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###### tags: `UX Research`
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# DAOhaus UX Process Sketch

#### 1: ID Users
- Identify user characteristics and types of users:
- DAO summoners
- Boost developers
- etc.
- Frame by adoption lifecycle: taxonomy of users
- Priorizes for user focus

#### 2: Assumptions & Empathy
- Develop assumptions about those users
- Elaborate demographics based on assumptions
- Who they are and what they are trying to do
###### Tool: Affinity & Empathy Mapping

#### 3: Interviews
- Apply user characteristics into an interview script
- Develop a script to in/validate our user assumptions
- Better to give something concrete to react to rather than pulling from scratch - can be conduted async
- Interviews are conducted, data in extracted and compiled, and analyzed for consistency
###### Tool: crafting script, conducting interview

#### 4: Personas
- Refine personas based on real info from those conversations
- Goal: find a signal that we have identified the top 3 problems with that target segment
###### Tool: persona creation based on key characteristics

#### MISSING: User Journey Map
- Stories > Flows > Journeys > Epics > Red Routes > IA

#### 5: Problem Statement
- Prioritize the target segments to reduce problems to core issues
- Craft this data into a succinct problem statment: 1-2 total
###### Tool: 'How Might We' statements to provide constraints

#### 6: Riskiest Assumptions > Hypothesis
- Bold as possible, moonshots, for how to solve our problems
- Prioritize the solutions
- Break them down into assumptions
- What does the user have to do (steps they have to take) in order to realize the value we are imagining?
- What are the *riskiest assumptions* we are making? What are the constraints of our assumptions (this must happen or it will never work)?
- Oriented towards **identifying the MVP!**
###### Tool: Rank Assumptions Canvas allows us to capture and prioritize all assumptions that are put out

#### 7: Experiment
- Create a scenario/stimulous to test user behavior
- Can be analog scenarios
- If we do X (experiment/stimulous), then Y% (metric) will produce Z (behavior/response)
###### Tool: based on the assumptions being tested, but usually a clickable prototype with recorded sessions. Might incorporate audio/video (screen) recording of the testing session. Eye tracking app.
###### Prep: screen recording

#### 8: Extrapolate Results
- Towards clearly articulated learnings that are supported by evidence
- Moving towards new insights informed by these learnings
Tool: Miro/figma board, mapping schemas

#### 9: Iterate the Experiment
- Based on new assumptions
- Alternatively, iterate on new riskiest assumptions