November 29, 2022
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November 29, 2022
When a research team takes on a journey mapping project, it's easy to get siloed in departments or specialties. As Credit Karma began researching how members approached a car purchase, we wanted to take a deliberate and cross-functional approach that involved designers, product managers, and leadership from beginning to end.
Facilitating the experience of research can help align cross-functional teams and create better outcomes for users and product development. In this piece, we’ll break down a recent journey mapping project and how we—as the research and design leads—enabled our cross-functional team to take a more active role in data collection, analysis, surfacing opportunities, and ultimately sharing and owning the work.
At Credit Karma, our product research team has used journey mapping not only as a tool to understand our members’ experience, but as a facilitative process for product designers, content designers, product managers, and even general managers to:
Cars are central to many Credit Karma members’ lives. For many people who don’t own a home, their car is their biggest financial asset. However, members with similar financial profiles end up paying very different rates for their auto loans.
Credit Karma was interested in understanding the car buying space from the perspective of their members. For example:
We had hypotheses about this process, but had never explored members’ end-to-end car buying journey. We wanted to understand members’ holistic car buying journeys and identify opportunities along the way for Credit Karma to provide them with unique tools/offerings, and set them up for financial progress after the point of purchase. We not only needed insights—we needed a tool for our team to make actionable design and product decisions about current and future work.
We decided to build a research-based journey map artifact to visualize milestones, actions, decisions, highlights, pain points, and environmental context for different groups of members. Furthermore, we wanted to do the research collaboratively in order to give each team member co-ownership of the research and artifact.
As the research lead and design lead, we facilitated the research and artifact creation process for our cross-functional team. Our team consisted of:
We used dscout’s Express Mission tool to gather insights about mental models of car affordability and car buying with a broader range of members. In addition to the analysis done by the research lead, we brought the cross-functional team into the analysis process.
The research lead developed worksheets that guided each team member to review a subset of member videos and open-ends in dscout, and then answer a set of reflection questions about patterns in the data and opportunities for our product. After the team completed their analysis assignments, the research lead facilitated analysis debrief sessions to discuss themes identified in the data, including product opportunities.
We also ran a separate Express Mission with a different group of members focused on finances around car ownership. For that exploration, dscout’s team helped us with analysis to expedite our process, which enabled us to focus on diving deeper into individual journeys.
To go deeper, we focused on a smaller subset of members to learn about their end-to-end car buying journey. Each participant completed a pre-interview diary mission in dscout, followed by a 1:1 interview over dscout live. The pre-interview mission enabled us to capture general areas of interest prior to their interview, while the interview enabled us to further explore details in more targeted ways.
At the time of this research, our cross-functional team was distributed and working remotely during the pandemic. We wanted to facilitate a participatory research experience for the team (see Will Myddelton’s post “User research is a team sport”), as well as create notetaking frameworks to organize large amounts of data for later analysis and synthesis (see Curiosity Tank’s posts on notetaking tips and strategies).
The research lead and design lead reviewed all pre-interview diaries, and they moderated and took notes for all interviews in a note-taking framework in Google Sheets.
However, the rest of the cross-functional team was assigned two participants (scouts), each whom they got to understand deeply in the following ways:
Before each interview, scouts reviewed each of their two participants’ diaries. They then created an empathy map of what these participants were thinking, feeling, and doing, including their goals and problems.
During each interview, they took notes for each of their two participants to more deeply understand the journey for our members, and to build empathy for the problems these members faced.
After each interview, cross-functional partners worked with the research and design leads to digitally create an individual journey map for each participant’s car buying journey. Individual journey maps consisted of behaviors, sentiment, thoughts, tools, and problems across the beginning, middle, and end of the journey.
These maps also captured additional information such as what prompted the participant to buy a car, key moments in their journey (e.g., most challenging, most rewarding, least prepared), and regrets and advice they’d give about this process.
After completing all data collection and visualizing individual journeys, we moved into developing an aggregated car purchase journey with our team. To do this together, we held a journey mapping synthesis workshop. This workshop required preparation, execution, and synthesis.
To prepare, the research lead and design lead developed a journey map “MVP,” where we divided the journey into six phases that we had extracted from the interviews. We then plotted participants’ actions and decisions along the way.
This surface layer, however, was missing participants’ sentiment, problems, goals, and touchpoints (external and Credit Karma). We developed a template for each journey phase where our team could populate that data.
During the workshop, we asked our cross-functional team to review the journeys of their individual participants and then plot their participants’ sentiment, problems, goals, and touchpoints across each phase of the aggregated map template.
After the synthesis workshop, the research lead and design lead evolved our journey map MVP by going through each journey phase and synthesizing the team’s participant data points into thematic clusters.
Our next steps consisted of a couple of team workshops on opportunity generation and prioritization.
The goal of this first workshop was to identify actionable, unique opportunities to play a differentiating role in auto purchase.To kick off the workshop and set context, our product management lead provided an overview of the product strategy and our research lead covered a set of key research highlights.
The research lead and design lead then guided the cross-functional team through an exercise where they used the aggregated journey map to generate product and design opportunities for each journey phase in a digital whiteboard. After the workshop, the researcher and designers synthesized the opportunities into a digital canvas to prepare for a prioritization workshop.
Our product design manager ran a workshop where we reviewed thematic clusters of opportunities as a group, and we annotated where there was high member value, near-term product bets, and longer-term product bets.
From this workshop, the research lead extracted a set of key differentiating opportunities. Those mapped back to journey phases, and we aligned with our product management lead on these as the key opportunities we would call out in the final journey map artifact.
Building on the efforts from our collective research power, our design lead refined our final artifact into a nuanced, two-layer journey map customized for our team’s needs:
This layer consisted of:
It also called out key journey moments about affordability, insurance, loans, high positive and negative emotions, etc. To learn more about a particular journey phase, the map viewer could click into it to dive deeper via Layer 2.
We wanted to know how we could safeguard against bad outcomes and increase good outcomes for our members. Being able to dig into each phase helped us understand members' experience with more clarity, and how Credit Karma could help.
Therefore, Layer 2 provided more detail about each journey phase, such as:
This layer also featured key differentiation opportunities for Credit Karma per journey phase and spotlighted additional supporting data, such as:
By bringing the team into the research and journey map development, our partners developed a shared personal experience with the work. Our partners felt more connected to the pain points of our members, as they were able to see that reflected in their memories of the journeys they’d witnessed.
They also understood abstract concepts in the journey map (e.g., affordability, mental/emotional bandwidth, urgency, and safety nets) in a more visceral way. This meant we did not have to explain the journey map from scratch.
The two-layer nature of the map facilitated this by making it simple to move from first layer actions and decisions to a sub-layer of sentiment, goals, problems, internal/external touchpoints, and additional data.
The shared experience of the research naturally led the team to co-own the research and journey map. We even brought in our cross-functional team to co-present the final research deck and journey map with us to a wider audience and help answer questions!
The research and design leads did not have to convince our team to use the journey map. By contrast, our cross-functional partners became the work’s biggest advocates, promoting the work in strategy presentations and discussions to humanize problems members faced, and using it to inform subsequent product and design explorations.
As a result, the shared, co-owned research experience inspired and enabled the team to:
Rather than having the research lead and design lead work in a silo and later reveal a polished artifact, we co-developed our journey map as a tool with our team. This enabled our team to build a shared understanding of the work, bring in multiple perspectives, and develop an actionable artifact for product and design use.
This is especially important in the context that foundational research like this takes time. It’s not a 20-minute user test of a product flow—it was months of work to get to this deliverable. Bringing our stakeholders along for the ride helped show just how much work was being done, and why it took the time it did.
Our cross-functional partners loved to participate in research, but research is not their primary job. They appreciated templatization, organization, and coaching throughout the process.
We helped our cross-functional partners by developing note-taking frameworks to organize the rich qualitative data from research participants.
For example:
The research lead and design lead carefully prepared for each workshop (e.g., context setting, team activities, communicating next steps, and post-work shop synthesis).
They then enlisted other teammates for help as presenters or co-facilitators, as needed (e.g., bringing in our product management lead to provide a product strategy overview). This pre- and post-work helped streamline our partner involvement.
However, not every cross-functional partner is able to participate in the same way, so it’s important to meet your team where they’re at. Some partners have more or less time depending on their project or leadership responsibilities. Some partners also have different interests in the research depending on their area of responsibility.
For folks who had less time, we asked how much time they were able to allocate, and we tailored their activities accordingly. When possible, we also gave people options of what areas to dig deeper in. For example, our Express Mission analysis worksheets gave folks a choice of what sections they could help analyze.
With longer-term foundational research, teams have concerns about waiting too long to use the work. To address this, we broke up the work in chunks and set the stage we would work iteratively from the start.
For example, we…
By the time of our final share out, our cross-functional team already knew the outcomes of the research because they had been part of it. This allowed our cross-functional partners to start using the work early—such as developing experiments and informing strategy conversations.
This ultimately improved our final deliverables, by gathering multiple perspectives on the work and co-aligning on actionable opportunities.
Tatiana Vlahovic is a Senior Product Research Manager on Credit Karma’s Product Research and Strategy Team. At the time of this article, Pedro Rodriguez was a Product Designer on Credit Karma’s Product Design team (he has now transitioned into Credit Karma’s Design Operations team).
