Data Experiences Study
How might we create a
successful data experience?
Context:
UX Researcher @ Granicus
Contributions:
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Aligned stakeholders
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Authored research plan
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Recruited participants
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Conducted research methods
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Analyzed data
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Presented findings
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Facilitated workshop
Problem Space
GovQA is a Granicus product that supports government staff in managing public records requests.
Within GovQA, government staff use a suite of data display features, Views, Reports, and Dashboards, to monitor public record requests and staff activity. However, the purpose of these features was often conflated. Users also found them difficult to use, often lamenting this frustration in support tickets and feature enhancement requests.
Methodology
Ethnography
Ethnography is a research approach conducted in participants’ natural environments. The goal of ethnography is to gain a holistic understanding of a group’s shared goals, motivations, needs, and wants and how those affect interactions with each other and artifacts.
Methods
Adjacent Product Analysis
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What: A review of products in the data processing / visualization space and in the products public records
request space. -
Why: To help establish functional requirements, performance standards, and with ideation.
Guided Tours
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What: Touring project-relevant spaces and activities experienced by participants, who act as the guide.
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Why: To become grounded within the natural context of use and familiar with participants' intentions and motivations regarding data.
Interviews
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What: Semi-structured, individual interviews.
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Why: To delve deeper into specific insights from the guided tours.
Secondary Research
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What: Analysis of support tickets, feature enhancement requests, and help documentation.
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Why: To support the insights gathered from the guided tours and interviews and connect them to
larger themes.
Insights
The insights were synthesized into user requirements. The user requirements were accompanied by affirmative statements of what the solution needs to meet said requirement.
The solution needs...
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Meaningful configuration
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More error prevention
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More automated quality assurance
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More transparent system mechanics
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To encourage a culture of data integrity
Workshop
Stakeholders, including the Product Manager, Product Owner, and Product Designer, were convened in a workshop to action the findings of the Data Experience study.
Outcomes
The findings from the Data Experiences study helped inform four concepts for the coming year's product
development roadmap.
Reflections
While the workshop was successful in facilitating ideation, the scope of the workshop was too large, which, coupled with the newness of it, overwhelmed participants. In future workshop iterations, borrowing from Design Sprints, the focus should be narrowed to target the highest-risk or the highest-reward aspect of the experience.