User research requires comprehensive and integrated understanding and analysis

　　How to understand users and requirements

　　1. Whether it is useful to users is the basis of all products, and the rational design process begins with understanding users。

　　There is an environmental basis for availability, high heels are available for PROM and not for tennis, for women and not for men;Only a deep understanding of the user and the context of use can determine whether useful, and turn useful into easy to use。

　　2, there are many ways to understand users and the environment, the most common is "data analysis"。

　　In the early IT industry, everyone called it "database marketing", Walmart has a "beer and diaper story" is a classic case of success, which reflects the huge business value of professional data mining。

　　3. Nowadays, many enterprises pay more attention to data analysis。

　　As far as I know, every page of the portal site is buried with data statistics code;The click-through rate and operation of each location on each page are detailed records。

　　For example, a registration interface: "How many users come in, how many registration success rate (conversion rate)", "how many users make mistakes", "How many users fill in the degree of detail", "how many users leave directly, how many users leave after experiencing setbacks, where there is what kind of frustration to leave" and so on

　　4. The mining and analysis of these massive data are of great value and guiding significance。

　　However, this kind of analysis and mining also has its own defects that are not perfect and not really accurate, because many unexpected factors can easily cause the deformation of data, and often data analysts are not necessarily aware of these unexpected factors。

　　For example, a button that should not be placed in a certain position, a picture that should not be so large, may cause a high number of clicks because of the obvious location and large area, then we can not get the correct conclusion through the results of the data。

　　5, really through contact and communication with users and then get the data, is an effective supplement to mass data mining。

　　The means of this practice can be more diversified: often we will take some of the prototype design to let users try, or give users similar products to let them use, the designer observes what the user does, so as to get design inspiration and ideas。

　　It's a way for designers to "see" for themselves;For example, to design a tool for opening wine, you can observe how the user is now opening wine, and then you can also give the prototype of the tool you designed to the user to use, and see how he uses the tool you designed。

　　In many traditional research methods (mostly in market research), many users will be asked to fill in a designed questionnaire or do telephone surveys, street interviews, face-to-face user interviews and tests, and then make data statistics。It's a way for users to "say";For example, to design a public phone booth, you can interview citizens on the street to collect their complaints and opinions about the existing phone booths and how they usually make calls from the phone booth。

　　Of course, we also often try to find out how users are thinking, and understand the MAP in the user's head。For example, if we design a round door handle that needs to be unscrewed, we can show the design to the user and ask him, "Seeing this round handle, how do you think it should be used to open the door?"。

　　6, sometimes we often do empirical analysis according to the attributes of the user group。

　　For example, statistics (or summative simulation) of the basic attributes of the user, analysis of the user's learning ability and use habits, etc., "education" on the number of computer degree, "age", "professional", etc., are also very useful reference basis for design。

　　7, the above mentioned means are some of the most common low-cost practices, of course, there are some rely on instruments。

　　However, at present in the country, I personally think that these expensive instruments can not play too much real role for most enterprises, or they are just a gimmick, performance.

　　8. In the previous paragraph, when talking about user research with a friend at Yahoo USA, she mentioned some interesting practices。

　　比如，In the reply to the last post someone talked about "approaching customer service"，Some of their late-stage user studies in Panama have people working with customer service to observe and record their work，They also try to answer hotlines themselves;Often, customer service personnel submit data to the data department after screening out data that they consider unimportant，The data submitted to the designer by the data department may have been sifted through again;And their selection principles and judgment may be very different from those of a designer.)

　　Another example is，Record the entire activity of an ID on the site，See how this ID is registered，Where did you go, where did you go, what did you do in the process，Record the user's real interaction trajectory，To adjust the design of "user operation flow";(This data is more realistic than mass analysis，More efficient and less costly than user-by-user interviews。But "privacy" concerns need to be taken into account)

　　It is also worth trying to get users to actively describe how they want to feel about the product in the way they are used to;For example, I mentioned once before the example of McDonald's taking the initiative to understand its users。

　　9. In general: relying on massive data statistics of the current situation may not be able to truly present the real situation, and relying on point-to-point interviews may not be able to comprehensively reflect the overall situation。

　　10, designers want to in-depth understanding of users and needs, the first premise is:

　　1> 通过各种方法走近用户，把用户当作老师；

　　2> 想方设法拿到一线数据，把数据当作可以淘宝的垃圾堆。

　　11. Data is not a gold mine, and users are not always right。

　　A lot of data and user feedback is useless and can even lead to misleading design。In the end, it requires rational analysis and sound judgment。 (So the Ueds I admire most are the "data analysts")