Sherlock - iOS App
Managing money is way too hard - especially for millennials. The market is saturated with many personal finance solutions (Mint, Level Money etc.). Unfortunately, none of them make managing money a habit. so. The aspect of forming a habit for your finances forms the basis of Sherlock. How do you make managing money an engaging activity for people who see it as a chore?
Inherent to a personal finance app is a large amount of data that needs dealing with. How do you cull through this data in a way to surface actionable insights? How do you reduce the perceived amount of work in managing money? These are some of the problems Sherlock aims to solve.
The process to develop Sherlock began with an intensive round of User Research. To begin, I focused on employed millennials residing in urban areas. I chose this group since I myself fall within it, so it made sense to design for people like me to begin. Once I decided on the first core group of users, I began my User Research Process to gather insights.
I used a simple survey to begin the research process. You can find the survey here. This made it's way to all my contacts that fell into my target demographic. Out of a 100 responses, I arrived at a few common themes and problems. My initial hypothesis was close! Most people disenchanted with money management were between 20 and 27 years of age. They lived and worked in urban areas and had a consistent salary. They used other finance tools, but nothing was completely solving their issues just yet.
From a combination of survey responses and in person interviews, I began formulating Personas. Two variants of users surfaced from my research. Young, recently graduated millennials and older millennials with families. Both of these groups have diverging spending habits, so I decided to cater to only one group for the MVP.
I chose to focus on, in my opinion, the larger use case - Young Millennials. These users have just graduated from college, and are working in urban areas with a salary. They are already immersed in mobile apps, some even for personal finance. But they are not won over completely by a single solution. One interesting insight I gathered that most of them want to know how peers are managing money. At the same time they are uncomfortable sharing too much data.
The building process began with a series of sketches on paper. The key themes identified in the Research phase evolved into core features for Sherlock. Important features included habit formation and knowing what others are doing with their money.
Beginning with paper sketches (shown to the right), these features evolved into wireframes. These wireframes went through a round of user testing in a focus group setting. It is here that key pivots to the design appeared. As close as I was to the design, I was unable to detach myself from it as much as someone seeing Sherlock for the first time. There were some features I thought were amazing, but they did not translate well to the average user.
Wireframes to Visual Designs
The first version of Sherlock uses metrics focused on user retention and in-app interactions. As such the One Metric That Matters for Sherlock is "Daily Transactions Swiped Per User". This is a clear indicator that the premise around making a habit is working. And the directional nature of the metric can provide insight into what's going well vs. what isn't.
By it's nature, this metric has an opposite metrics attached to it. The number of times users use the "Auto-Categorize" feature. More automatic categorizations would reduce time spent in app. Engagement metrics like Daily Active Users are also considered.
Determining the financial viability of a product is important. For this, I ran many simulations of revenue and cost for Sherlock (shown below). These scenarios considered factors like user growth, fixed and variable costs and external funding. For more details on the model, reach out to me if you want to discuss more!