Understanding users from data--application of data in the revision design of existing products

Yinzidu

Usually, we can through the user interview method to understand the user needs, in fact, designers can also analyze the user survey data and Web page data, and other ways to understand the user needs and users in the use of products encountered problems.

Moreover, the direct contact with the user to understand the demand may only be a case, in order to enhance objectivity, usually through large sample survey, from the perspective of empirical data, further more accurate and objective to find the general needs of users.

In addition, by comparing and synthesizing the qualitative analysis results obtained from the data analysis result and the user interview, the designer can understand the user's real demand from different angles.

From the perspective of research, interactive design, including new product design and the existing products of the revised design of two major categories of business, the author will be divided into two times separately in these two categories of business, how to use the data to understand user needs. This paper mainly discusses the application of data in the revision design of existing products.

Because of the confidentiality of business information, this case used 2011 years of projects, Internet products iterative frequent, the article mentioned in the product page has been revised for many times, we only need to understand the entire article of thought can be.

Actual case

Business Service platform on the line, the smooth development of a period of time, but with the platform of various information proliferation, users began to complain that the original page can not quickly find the right content. This is the time to ask the interaction designer to refactor the page to help users find the information and services they really need.

In the revision design, the researcher unifies the data of several sources to carry on the research, provides the designer the more comprehensive data result, including the page data, the page feedback questionnaire research data, the EDM questionnaire research data and so on analysis result.

1. Access to data through the monitoring page

In fact, the interactive design is more relevant to the page of the number of clicks, through the analysis of these data, designers can see the extent of the attention of each module, but also can calculate the page of the click of the heat map, and then investigate the conversion rate of each module.

The focus area of the user's short-term attention is different from the thermal diagram of the Eye movement experiment, click on the hot map is the user's long-term accumulation of the focus of the application area, on the other hand, also measured whether the interactive design and product planning in line with the original intention, can make important content is smoothly found and effective click.

In this case, the Merchant service platform on the line, do a page buried point, convenient long-term monitoring of page data, such as PV, UV, clicks and so on.

2. How is the page data analyzed?

The method of analyzing page data seems simple, but it is not easy to analyze thoroughly. First of all, if you want to be accurate, it is necessary to clean the background data, to investigate the extreme values, unexplained data is the cause of the specific reasons. Of course, many times in order to save time, but also direct application of background data, approximately as a reflection of the real situation. In addition, with clean data, various metrics can be derived from the underlying data, evaluating and directing the interaction design.

For background data, there are usually four types of analytical methods: aggregation metrics, operational statistics, user based statistics, and path analysis.

--Aggregation metrics

Background behavior data is the advantage of a large number of user use of the aggregation, can be examined indicators are:

The amount of page views over a period of time. The distribution of page browsing for a specific period of time. The distribution of page views throughout the site.

These are the metrics of the raw data, not just the numbers, but the reasons for the data.

Other aggregation metrics include:

the operating system and browser ratios. The client type. New user/Duplicate user.

--based on operational statistics

The most useful indicators may be operational information-related metrics that identify richer user behavior rather than simply counting large numbers.

Some of the most useful indicators are as follows:

the average number of page accesses per operation. The duration of the average operation. The first and last pages of the visit.

--Based on user statistics

The user background information judged by cookie or login information can further aggregate the behavior information of individual users, summarize the behavior information of different users, and count out some indexes, which will play a very important role in understanding users. These indicators include:

Number of

visits. Access frequency. Total site stay time. Retention rate. Conversion rate.

--Path analysis

In addition to general metrics, there are other metrics to understand the user experience. Of course, as with all indirect user research, none of these methods can reveal the behavior of the user "why" in some way, but they certainly help the researcher to narrow down the possibilities of how users are used.

The most useful method in these synthesis methods is path analysis. Path analysis is an analysis of how users browse through the site and find common ways in which they can browse. Path analysis can produce the following results:

General browsing path. Next page.

For E-commerce sites can also have more professional results, such as:

Purchase Path Shopping cart use path

In this case, because the project cycle is limited, the researcher does not deeply analyze the page data of the Merchant Service platform, but simply calculates and compares the clicks of the key module to evaluate the effect of the interaction design. From the data, navigation shop decoration, shop promotion of the number of clicks significantly higher than other modules, but with the expected gap, and combined with questionnaire feedback, some sellers reflect the classification of navigation and the contents of the content is difficult to understand, and more messy, so the need for navigation, classification methods and so on to improve.

3. Page Feedback questionnaire and formal questionnaire survey

Feedback Questionnaire is an informal network questionnaire survey, the content of the study is generally more concentrated, less space, can be adjusted in time with the development of products, easy to find problems and solve problems quickly. The results of the selection of feedback questionnaires are generally not generalized, only as a quick understanding of the product status of the reference, because the users have the intention of feedback is most of the users encounter problems, can not represent the entire user community; A feedback questionnaire is most important for the content of open questions, because these users ' voices can help the interactive designer in limited conditions , to maximize contact with users, listen to users, and then understand users.

Feedback questionnaires are usually hung on the page where the product is relatively obvious, or in the page task to complete the location, or the use of floating bar, and so on, if the product users are relatively subdivided the crowd, and the position of the questionnaire is more obvious, collected more samples, the universality of the data will be better, the results of the questionnaire will be more reference value.

Note, however, that there are a few things to keep in mind when reading a user's opinion:

read from the user's point of view. Focus on the facts. Be in no hurry to conclude. Don't take the FAQ list as a mandatory list. Don't be completely convinced of feedback.

For analysis, researchers can ask themselves the following four questions to better track the user experience.

Who is the

user? What do they want to do? How do they deal with the problem? What's wrong with them?

In this case, the business Service platform in the revision stage, the goal of setting up feedback questionnaires is to collect the user's current products using pain point and improve demand, so that more targeted revision. After the questionnaire design, the questionnaire link is displayed in the Merchant Service Platform page by the right floating bar.

After one months of the feedback questionnaire, the researcher summed up the open questions, and collated the analysis reports as follows:

As a result of business adjustment, the service platform will highlight the third party services, research purposes need to understand the seller of Third-party service attitude and behavior, on the other hand need to understand the seller choice of services, the page layout preferences, choice of psychology and behavior habits, so as to guide the page revision.

Taking into account the issue of the project execution cycle, using the formal questionnaire survey to study the layout of navigation, service classification and so on, in fact, the study of such problems, you can use qualitative research methods, such as A/b test, participatory design, card classification, but in order to save research costs, try to use questionnaires to solve the key problems. As a case, just a kind of introduction, in order to explain that the revision can also be applied to research methods, using data to guide the interactive design.

We can take a look at the key parts of the questionnaire:

Special NOTE: This problem uses the analogy method, set up another similar use scene, to examine the user's usage preference.

Special Note: Network research questionnaires can set options randomly, which in some way avoids the choice due to the fixed ordering of options.

The final analysis of the data, found that the seller of the layout of the trend is more obvious, nearly half of the users like a style.

Sellers tend to classify services from a functional perspective, as shown below:

The points of the same color in the figure are more likely to be the same classification; According to the specific service content of each type of service, the name is given, and the number before the category name represents the sort of the overall reference height. In addition to decoration, the other sort of sorting is not very different. In addition, the ranking of information is related to the source of the sample.

4. Data Guidance Design

--Optimize the layout of home navigation, more close to the sellers shop in the demand

The data shown in the survey above, the seller is more inclined to use the function of the service and Tools division, so the new home according to the function of the layout, the original home on the tool or service, according to the research data show the seller classification preferences, categorized into various categories.

The function category is placed on the left side of the first screen of the page, and all kinds of functions are named and sorted by reference to the research results. At the same time, each function of the display, service and tools as far as possible separately display, but also applied research data.

--Home Add Sellers Tool order list and the latest service module, add seller information, seller experience and Success case module

Through the analysis of product feedback questionnaires, sellers need to grasp the current use of the most and the latest shelves of services, as an important reference for the selection of services; they also need Taobao official based on experience, packaging some services, direct push, but also hope that the service platform can become an exchange of experience, information collection platform.

The research questionnaire designed the corresponding topic to examine, the data result shows these are the demand exuberant module. Therefore, in the revision design, all appear in the first screen, more convenient sellers to choose.

--Optimized service collation at the end of the page

Through the comparison can find that the end of the shop management and marketing promotion of content, naming more clearly, classification more reasonable, also reflects the role of data.

Written in the last

For product research, whether quantitative or qualitative, the final conclusion as long as reliable and effective, will be a powerful guide to the work of interactive designers. In general, qualitative conclusions are used to understand users and products, to provide design ideas, and quantitative conclusions help interaction designers to define the focus and direction of design.

The combination of quantitative and qualitative research methods can produce effective complementarity, in order to excavate user's demand more deeply and produce more scientific and valuable research conclusion.

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