Shulou(Shulou.com)06/01 Report--

This article is about how to quickly build a user model Persona based on data. Xiaobian thinks it is quite practical, so share it with everyone to learn. I hope you can gain something after reading this article. Let's not say much. Let's take a look at it together with Xiaobian.

In reality, very few mature companies, product managers, interaction designers, or user researchers spend time building user models, and I believe there are at least two reasons for this:

One of the main reasons is that building user models according to traditional methods is costly and time-consuming, which is not affordable for ordinary companies and teams.

Another reason is that traditional methods have high requirements for user model builders, especially for user interviews and observations. There are many methods and techniques, many product managers dare not try, some people try and do not get useful information, and then they often stop doing it.

We will try to propose a method for fast user model construction based on user behavior data.

Traditional methods of user model construction

Alan Cooper proposes two ways to build user models:

User model: based on interviews and observations of users, rigorous and reliable but time-consuming;

Ad hoc persona: A quick but biased understanding of users based on industry experts or market research data.

Method 1: Building user models based on interviews and observations (orthodox method)

In Alan Cooper's approach, interviews and observations of users are an important basis for building user models. The complete steps are as follows:

Step 0: User interviews and observations (and other research). Think of the user as a master, and observe the behavior of the master as an apprentice, and ask questions. Collect and study user behavior, environment, conversation content and other information throughout the process to discover user behavior, context and goals. (For example, the user roles of a children's community are roughly divided into four categories: children, mothers, fathers and grandparents, which need to be studied separately)

Step 1: Group interviewees by role. According to the research results and understanding, the users are roughly divided into roles, and the users to be interviewed are grouped according to roles.

Step 2: Identify behavioral variables. List the salient behaviors of each character into groups of behavioral variables. Generally, it includes user activities (behavior and frequency), attitudes (to products and related technologies), abilities, motivations, and skills.

Step 3: Match the subject to the behavioral variables. It's basically labeling each behavior for each interviewee.

Step 4: Identify important behavioral models. A significant combination of behavioral patterns was found among the interviewed users. (For example,"some parents" of children's community products will "closely monitor" their children's activities in the community, while "other parents" will only "occasionally learn" about their children's situation.)

Step 5: Combine the characteristics and clarify the goal. Synthesize/mine user goals and other characteristics from user model behavior details.

Step 6: Check integrity and redundancy. Make up important gaps in behavioral characteristics for each user model, combining user models that share the same behavioral patterns but differ only in demographics into one.

Step 7: Specify the type of user model. Prioritize user models, identifying primary, secondary, supplemental, and negative user models. The primary user model is the main object of interface design. There can only be one primary user model for an interface of a product.

Step 8: Further describe characteristics and behaviors. Describe user models in terms of third-person narratives and select appropriate photos for different user models. At this point, the user model is complete.

Method 2: Build an ad hoc persona

When there is a lack of time and resources to interview and observe users, a "temporary user model" can be established based on industry experts 'understanding of users or demographic data obtained from market research.

The process of building a temporary user model is similar to that of building a user model, except that one of the data bases comes from interviews and observations with real users, and the other comes from understanding users. There are differences in accuracy and precision between the two.

Method for quickly and iteratively constructing user model based on user behavior data

It has been almost 20 years since Alan Cooper*** proposed the concept of Persona. During this period, the process approach to software product development and the way companies operate have changed a lot: agile development methods characterized by rapid iteration have replaced the traditional waterfall model, and lean entrepreneurship methods centered on the feedback loop of "development → measurement → cognition" have gradually influenced and changed the way companies operate.

However, the traditional user model construction method has not changed greatly since its birth. For product managers and interaction designers accustomed to agility and speed: on the one hand, spending a long time studying users to build user models requires considerable determination and effort to obtain the time and resources required; On the other hand, the time spent on cold start-up of Internet products is getting shorter and shorter. In order to reduce costs and risks, product teams often choose to push products to users as soon as possible during the start-up period and get feedback as soon as possible to "quickly try and make mistakes." Reality and pressure force most new product PMs to not invest a lot of time and energy in user research. It's easy to understand why user models are considered good, but few people actually use them at work.

Next, we propose a lightweight method for fast, iterative user model building based on user behavior data.

First, at the beginning, collate and collect any knowledge, experience, and data that has been acquired about the user.

They may be your understanding of users and your team, or user-related information recorded in your product's business database (such as user gender, age, level, etc.), or any form filled out or information left by users (inside and outside the product)(such as questionnaires filled out by users, WeChat accounts left behind, etc.).

You can map this information into user description information (attributes) or user behavior information, and store it to form a user profile (the final result is shown in the figure below).

Note: From this step, you need a database system that stores user information and user behavior information, which can support you to quickly carry out various analysis and exploration until the user model is formed.

Then, users are grouped according to the acquired knowledge and experience, and these user groups are the basis for further research. For example, if you think users can be divided into four categories: children, mothers, fathers and grandparents, or if you think shopping users can be divided into two categories: men and women, then divide them according to the data.

Next, you'll analyze each of the user groups from the previous step and try to discover significant patterns of behavior.

For each user group, the analysis steps are as follows:

Randomly select some users from the user group (generally according to your time situation, you can select dozens to hundreds of users, and it is recommended that at least 30 users be selected);

Interpret the attribute characteristics and behavior records of users one by one, try to restore the user's real use scenarios and processes through these data, and try to speculate on their goals. As you interpret, keep track of interesting behavior patterns and puzzles you find. (Note that this step is critical, and the perception of users and their behavior is the basis for subsequent work.)

According to the typical behavior patterns, scenarios and target speculations found in the above steps, the user group is divided into more detailed segments. For example, if you find that some users regularly purchase large amounts of office supplies (interesting behavior pattern), and speculate that these people may be the procurement personnel of the enterprise administrative department, they have to complete the procurement tasks (scenarios and goals) according to the needs of other employees on a regular basis, then you can divide this group of people as a single user group (candidate user model) for subsequent research.

For the candidate user model (user group) formed in the previous step, perform statistical analysis on its attribute and behavior data to preliminarily verify your guess.

Next, for each candidate user model formed above, the inference of its goal and motivation is further completed. Also, if there is any confusion in the process, please record it.

Select a small representative number of users from each user model and conduct interviews or surveys to eliminate the confusion you encountered in previous research. In this step, if you have enough time and resources, you can select more users and do on-site interviews and observations as much as possible; if you have limited time and resources, you can select fewer users, or complete interviews by telephone, questionnaire, etc. For users with high cooperation, you can consider using tools such as screen recording or QQ remote assistance to observe the real behavior of users. Because you already have some insight into the actual behavior of users in the previous steps, you can save a lot of time and resources by not strictly following Alan Cooper's user research method in this step. However, unless there are special circumstances, please try not to skip this step. Remember: even a small amount of communication with users can help uncover unknown problems, which is well worth it.

Once you've done that, you're ready to review and refine the candidate user models one by one. Combine similar ones, supplement incomplete ones, describe each user model in narrative form, and select appropriate photos for them, so as to obtain the user model of this iteration (as shown in the following example, the picture comes from the network). You can use this model to guide interface design, communicate with your team...

Finally, based on your cognitive changes and product needs, you can make a new round of corrections to the previously obtained model at the right time. The process of correction is the same as before, and you may have several iterations of the user model interspersed between product iterations, the longer the user model gets, the closer it gets to the real user situation.

The above is how to quickly build a user model Persona based on data. Xiaobian believes that some knowledge points may be seen or used in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.