User research: User issues in product design

Description of the problem:

1, the user problem: Through the user test found the problem. There are also "usability issues" on the market, and I have not yet figured out which aspect of focus will be more conducive to product optimization.

2, severity: is the severity of a problem--~ is usually linked to the resolution of the problem, but also the problem of the discovery and problem-solving focus, the beginning of the conflict between the product designer and the developer, or usability analyst and product designers conflict.

In the past few years the actual application process, let me feel that the severity is not only a one-time problem to solve the priority, it should be in the mechanism and design norms complement each other, complementary, updated. It reflects a design team or a product to achieve the design goals of the part, specifically with the user-related part of the use.

So it can be said that the severity of the part reflects that we want the product design team to do, focus on what, and it reflects the design requirements are very basic level, because then down is "user problem"!

The severity of the effect lies in:

And the priority of the problem-solving, so that the measurement of transparency, the meaning of the business unit is equivalent to the KPI definition, easy to target consistent, and in the same language communication;
Let product designers in considering design, can "have the basis" of "rational" "structured", consider the views of users;
OK, after finishing the background, I can safely share some small ideas about how to define severity, just personal thoughts, application please combine local environment ha.

The theoretical definition of severity:

reflect the impact of the problem face
Reflect the extent to which the problem affects the task
Reflect the extent to which the problem affects the product objectives
Using my usual questionnaire design method, around the above three points, combined with Alipay products need to specifically solve the "new use", "inefficient use" problem, the severity of the operation is defined as:

D1 Estimated impact ratio: based on actual sample ratio + product use number to estimate
Impact of D2 on product success Indicators: Product designer settings
Whether the D3 caused the task to fail
Second, the key data to be concerned about:
Ease of learning: first use success rate; puzzles & need help times (users ask or find help themselves); Number of occurrences of a single user
Operational efficiency (baseline required): time, number of operations

Of course, this is only a framework, the weight, indicators and other applications need to be refined, in the attitude of research, I personally prefer the actual data to continue to optimize the program. Instead of the fault based on the design goals have changed, a person's ideas have changed to adjust out. The goal of optimization should be to make the severity of the index more and more sensitive, and close to the research validity. omg--

Wordy repeat again, the key point of this framework optimization is the synergy with product design objectives. So don't think of it as a "user" unrequited product, which is used to guide part of the product design. Must have the participation of product design planners.

Finally attached to my reference to the same product practices, I have not collected enough, the domestic thinking about these details of the abnormal low-key ah.

Reference 1:nielsen: Impact number + impact on user experience size
I. Impact on the user experience (1-3 points)

1, the participants will be upset or frustrated, but will not lead to failure of the mission
2, and task failure has a certain relationship, but will not directly lead to failure of the task. (e.g. detours, impact efficiency and satisfaction)
3, directly lead to mission failure

Ii. Estimated frequency of occurrence (1-3)

Iii. Impact on Business objectives (1-3)

Reference 2:
Number of people affected
Can overcome the number of people
Frequency of individual user occurrences

Reference 3:
P1 stumbling block: Unless amended, will cause serious problems
P2 Heavy impact: Significant impact on website/application availability
P3 medium Impact: Potential for negative impact
P4 Mild impact: unlikely to cause significant impact
Second, the key reference data: The number of people who have problems, the time spent on the issue, the outcome of the problem, the impact of the schedule, the impact on susceptibility, the number of errors, and the overall degree of satisfaction

Original: http://www.iefen.cn/?p=381