Retirement Manager (RM) participants don't have a self-service system to get information about their investment portfolios. This results in high call volume to RM support and overhead for Morningstar.
With this project, we had the opportunity to help users answer their own questions and improve the service experience, leading to increased retention rates for the RM service.
This is how I got started:
I examined the most-asked questions. I pulled 6 months worth of customer support data and combed through it to understand what drove RM users to reach out to Morningstar.
I connected with colleagues from across the company. From sales to support, cross-disciplinary input was essential because it helped me understand the nuances of a retirement saver’s experience across service touchpoints.
By the end of my discovery phase, I had an itemized list of the most commonly-asked questions that Morningstar received from RM users.
I took the extra step of categorizing these issues into buckets, to improve visibility into the key areas of the platform that needed to be addressed from a service experience standpoint. I tagged them and organized by user journey phase and service touchpoint. This not only helped prioritize issues in order of need but also helped to create my roadmap for the rest of the project.
Question categories
How to cancel an RM membership
RM’s investment strategy
Explaining ups and downs of the stock market
How RM constructs portfolios
Changes to plan balance
Updating profile information
Searching in RM
Understanding RM’s Fee Structure
I worked towards addressing these pains by focusing on the motivating emotion behind each question. Retirement is a sensitive subject for many people and I wanted to understand that piece of the puzzle better. What was the question behind the question?
For example, if a user asks: "Why have I lost X amount of money?"
what they're really asking is: "Can I trust Morningstar with my retirement savings?"
I wanted the help center to cater to emotionally charged questions with the best tone of response to comfort the user while providing their answer.
I determined four “levels” of motivation and the respective tone of response for each.
Motivation
Interested
Interested, Cautious
Confused, Frustrated
Frustrated, Scared, Controlling
Tone of response
Informative, Helpful
Informative, Helpful
Reassuring, Informative, Helpful
Calming, “Let’s handle this together”
I also considered the touchpoints that users would have with RM, in addition to their level of experience with retirement saving, a term coined investor maturity. For the former, I mapped out the user journey and determined the top four service touchpoints users would have with our platform.
Service touchpoints
Sales materials
In-app content (i.e. tool tips)
Help center FAQ
Call center scripts
User Journey
Introduction to RM
Research and evaluate
Enrollment in RM
Engagement and re-engagement
For the latter, I utilized a framework previously built by the RM design team.
This framework divides users into “maturity groups” based on their knowledge and understanding of retirement saving. These groups affect what questions users ask and the potential motivation behind them.
Compiling all the factors I assessed in my Discovery phase, I created a content model to inform the remainder of the project.
Motivation
Tone of response
Service touchpoints
User Journey
Question category
Investor maturity
The content model was an essential step in my process towards a well-rounded help center. I could now use it to map any customer question along it’s various touchpoints, from user journey to investor maturity.
The model could also be used by the RM team long after this project was complete to track user inquiries across various factors.
I was ready to start writing. (finally)
I researched and wrote answers to the entire list of user questions.
Once my writing was complete, I could start testing. For this project, testing was limited to internal Morningstar employees, all of whom were enrolled in RM.
I conducted highlighter testing with 5 people to test their comprehension and reactions to my content.
Based on the user testing, I found the following key insights:
Unfamiliar phrases create uneasiness. Vague phrases like “projected earnings” and terms like “total wealth methodology” made testees uncomfortable.
More emphasis on customization = good. Testees liked references to customization and appreciated emphasis that their retirement plan would be tailored to them.
I tweaked my content to align with this feedback.
I mocked up the UI of the help center using Figma. I opted for an accordion menu navigation on the left side, with questions categorized into their respective categories.
I wanted the final design for the help center to have a welcoming feel, meeting users where they are and not overcomplicating the experience with academic terms.
As a result, I updated the phrasing on many questions and category titles to be easy for users to understand and navigate. For example, “How it works” rather than “Methodology.”
I included links to additional resources like methodology papers or research articles, and easy access to reach out to our RM account reps. This way, if a user had more questions, they were immediately routed to more avenues of information on RM.
The best designs come from collaboration. This project was a success in large part due to the partnerships I formed across the company that resulted in an interdisciplinary and well-rounded final result.
Thorough research is key to effective solutions. Using real customer data to determine questions and testing my answers to those questions helped me stay focused on putting the user experience first.
Keep it simple, stupid. I picked up quickly in testing that my user base had varying levels of experience with retirement investing. Especially in content development, avoiding advanced, academic language was necessary to meet users in their comfort zone.
