer need to analyze the data in a rational way. Thus, let’s talk about some methods that interactive designer can use and understand the data effectively.
Qualitative and Quantitative:
Quantitative data is data that is in the form of numbers, or that can easily be translated into numbers. For example, the number of years’ experience the interviewees have, the number of projects a department handles at a time, or the number of minutes it takes to perform a task. Qualitative data is not expressed in numerical terms. For example, qualitative data includes descriptions, quotes from interviewees, vignettes of activity, and images.
For this part,I would like to share a very good link:
A/B Testing:
A/B testing (sometimes called split testing) is comparing two versions of a web page to see which one performs better. You compare two web pages by showing the two variants (let’s call them A and B) to similar visitors at the same time. The one that gives a better conversion rate, wins!
All websites on the web have a goal — a reason for them to exist
eCommerce websites want visitors buying products
SaaS web apps want visitors signing up for a trial and converting to paid visitors
News and media websites want readers to click on ads or sign up for paid subscriptions
Every business website wants visitors converting from just visitors to something else. The rate at which a website is able to do this is its “conversion rate”. Measuring the performance of a variation (A or B) means measuring the rate at which it converts visitors to goal achievers.
In conclusion, you can use many kinds of methods in your process of data analysis. The main point is you need to exploit the users insight and transform this information to consideration in your design. The designer need to know the important thing is users’ habit. Effectively use the data and rationally analysis the data will help designers make a excellent product(website or app…)
