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User Research

Getting to knoooow youuu... getting to know alllll abouuut youuuu
Last edited 219 days ago by Ashton Coghlan

Why

User research is crucial to building a platform because it provides valuable insights into the needs and preferences of the platform's users. Here are some reasons why user research is important:
Creating empathy: User research can help to create empathy between the design team and the platform's users. By understanding the users' needs and preferences, the design team can create a platform that meets those needs and is more likely to be successful. Additionally, by involving users in the design process, they feel valued and engaged, leading to a better relationship between the users and the platform.
Understanding user needs: User research helps to identify the needs of potential users, which can be used to design a platform that caters to their requirements. By conducting user research, you can gather information about users' behaviors, preferences, and pain points. This information can be used to create features and functions that will meet the users' needs.
Validating assumptions: When building a platform, there may be assumptions made about user needs or behavior. User research can be used to validate or invalidate these assumptions, helping to avoid costly mistakes later on. By understanding user needs and preferences, you can make informed decisions about the design of the platform.
Improving user experience: User research can help to identify user experience issues that may negatively impact the platform's usability. This could include things like confusing navigation or complex user interfaces. By conducting user research, you can identify these issues and work to improve the user experience, making the platform more intuitive and user-friendly.

Qualitative Research

Qualitative and quantitative research are important for building a comprehensive understanding of users. Qualitative research provides rich, detailed insights into users' needs, attitudes, and behaviors, which can inform the development of a platform.
It involves collecting non-numerical data through methods such as interviews, focus groups, and observation. The aim is to gain an understanding of users' experiences, attitudes, and behaviors. Qualitative research is exploratory and allows researchers to gather in-depth insights into users' needs and motivations. However, the findings are typically not generalizable to a larger population.
This is what we’ll be doing for a while:
JTBD stands for "Jobs-to-be-Done," which is a framework used to understand the underlying reasons why people buy or use a product or service. A JTBD interview is a type of user research interview conducted with the purpose of identifying the specific "jobs" that users are trying to accomplish when using a product or service.
During a JTBD interview, the interviewer will ask questions to uncover the user's motivations, goals, and context around the product or service. The goal is to understand not just what the user is doing, but why they are doing it, and what problems they are trying to solve. This information can then be used to develop a better understanding of the user's needs and to design products and services that better meet those needs.
JTBD interviews are typically open-ended and exploratory in nature, with the interviewer asking follow-up questions to dive deeper into the user's thought process and decision-making. The interviews can be conducted in person, over the phone, or through online video conferencing, depending on the needs of the research team.
A bit, once we get meaningful traction:
Usability testing: observing users as they interact with a platform to understand their experience and identify usability issues.
Ethnography: observing users in their natural environment to understand their behavior and interactions with the world around them.
Not for a while:
Diary studies: asking users to keep a record of their experiences over a period of time to understand their behavior and attitudes.
Card sorting: asking users to organize information or features into categories to understand their mental models.
Contextual inquiry: observing users as they perform tasks in their natural environment to understand their goals and motivations.
Never
Focus groups: moderated group discussions with users to understand their perspectives and opinions on a specific topic.

Quantitative Research

Quantitative research can provide statistical validation for hypotheses and help identify patterns and trends in user behavior, which can be used to inform decisions about design and development.
It involves collecting numerical data through methods such as surveys and experiments. The aim is to measure users' attitudes and behaviors in a standardized way. Quantitative research provides statistical data that can be used to draw conclusions about a larger population. However, it can be limited in terms of understanding the "why" behind users' behaviors.
This is what we’ll be doing for a while:
Analytics: analyzing data collected from a platform, such as website traffic or user behavior, to identify patterns and trends.
Not for a while:
Surveys: asking users a set of standardized questions to collect data on their attitudes, opinions, and behavior.
A/B testing: testing two or more versions of a platform to determine which version is more effective in achieving a specific goal.
Clickstream analysis: analyzing user clicks on a platform to understand how users navigate and interact with it.
Net Promoter Score (NPS): a survey-based metric that measures how likely users are to recommend a platform to others.
Once the Metaverse catches on:
Eye-tracking: using technology to track where users look on a platform to understand what catches their attention.

Feed Me!

Qualitative and quantitative research can also feed into each other. Qualitative research can inform the design of quantitative surveys or experiments, providing insight into the most relevant questions to ask. Quantitative research can then be used to validate or invalidate the findings of qualitative research. For example, if a qualitative study suggests that users prefer a particular feature, a quantitative survey can be conducted to determine how many users actually use that feature and how important it is to them.

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