Product Design
Data To Visualize the Customer Journey
Company
User Testing (UT)
Categories
Data Visualization
Product Design
Tools
Figma
UserTesting
Live Interview
Role
Lead Designer for experience from concept to launch
Results
Patent awarded for experience
Top performing, popular feature of customers
Reduced time to insights from hours to minutes
Problem Statements
How might we quantitatively visualize the results of qualitative research in order to surface experience insights faster? How might we enrich insights with data captured from Natural Language Processing (NLP), Computer Vision (OCR), and Intent Ontologies?
User Needs
Customers need data that is enriched with sentiment and intent indicators in order to make meaningful connections with interactions.
Customers need to zoom into individual, qualitative research content in order to trust as well as validate aggregate views and extract contributor stories that motivate stakeholder action.
Principles
Natural Mapping
Data relationships should be clear and demonstrate connections between participant, interactions, intent, and sentiment.
Clear Expression
Expressing complex data sets calls for scrutiny on simplicity and the need to reduce information wherever possible.
Actionable Insights
Data signals and related content should be actionable in order to create value for customers.
Continuous Improvement
Design light-weight feedback patterns that enable customers to do their work more efficiently and assists ML training models.
Constraints
Innovate in a System
Create new patterns and leverage existing design system patterns in order to create a familiar, but innovative experience.
Maintain Context
Leverage Progressive Disclosure by using the familiar “drill-down” interaction pattern to help customers easily understand new information.
Technical
Future-proof design to enable more interactive and collaborative features when technical capabilities advance.
Product Research
A comparative approach help set expectations for higher standards and generated new ideas for related experiences.
Explorations & Iterations
Design exploration was a critical aspect of better understanding how our technical capabilities could align with customer needs and expectations.
Evolving my designs from raw sketches and mock-ups to more and more refined visuals helped the team hone in on our research-ready, pre-production design and live prototypes.
Customer Research
Observation
Our team’s lead researcher interviewed customers to gain insight on perceived and real value of the experience as well as points of friction in the flow.
Improve Clarity of Expression
Our aim to visualize all ontologies in one view overwhelmed some users and lacked clarity. We responded by separating sentiment from intent views as well as creating an overview.
Lean Into Actionable Insights
Interactive visualizations that progressively display more detailed qualitative insights enable users to get the right information at the right time. This design was essential to optimizing users’ time.
Production Designs & Outcomes
Interactive Path Flows (IPFs) with sentiment, intent, and interaction overlays were launched to General Audience and Private Beta while I worked at UserTesting and are all now available to General Audience. IPFs continue to be a popular feature that is a differentiator for UserTesting. We applied for and were awarded a patent for this work and feature.
Interactive Path Flows (IPF) & Click Map
IPF charts are Sankey diagrams visualizing participants flow through a task. Below is a sample of the Sankey diagram and related interactions. Interacting with the diagram progressively discloses a Click Map, which visualizes interactions that users take on a website or mobile application. Interactions are listed in conjunction with quick links to video excerpts to watch participants behaviors and listen to their feedback.
Sentiment Analysis
Establishing the IPF foundation enabled our team to integrate Sentiment Analysis insights from Natural Language Processing (NLP) Artificial Intelligence (AI). I designed aggregate overlays to seamlessly add value to our experience.
Intent Overlays
We further enhanced our IPF foundation by integrating Intent Overlays that were enabled via an intelligent ontology. Leveraging the data visualization palette I created was critical to designing an accessible experience. I ensured the effective display of categorical data by limiting the number of categories displayed to the top eight. Prioritizing data display to tell an effective story supports user discovery and improves the analysis experience.
Coaching & Transitioning
Having completed the core IPF experience, including the Sankey Diagram, Click Map, Sentiment overlays, Sentiment bubble diagram, and Intent overlays, I handed-off the experience to a junior designer for her to polish and enhance the visual design.
I coached her on the context of the experience, purpose for the visualizations chosen and how to maintain the integrity of the aggregate view of the qualitative data.
Transitioning and coaching enabled me to focus on designing intelligent feedback loops and search mechanisms for the experience.
