Overview
Process
Research Planning
Research Questions
Discover & Define Phase
Conduct qualitative research
Desk Research & Recruitment
Recruitment criteria: Startup employment status, experience in data collection planning, level of expertise in data, Etc.
In-depth Interviews (12 people)
Conduct interviews in-depth understanding of data taxonomy design pain points
Thematic Analysis
Derived through the process of transcription, in-vivo-code, and theme grouping.
6 Key Findings
The Role of UX Designers in lean startup environments without data experts
They actively participates in the process of selecting key indicators and designing data collection, and leads communication.
It is difficult for a beginner to select key indicators.
They want to know service usage patterns by collecting important indicators according to the funnel, but they are not sure which data to select when selecting indicators or whether there is more suitable data.
It is necessary to discuss priority and naming before designing data collection.
Communication with other teams is essential for selecting important indicators for each service/team and tagging events.
Determining the scope and level of detail of data collection
It is most difficult to determine the scope of data collection and the degree of detail, and to design it structurally/extensibly according to the type of event data.
They ponder how to learn about data collection.
It is easier to apply to actual services by referring to services that have similar user behavior patterns rather than learning and applying theories one by one, and efficient because it can increase the understanding of internal team members.
Resource Limits for early Startups
Because startups often have limited time, personnel, and resources, it is important to first utilize free tools and carefully consider the scope of data collection so as not to interfere with the development of the actual service.
Design Phase
Ideation Workshop
The most efficient form of solution to solve the major pain points is a tool
The flow should be able to follow steps according to the 'flow of time'
Solution
Set the design direction
Summarized all the previous research results and set the design direction.
Design for Key Scenarios
After selecting a key scenario, designed the information architecture and UI structure.
Define goals & set priorities with hypotheses
It's organized in chronological order so that users can simply follow the flow and set up their goals and hypotheses setting steps.
In the recommended goals section, users can see goals that are commonly used.
Hypotheses are inputted while reviewing reference data for each added goal and these can be used for team communication.
Select defined goals and define each step as a funnel.
It is possible to refer to recommended funnels according to service type.
If six or more funnel steps are selected, a suitable data collection range will be proposed.
Selecting indicators while checking goals
When selecting indicators, one can filter by tools or domains to be used, one can refer to a discussion history.
When selecting the extent of collection, it is divided into three stages and one can choose how detailed they want to collect data.
Recommended properties are provided to show an appropriate range.
In addition, if the collection structure has been set in the settings, the naming of properties and collection structure will be automatically set.
Gather Feedback
Conducted a utility assessment to assess whether the data collection design tool,
which is the result of this study, is useful for target users
Utility assessment
Received an average score of 4.6 out of 5, indicating a high overall level of usefulness.
The scores for suitability and efficiency received relatively low scores of 4.3 and 4.1.
Limitations and direction of improvement
Received feedback that it needed visual improvements and additional clarification.
It is necessary to evaluate the effectiveness in actual collaboration situations.
There is a need to further expand the scope of this study to include data analysis and A/B testing to provide a more comprehensive approach to data collection.
Summary
This study identified the problems that UX designers face when collecting user behavior data in lean start-up environments without data experts.
It proposed a tool to assist with data collection, which received positive feedback from target users, to help efficiently collect meaningful data in such environments.
