Quick Payments
HeyGov • 2022
For US municipality residents, HeyGov has always been the platform where their day-to-day transactions were made. However, citizens of larger municipalities often complained that there were too many services and could not easily find what they were looking for.
ROLE
Lead Product Designer
contribution
User Interface Design
User Research
Product Strategy
Challenge
Municipality clerks have the authority to add as many items or services that citizens can purchase as they like. This resulted in a very cluttered interface and scalability issues. Citizens were no longer easily able to find the services they used to pay for.
This is what a typical list of services for small municipalities looked like.
A more common list of services for a larger municipality.
While the problem was always in the back of our minds, it didn’t really present itself as a problem early on as most of the municipalities on the platform were small-sized and did not have a long list of services.
Our Vision
Curate the list of services based on previously paid services. We aimed to not only solve the issue of scalability, but also increase # of payments month-to-month.
A more personalized experience
We would curate the first 7 services based on the user’s behavior. Things like how often a user pays for said service and how much they paid would dictate whether or not the service would appear on this list.
Initially, we would not have enough information to start showing the most used services. Our plan was to use our existing data to show the most popular services app-wide, and over time as more data started coming in, start personalizing the experience.
Reduced options
With the new grid layout, we’re no longer facing any problems when it comes to the issue of scalability. With intent behind what services are visible, we can comfortably hide any additional services behind another page.
Results and Summary
We set two primary metrics for success for this new redesign. Higher # of payments made per month, and improved time to action.
A month after launch, we saw an increase of 12% in number of payments made per month, and users, on average, spent 20s less looking for the service they want.
This experiment has generally led us to think more about how to approach problems using more personalization that should hopefully lead us to higher revenue. While that wasn't a metric we were tracking for this problem, it's definitely something that was put in the backlog as a result.
A few of the key takeaways I got from this challenge:
More technically challenging solutions usually require more robust data to get buy-in.
Set some time to revisit the backlog every once in a while, some problems may be glaring right at you, especially as you scale.
