User Research experience: Interactive design avoids dogmatism and take for granted

Article Description: elaborate on "user classification": How to avoid dogmatism and take for granted.

When I learned about the White Crow's microblog today, I found a sympathetic chord: "The afternoon was asked again:" How many users are you in this product? I don't have a specific answer. Because I really don't care, I only know in the big net buys the crowd to be OK, relative to the age such population attribute I pay more attention to the user's behavior attribute, for instance his net buys the passive and the active proportion, is not likes compares, the average consumption amount, the consumption category, the Internet time, does not have on the microblog. Just a few days ago to see Shimu's blog is also discussing this issue, and talked about some popular user classification methods of questioning, coupled with my work also often encountered some colleagues on the classification of users with popular misunderstanding, so it is necessary to put this question flap to carefully analyze some, Hopefully it will help to correct some dogmatism and take it for granted.

In user research there is a typical dogma is: User classification is to understand the user's premise, no user classification is equal to no user research. This is actually the purpose and nature of user research to understand the wrong. In fact, user research simply does not have the ability to study the "user" itself clearly, this is a impossible mission. Because the user is "human", the person as a species, overall look is an unusually complex system, and specific to each individual, is different, "the world does not have two identical leaves", so the scientific psychology around people to do research for more than 100 of years, until now has not developed a complete system. What's more, in the enterprise a small project, you say you can the user's personality temper, style, emotions and study clearly? It's impossible. Anyone who thinks it is so easy to study clearly is either a fool or a jerk.

So what does user research do? User research can only be in the "user" a large range of the delineation of a small piece to do research, is in the watermelon cut a triangle, taste, eat in. Of course, the location of the triangle is not random cut, but to select the most directly related to the product design of the part of the most direct link-the user and the target product interaction and the psychological process behind the (note: the "interaction" here is not narrowly defined the interaction of the use of behavior, It refers to the interaction between the user and all contact points on the product touch-points. so many people on the understanding of UCD deviation, made a words too literally mistake, that the user-centric is to the user research clearly, the big fallacy, the correct understanding is to study the user and product interaction process. Remember, the UCD method is conceived in the process of human-computer interaction (Human Computer interaction) and human Science (Human Factors), and one of the core methods of these disciplines is task analysis. So a few years ago, Tang Norman wrote a special article, radical, call to return to the "activity-centric design", that is the truth. Of course, we're looking at Mission analysis today, do not narrow the understanding that user research is not narrow enough to only study the task behavior itself, but to include two important extensions: 1 The object of study is not only the interaction behavior itself, but also other behaviors which are directly or indirectly related to the interaction; 2 is not just research behavior, We should also study the user's experience, attitude, demand and the cultural psychological factors behind the product.

All right, look back. User classification. All methods and means should serve the purpose. Whether the user classification is necessary depends on whether it is always beneficial to our users ' research goals. The answer is, not necessarily. Because in many cases, in a specific task scenario, the user faces a specific product, and the behavior does not show an essential difference. How do you understand this problem? First of all, how does "behavior" arise? Any kind of human behavior is the result of dozens of kinds of internal and external factors. In different scenarios, although the types of factors are still so many, but the impact of various factors will change the weight. in the process of interaction between a user and a particular product, it is possible that the product's own characteristics of the user's constraints become the most important factors affecting user behavior, rather than the user's own characteristics, such as gender, age or personality. and because the characteristics of a particular product are unique, it is possible that people with different intrinsic characteristics may be similar in their behavior to the same product. At this point, the value of user research is to observe and discover how users react to these binding factors of the product, rather than to nowhere near to study how to classify people.

Of course, I'm not saying that user classification must not be necessary. In many cases, user classifications are also required. The criterion of judgment is whether there is such a user classification, in which the response of different categories of users to a particular product will show very obvious differences between groups. The reason is very simple, for instance, this category of gender dimension, there may be such a situation, in all play "Angry Birds" in the user, whether male or female, their behavior does not exist a very obvious difference, then should not be sex to the user on the line classification; There may be such a situation, in all playing "Jin dance Group" of users, male and female behavior there is a significant difference, then should be the use of gender as a user classification dimension, the user classification, and then to study the behavior of different categories of users. So in the "user Classification" thing, the terrible is not the classification itself, but dogmatism and take for granted, the terrible is not clear whether there is a need to classify, it is necessary to classify, the terrible is not yet clear which dimension is the most important factors affecting specific behavior, are all gender, Age this general demographic dimension goes fit and mechanically.

Here, the idea has been basically clear. User classification is not an end, but a means to describe and refine the interaction and psychology of the user and the target product as true and accurate as possible. Whether it is divided or not, whether the use of demographic dimension or motivation, personality and other psychological dimensions, should be in the analysis of specific research tasks, based on the necessary preliminary research to determine, so there is no rigid classification pattern. However, at present, some of the existing practice is to engage in a High-profile user classification, engage in persona, play the idea that the user research is done, but also complained that the report was not practical attention. The problem is that in the classification of users of all kinds of superstition, if the user classification from specific products and scenarios, to engage in air-to-air, not to the interaction and psychological insights, how can the product design and innovation have a practical contribution?

The selection of user classification dimensions is a very complex and need to be cautious work. The correct dimension selection is the prerequisite for successful user classification, if the first dimension is chosen incorrectly (for example, because of "take for granted"), then the user classification is certainly invalid, even produces the opposite effect. In fact, any kind of population differentiation dimension, the interaction behavior and psychological impact must exist, the crux of the problem is whether the impact is large enough to have to separate out the user to classify the degree. A popular dogma is to apply the traditional approach of market research, regardless of the product, gender, age, occupation, etc. as the key dimensions. But in fact, in user research, the demographic dimension is ineffective in many cases (not all cases) because these dimensions are independent of the user's interaction with the product, and although they will certainly have an impact on the interaction, the effect is indirect, and because of the indirect, So this effect is weakened in the process of transmission, and may end up being less than 5% of the action.

What other dimensions, in addition to the demographic dimension, can be included in the list of alternatives? Common dimensions include user motivation, user experience and competency level, user personality characteristics (e.g., based on the Big Five personality theory ), the user's lifestyle and values (e.g. through the vals scale), The cultural identity of the user's organization and region (which can be evaluated based on the Hofstede culture model) and the user's attitude to the new technology product (according to Rogers ' innovative diffusion model, the user can be divided into innovators, early adopters, early adopters, late adopters and other types of people. However, in some cases, a more efficient dimension might not be a common dimension, but a dimension that is directly related to the domain of the target product or product and that reflects a particular interaction behavior feature.

Since there are so many alternative dimensions, how do you choose the right dimension when you receive a specific research task? There are two main approaches:

One is "insight" orientation. This refers to the researcher based on their own experience in the target product and product areas of accumulated experiences and thinking, as well as through observation, interviews and other qualitative research methods to understand the user discovered after the impact of the key dimensions of user behavior. This method is strong in depth, and the found dimension may be more striking in nature.

The other is "statistical" orientation. That is, through the quantitative research methods such as questionnaire survey and log analysis, the key factors affecting user behavior are analyzed in quantitative data. These methods are more scientific and persuasive, but the found dimension may be only a factor of the middle layer, not necessarily the essential factor.

In practice, the statistical orientation has higher requirements for organization resources, and the insight method is more efficient. So when resources are available, it is recommended to use insights and statistical methods to first filter out the most likely alternative dimensions by means of insight, and then to use statistical methods to validate, and when resource constraints, it is recommended that you use only insight. Of course the effectiveness of the insight depends on the researcher's own skill, not only the mastery of the ideas and methods of user research, but also the depth of understanding of the target product and its domain, which is called "Kung Fu in Poetry".