The Role of UX Research in Government Digital Product Management

When adopting a product management approach to managing digital services at federal agencies, the first step is typically a realignment of IT Projects into Products or Product Lines. This is often followed by a strong focus on agile processes and setting up a modern DevOps infrastructure supported by a culture of continuous delivery.  These are great—and critical—steps in the product management adoption journey.  But they are only part of the product management process. 

As I wrote in my last blog post, a product mindset aligns government digital service delivery teams to create government products that deliver value by being:  

• Desirable – digital products that customers and users want and need.  
• Usable – digital products that support user goals and allow users to quickly and accurately complete tasks. 
• Feasible – technical solutions that are both innovative and feasible, given available technology, time, and budgets. 

What we often do not see during the early phases of adoption of the product management approach is a focus on understanding user needs to create desirable and usable digital services for citizens and federal employee end users.  This is where discovery and continuous engagement with end users comes into play using Human Centered Design (HCD).  The HCD discovery and user engagement process is commonly referred to as UX research or user research. 

The key to meaningful UX research is engagement with real, representative users—and not only product owners, business stakeholders, and technical leaders.  At RIVA, our UX research process begins with baseline discovery. Throughout this post, we will detail RIVA’s approach to UX research and initial discovery. 

Baseline Discovery Methods to Uncover User Needs 

RIVA’s method for creating great digital product user experiences (UX) starts with gaining a complete understanding of the end-to-end customer experience (CX). By looking at processes as a holistic non-digital and digital service, we examine the end-to-end experience from the perspective of the people involved. Our UX researchers use a mix of qualitative research (user interviews, contextual inquiries, and task analysis) and quantitative research (digital analytics, surveys, system metrics) methods, which help us understand the “what” and “why”.  The following is an overview of some of RIVA’s most common baseline discovery UX research methods. 

User Interviews 

We find that nothing beats spending time with real, representative users of services and systems to gain an understanding of their work, workflows, pain points, and opportunities for improvement. The key to conducting successful user interviews begins with identifying key user groups and gaining access to real, representative service/system users. Ideally, we like to recruit and interview 8-10 representative users per user group to be able to capture enough qualitative data to identify trends. Before conducting any interviews or user research, we create a research plan where we clearly articulate research goals, target user groups, and provide a script for the moderator to ensure consistency across interviews. User interviews are typically 1-hour interview sessions with a single participant, a UX researcher who moderates, and a note taker taking place in-person or virtually.  

Contextual Inquiry & Task Analysis 

When tasked with redesigning an existing system, direct observation of existing system usage can be extremely insightful. Observing user interactions with a system or service can provide a valuable context for interview questions, inquiries, and the analysis of the tasks users complete utilizing the system or service. Contextual inquiry and task analysis techniques are frequently embedded into user interviews via screen sharing and session recordings are invaluable. 

Voice of the Customer (VoC) Survey Data 

Voice of the customer (aka user) survey data provides another valuable set of data points to help complete the picture of the customer/user journey. Some organizations have ongoing VoC surveys, which often are a combination of multiple-choice user satisfaction questions and free-form text fields where users can provide detailed feedback. If available, our HCD team will ask for 12 months’ worth of survey data to include in our baseline discovery analysis and synthesis process. Satisfaction data can provide direction and answers to “what”.  Detailed, free-form feedback data can frequently turn out to be a valuable source of information to the questions of “why”.  As with any research, proper survey design and methodology is key to getting the most reliable results. 

Digital Analytics 

To compliment qualitative user interview and survey data, we examine quantitative data that is frequently available via digital analytics programs such as:  

• Google Analytics 
• Digital Analytics Program (DAP)/Unified Google Analytics 
• Commercial CX Measurement Platforms 

These data sets can provide even great insights into the “what” question—in many cases, the data will tell us what user interactions with systems are trending, including navigation activity, scroll behavior, and search terms.   

Data Analysis & Synthesis (Qualitative & Quantitative) 

Once baseline discovery data is collected, layering in qualitative data from user interviews and quantitative data from digital analytics tools, UX researchers code and synthesize the data using tools such as Miro (for affinity mapping), Trello (yes, Trello, for coding and thematic analysis!), and spreadsheets. UX researchers conduct thematic analysis of both attitudinal and behavioral data to identify trends to create a complete picture of key system/service user groups, top-tasks and workflows, pain points, and opportunities for improvement. 

Final outputs from the data analysis and synthesis process are the basis for documentation of findings in the form of personas and customer journey maps. 

Documenting the Customer (User) Profile and Their Journey 

Once our HCD team has collected and analyzed baseline discovery data, insights are compiled into personas and their journeys are documented with customer journey maps. These HCD artifacts are used to share research-based information about service and system users with Agile UX design and delivery teams to give our teams a common understanding of the people we are designing and building digital services for. 

Personas 

To bring the UX research data to life, we develop primary and secondary personas. While personas sometimes get a bad rap, particularly those that focus only on the “story” and are not derived from real UX research, we find that they help document how people think, process information, and make decisions to perform top tasks. Our data-drive personas typically include items such as: 

• Demographics/Bios: the customer background/story to make the persona “come alive”. 
• Behaviors: the actions users take as they interact with systems, people, and artifacts today. 
• Goals/Motivation: top tasks related to existing service (both digital and non-digital) workflows. 
• Attitudes: how users feel about existing service workflows, tools, and system today. 
• Challenges/Top Pain Points: major frustrations with the current existing service workflows, tools, and system today. 

Customer Journey Maps 

Before using rich UX research discovery data to inform digital product design, it is critical to document the entire customer (or user) journey.  With synthesized user research data in hand and primary user groups represented as personas, we document the customer journey (aka the user’s journey) in the form of Customer Journey Maps. UX researchers sketch the process and touchpoints that each persona faces during the end-to-end process, identifying key pain points and opportunities for improvement.  Journey maps are shared with the product, design, and delivery teams to drive alignment of the problems to be solved and the people our solutions will benefit.  

The Power of UX Research in Product Discovery 

The discovery process in product management is a cornerstone for the creation of not just viable products but ones that truly resonate with the end-users and allow them to complete tasks efficiently and with few errors. As we’ve journeyed through its intricacies in this post, it’s evident that the intersection of UX research and product discovery is where the magic happens. It is this synergy that ensures products are not built merely on assumptions or gut feelings, but are rooted in genuine user needs, pain points, and behaviors. 

UX research demystifies users’ wants and contextualizes their needs, enabling product teams to make informed decisions. From user interviews to usability testing (a topic we will cover in detail in an upcoming post), every method offers a fresh lens to view the product, ensuring that every feature, interface, and interaction adds value. Moreover, it’s a dynamic process that encourages iteration, ensuring that the product evolves with user feedback and the changing landscape. 

Organizations that embed UX research into their product discovery process stand a better chance at crafting products that are not just usable, but also highly desirable.  In the end, product discovery, enriched with UX insights, isn’t just a phase; it’s an ongoing commitment to delivering experiences that users cherish. Let us not just build products; let’s create highly usable experiences that always deliver value to both end users and our Agency partners. 

Next Up—Using UX Research Data to Drive Iterative Digital Product Design 

Stayed tuned for our next post outlining additional UX research methods  for iterative digital product design process, including usability testing. As always, feel free to reach out if you want to chat CX, UX, HCD or anything in-between!