Venmo Split
PROJECT OVERVIEW
Project Length: 5-day sprint
Goal: To analyze an already existing and highly adopted app and incorporate a new feature into the existing product. This feature is based on an area of functionality to be explored and compared to user input.
Discover
MARKET RESEARCH
In the discover stage we focus on understanding the client, asking broad questions, looking for client and user challenges, and identifying what we do and don’t know.
We thought of potential business problems, desired outcomes, user types, and challenges. This helped us discover any assumptions we might have about the business and users and figure out ways to test them.
Feature Comparison Chart
The feature comparison chart is a tool that allows us to compare our app’s features side-by-side with its competitors. This helped us identify any trends and openings in the market more easily.
Identifying mental models helped us understand what users expect to see in a cash sharing app so that our solution would resemble features that users have seen before, thus allowing it to feel more intuitive and easy to navigate.
We struggled to see some features that Venmo lacked other than an investing feature, which only a few other apps had. But, we also noted that Venmo was the only app in the market that had social features, specifically a social feed.
Market Positioning Chart
A marketing positioning chart is a tool that allows us to look for an opening in the marketplace with untapped potential, or what we call a “blue ocean.”
By placing the competitors based on the labels created, we can better identify an open space on the chart which indicates a blue ocean.
As you can see, we labeled our chart from transaction-oriented to socially-oriented, and app simplicity to app complexity.
We can see that Venmo is the most social out of all its competitors. This chart provided clarity on the direction we should move in when creating our added feature.
USER RESEARCH
After finishing up our market research, we moved onto user research. We began with a survey, which we sent out on Facebook and email to our contacts.
We used Facebook to reach a broader range of people of all different ages and backgrounds, and understand their experience using cash sharing apps.
Quantitative Data: Surveys
We collected 52 surveys from Facebook and friends using Google Forms, which provided many insights about the ways in which users interact with cash sharing apps.
Qualitative Data: Interviews
We interviewed around 5 people total, each of whom had experience with Venmo and at least one other cash-sharing app.
This was helpful because I was able to get a deeper understanding of our users’ motivations for using Venmo over apps like Cash app and Pay Pal.
Define
MAKING SENSE OF THE DATA
Affinity Map
An affinity map is a tool that allows designers to structure the data from their qualitative research and find underlying themes and trends from their users.
Significant themes that were observed involved the frustration of splitting bills, the pains and gains of Venmo, and a general liking for the social features in Venmo.
This map provided a lot of insight when organizing our data and finding a direction for our problem definition.
Value Proposition Canvas
A value proposition chart helps designers clearly identifies measurable and demonstrable benefits users receive when using a product or service
Creating this chart based on our data helped us understand ways we can add value to our users’ experience on Venmo according to their goals, motivations, and jobs they need to get done.
We are also empathizing with the user’s highs and lows so we can consider the psychology behind their behavior.
User Persona
In order to get a more tangible grasp on who our user is and how we can help them, we created a user persona based on our data.
We identified some of the most common characteristics of our primary user to develop Downtown Dakota:
Dakota is a single 27-year-old woman who lives in Los Angeles, loves exploring her city, and is an aspiring actress. She frequently checks out hot spots with her friends and loves to meet new people. She’s rather social and uses Instagram and Twitter every day
The user persona is so important because it helps give a face to our primary user group and makes it easier to relate and empathize with the problems she faces in her everyday life.
The user persona also helps prevent us from inadvertently designing a solution for ourselves and not the user.
As-Is Scenario and User Journey Map
The as-is scenario map is a tool that helps us find hidden user pain points and frustrations that we might have left out in our process.
Since most of the users we interviewed use Venmo to split drinks and food when you're going out with friends, we had our user scenario reflect this. We follow Dakota on a night out with her friends. We see her go to dinner, uber to bars, and then go home.
We were then able to plot Dakota’s emotions on a user journey map, where we can clearly identify the lowest emotional points, which indicate her biggest frustrations on a night out.
Dakota’s main pain points were:
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Splitting the bill at dinner
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Splitting Ubers throughout the night
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Calculating the amount owed to each person the next day
The value-proposition map and user journey map taps into our users’ psychology and provides insight on WHY these were her biggest pain points by looking more closely at her emotions and thoughts.
So, What is the Problem?
From our journey map, we defined three clear problems that occur Dakota faces when tries to complete the three actions in her user journey.
Problem Statements:
1. Our user is agitated because she wants to split a payment without switching from app to app all night
2. Our user is unsure and indecisive about how to keep track of multiple bills throughout a night out with her friends
3. Our user is anxious and full of dread about having to calculate and request money after a long night out with her friends
From these three problem statements, we also created three “how-might-we” questions that would help us think of ways we could solve these problems.
How Might We…
1. help our user easily split multiple payments on one platform?
2. help our user keep track of multiple bills between friends throughout her night?
3. help our user efficiently calculate and request payment amounts from friends to alleviate her anxiety?
Develop
PROBLEM MEETS SOLUTION
Ideation + MoSCoW Method
We used a tool called the MoSCoW method to group each of our feature ideas from most essential to least essential, based on our data and the problems we found that our users were experiencing.
We took every idea from our brainstorm and placed them into one of four categories: Must-have, Should-have, Could-have, and Won’t-have. This process helped ensure that we only focused on the most essential features that would solve our problems directly.
After narrowing down our must-have features, we returned to our value proposition canvas to ensure there was a strong product-market fit.
Minimum Viable Product
At the end of the development stage, we finally reached our minimum viable product.
An MVP is a product which solves users’ frustrations and adds value to their experience with the minimum amount of features.
The MVP is important in order to create features that are essential to solving the problem, rather than for fun design or innovation.
How will users navigate through our product?
User Flow:
A user flow chart is a tool that maps out paths our users will take when navigating through our product to achieve a certain goal.
This process involves organizing information architecture, where we strategize how to display and structure each piece of information within our product.
Display Page
User Decision
Computer Decision
Group Tab
Path
Split Tab
Path
Key:
Split / Create Group Tab
User selects Create
Group Tab
Create Group
Tab Name
Group Created
Add group
members via
type or scan
User adds
6 group
members
User selects split tab
Add split recipient
User types username of recipient
Add bill amount + description
User adds amount and description
Split Bill amount sent to recipient
User
confirms bill
Review and Confirm Split Bill
User adds
a new transaction
Current
Group Tab
Opens and Displayed
User selects current
group (live)
Group Tab
Home Page
Displayed
Sends out
requests to join
Transaction
Details
are displayed for user to fill out
User adds description and receipt photos
Review and confirm Transaction Post
User confirms and posts transactions into group tab
New transaction displayed in group tab
We can see that the user will either split a payment directly or create a group tab with their friends. The user is able to create a fun group name, invite friends, add new bills and receipts, and split these payments between their group at the end.
After we developed a general idea of how our feature will flow, we moved into prototyping and testing.
Deliver
Wireframes to Prototypes
Lo-Fidelity Wireframes
We created a lo-fi prototype using a pen and paper for easy iterations and changes. We decided to make our features mirror the Venmo brand and its features as much as possible.
How we decided to design our features:
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When users attempt to create a group tab, users will find that adding people to their group is almost identical to the way that users currently type to find friends when making a payment.
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Users will be able to add a description for their group transactions, just as they currently do in the Venmo app when making or requesting a payment.
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The group tab page is designed to resemble the current social feed within Venmo, where users can view transaction between their friends.
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Previous group tabs are organized in a list form, in the same fashion transaction posts are displayed on Venmo.
We used Maze to create a usability test for our lo-fi prototype before moving on with our design.
Usability Testing
Most users said that the placement of buttons, pop-up windows, and navigation elements felt intuitive and easy to navigate through, although we made the mistake of marking where our users should be clicking.
Heat maps confirmed that our users knew where to click, although this data was slightly corrupted.
Mid-Fidelity Prototype
The next step was to make changes according to user feedback in our lo-fi prototypes. Our product mirrored the interface of Venmo, and since most users we tested with were familiar with Venmo, they easily recognized the placements of buttons, menus, and information in our prototype. However, we used Maze metrics to gain a deeper insight into our users' actual engagement with our design.
Usability Testing
Our usability metrics were overall higher, with a 100% success rate and a 91 usability score. After we made minor changes based on our user data, we finally got to designing our hi-fi prototype.
Hi-Fidelity Prototype
Once we analyzed all of our user feedback from our mid-fi prototype, we made minor changes mostly related to placement of headings, buttons, button labels, and navigation elements.
From there, we filled in our mid-fi prototypes with color, text, and photos to bring our final design to life. Click the button below to view and engage with the full prototype.
Creating the group
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Users can easily add group members by typing in a username, phone number, email, or scanning a QR code. This feature reflects Venmo's design.
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Users can see who is in their group and create a unique group name.
Adding transactions
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When looking at a new group tab, the feature hints to users on how to add a new bill.
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Users can continously add bills throughout the night, view other members' bills including bill descriptions and receipt photos.
Splitting the bill
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When users are want to close out their group tab, they can hit "End Tab." This prompts a screen which asks users to confirm this action to avoid errors.
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The feature will then automatically calculate and split the entire bill evenly, showing a breakdown of each payment amount and all receipt photos.
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Users can also edit this calculation manually to correct errors.
Next Steps
For this project, we didn't end up testing our hi-fidelity prototype with users so we listed next steps, including success and failure metrics to determine how well our product works with users.
These metrics involve app analytics, tracking how often users engage with our feature, increased traffic and user retention, reading app reviews, and how quickly users give up on tasks related to our feature.