Doing design also need to look at data? Big data is the whole picture for designers

Big data is often associated with technology and the Internet in everyone's eyes, while design is considered by most people to be an art-related discipline. In their eyes, what else is big data but a visualization aspect that can have something to do with design? Many designers never look at data, either because there is no data to look at, or simply do not want to look at it, but also do a good job of design! Design is all about emotion, so why does it have to be about data?

Let's take a look at what the nature of design is.

Design is different from pure art, which originates from the artist's observation and thinking about reality, and the self-expression of such observation and thinking; design is inherently for others to do things, even though the same need to observe and think, but this observation and thinking is not for the expression of the designer's ego, but in order to better serve a certain group of users, and thus the designer to understand the user has become very important. Therefore, it becomes very important for designers to understand users. Especially to understand the user's goals, behaviors, attitudes and other related situations, we are talking about the data is actually the quantification of the user's goals, behaviors, attitudes and other situations, so through the analysis of these data, we can better explore the user's needs, and then provide a better experience for the user.

To put it simply, design is a service to the user, and data is a way to understand the user in order to better design.

Therefore, big data has a role to play:

? Pre-design: data helps you identify problems.

All the research and analysis before the design begins is to get clearer about what the user needs and why this design is being done. From the business point of view, what value does this product have for the company and what purpose does this design serve; from the user's point of view, what value does this product have for the user and what problem does this design solve for the user; in the process of understanding the business requirements and user requirements, we inevitably need to use data, at this stage, the role of the data is to "find the problem" and see how the design can solve it. "

What is the goal of the design?

Of course, in the specific work, most designers are more entangled, both to consider the business requirements, but also to consider the user requirements, if the two can not be completely matched, what should we do, is the sum of the two? Or we just consider the user requirements, the business requirements to see. My personal understanding is that the reality of work we are not in pursuit of the most perfect design, more in the balance, if it is a user-oriented products, such as bias for the user to provide a certain function of the platform, itself is completely from the user's point of view, through the provision of functionality for the user to help the user to solve the problem, it should be more close to the user's request; if it is a business-type products, such as bias for the user to provide certain content platforms. If it is a business-type products, such as biased to provide users with certain content platform, then in order to provide users with the initiative to find the entrance at the same time, can be moderately tilted toward the business development needs, to do a moderate business level guide; of course, this is not absolute, often the same platform, the same product, in different stages of development also have different needs, if it is a brand new product, the survival of the business has become extremely important, this time The design should give more consideration to the business requirements and help the business to survive first, otherwise, the product is going to hang, how to provide services to the users?

Of course, good designers can always find a clever balance between business and users, and find the intersection of the two, for example, if the product is to do this stage of the user scale, and the user demand is to enjoy personalized service, it seems completely irrelevant to the two demands, in fact, we can be completely through a better personalized service to enhance user satisfaction, to get a good reputation, and then indirectly through the user's reputation to enhance the product. Indirectly with the help of user reputation to enhance the user scale of the product, the two are not completely unrelated, more often depends on whether we can find their relevance, to seize the stage of the design goals.

In design: data helps you determine the idea.

Because the personal experience of designers is different, creative thinking is different, so different designers face the same problem, the solution is also likely to vary greatly, even if the same designer will think of different solutions, in the end, which program is more appropriate, in some cases, the data can give you a reference to the views of you to provide you with the "judgment of the ideas ", to assist you in making decisions; all roads lead to Rome, but which road is the most appropriate at present? Many big data-related analysis tools can help such decisions. Big Data Magic Mirror and other new high-quality big data analysis tools for design decisions provide unlimited possibilities.

Through a specific example to see, how to use data to determine the idea? There is a wholesale e-commerce site's channel home page, we found that the user's conversion rate is very low, we went to study the data, and then combined with the conclusions of the user interviews done with typical users, and finally found that the conversion rate of the bottom of the reason is in fact very simple, the channel's home page entrance is mainly derived from the entire site's home page, and the entire site's home page is a full industry category page, the user if the women's clothing industry buyers If the user is a buyer in the women's clothing industry, she clicks on a link from the home page of a whole category to enter another whole category page, and then difficult to find women's clothing in this category, and then click to enter the List page to view the goods, this path is very deep, so how to solve this problem? That is to avoid doing women's users from the home page of the site into this channel after you have to select the women's category again, in order to see the women's goods!

What are the ideas to solve this problem? Can increase the entrance to the home page of the website, so that users directly click on the women's clothing category to enter the channel home page, to show the user women's clothing goods; users can enter the channel home page, according to industry preferences for personalized data to recommend goods, recommended inaccuracies, the user can also go to the customization; in the end, which is more reliable? Two ideas have their own pros and cons, given that the former idea needs to have an external dependency, to change the home page of the site, so we are very much looking forward to the latter idea can run through, but how do we know that this idea is not feasible? First of all, we need to know the industry's personalized recommendations can cover how much of the population, and how many people are willing to customize industry preferences?

For an ordinary website this may be a problem that is not clear enough, but this site is a member of the user has long been over a hundred million class B e-commerce site, with such a large scale of users, high user coverage, which means that the accumulation of data on user behavior, and then class B users have a significant feature is that in a longer period of time, the industry's preference for relatively stable, if a main user of the industry's personalized recommendations, the industry's preference for the industry's personalized recommendations. relatively stable, if it is a buyer of women's clothing, then her preferences will generally be mainly women's clothing, will not go beyond the scope of clothing, at most a small amount of clothing peripheral supporting procurement.

After the design: the data helps you validate the program.

Our design program in the end to do a good job? The standard of measurement is to see whether the design program can achieve the design objectives? This also requires data to quantify, usually with the GSM model to support the validation of the design. G (Goal) design goals, S (Signal) phenomenon signals, M (Metric) measurement indicators, the so-called design goals, is to determine the design to achieve what results to solve what problems; measurement indicators, we can not guess out of thin air, it must be built on the basis of the design goals, first Assuming that the design goals will be achieved, what phenomena or signals will occur? List all the phenomena or signals, choose what we can monitor, and then quantify the phenomenon or signal products, naturally, we get a measurement indicator, but the fluctuation of the indicator is often dependent on experience to set.

For example, the design goal of a certain product is to make more buyers to produce a purchase through the design of the guide, imagine if the design goal is achieved, what will be the phenomenon? There may be more people who have the willingness to buy, look at the product detail page, click the buy button, etc., and eventually also produce a purchase, then, which is the measurement indicator? Design only changes the way of presenting commodity information, and can not change the quality of the commodity itself or the service behind it, so we should focus on examining whether the design strengthens the guidance to enhance the willingness to buy, whether to stimulate the behavior of the user to further understand, mainly refers to the behavior of browsing, the most typical is to arrive at the list of commodities or commodity details page, etc., to quantify the results is to look at the further behavior of the users of the The proportion of users who have further behavior.

The above is what I have shared with you about designing with data?

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