UX UI Case Study

Airbnb Split Pay: A Simple Fix for Group Payment Hassles

Febrary 20, 2024

Challenge

A 2022 study found that 47% of Americans split accommodation bills using p2p payment apps like Venmo, Zelle, and Cash App. However, these apps are limited to the US, posing challenges for international splits. This highlights a potential need for an in-app payment split feature in platforms like Airbnb to accommodate international travelers.

My goal is to enhance the user experience of booking accommodation as a group. Currently, only individuals can book accommodation and encourage their friends or colleagues to pay them back after payment is made. We'd like to make it easier for groups of people to split the cost of an Airbnb when traveling together.

Results

I designed a built-in payment splitting feature that requires all traveling guests to pay before completing the booking, eliminating the financial burden on one person to front the entire payment. The feature allows users to customize payment distribution based on different lengths of stay, removing the need for manual calculations. During user testing, our solution completely eliminated errors in uneven payment distribution, and post-task surveys showed higher user satisfaction compared to existing solutions.
50%
Time to complete reduced by
100%
Error rate reduced by
32.2%
Increase in SUS score

User research

I utilized Google Forms to survey a diverse sample group of 20 individuals across various demographics. They were asked about their group travel experiences and accommodation preferences to gain insights into recurring behaviors and pain points. Here are some of the findings.
What challenges have you personally experienced when splitting accommodation payments with a larger friend group?
The data revealed significant social pain points in expense management among friends. 54% experienced delays in reimbursement, especially pronounced when dealing with friends rather than close friends (25%). Payment tracking was also a notable concern, highlighted by 20.8% of respondents.

Affnity mapping

To further synthesize the gathered data, I used Dovetail, establishing a taxonomy system rooted in observed behavioral patterns and trends gleaned from the data. Based on this, I crafted visual affinity maps to cluster recurring patterns. Here are some key findings:

Behaviors - one person accountability

Usually, one person bears the responsibility of booking and paying for accommodation upfront, leading to an unequal burden of accountability.

Motivations - price, points & easy cancelation

The data revealed common reasons why users preferred competitors over Airbnb: easy cancellation, cheaper pricing and point systems.

Pain points - lack of common payment system and fear of losing money

The person who pays upfront often feels burdened with excessive accountability, having to manage and track payments from fellow travelers. While apps like CashApp, Venmo, and Vipps exist, they're limited to specific countries (e.g., CashApp and Venmo in the USA, Vipps in Norway). This indicates a market demand for an in-app group payment management feature.
“everyone have different way to make transaction, some people only use cash, bank transaction, Line Pay or Paypay. It is bit hard to collect when they all use different method.”
Additionally, one user mentioned feeling like they're "losing money," even though they're not. This reveals an irrational fear that our solution should aim to alleviate.
“Getting all these expectations can be tricky because ultimately it's the person who paid for something's job to track and communicate with everyone, and sometimes that can be awkward if expectations aren't aligned. One person accountability.”

User Scenario

Instead of creating personas, I’ve rather decided  to create user scenario (or rather a narrative) and focus on capsulating the users behavior and pain points. I also took the liberty to add some fictional aspects that weren’t necessarily mentioned in the survey, however as a tool to emphasize the the some of themes for our affinity maps. ablishing a taxonomy system rooted in observed behavioral patterns and trends gleaned from the data. Based on this, I crafted visual affinity maps to cluster recurring patterns. Here are some key findings:
The main user arranges a trip for five friends, booking an Airbnb to suit their group's cultural interests. One friend abroad lacks access to common payment apps, complicating expense management.

The end-user pays upfront but dreads the tedious reimbursement process, especially with a forgetful friend. One of the friends is staying one day less, which add to the complexity to the payment distribution, causing stress.

Despite expecting post-trip reimbursements, the upfront payment causes anxiety of the main user. The group's use of diverse payment methods, including cash and various apps, complicates matters further.

The main user also fear that these inconveniences may strain their friendships.

Problem statement

Managing group travel expenses is a significant challenge for users booking accommodations on platforms like Airbnb, especially when dealing with diverse payment methods and international friends. The primary user, often responsible for fronting the costs, experiences stress and anxiety due to the cumbersome reimbursement process, varying lengths of stay, and the lack of a universal payment system. These issues can lead to errors, delays, and strained friendships, highlighting the need for an integrated, in-app group payment management solution that simplifies expense sharing and enhances the user experience.

How may we design a solution that streamlines group expense management, alleviates the stress of upfront payments, and ensures timely reimbursements while maintaining harmony among travelers?

Competitor Usability Audit

To better understand industry best practices for both accommodation booking and peer-to-peer payment systems, I conducted a usability audit of direct and indirect competitors: VRBO and Vipps.

In VRBO, I observed how they effectively visualized the cancellation policy timeline using a progress bar. This inspired me to consider how communicating deadlines, especially within a group booking context, would be crucial for my project, ensuring clarity for all users involved.

From Vipps, I gained insights into how personalized and animated components can enhance the user experience and motivate specific actions. For instance, by adding cosmetic elements to payments, Vipps personalizes transactions in a way that adds a positive touch for both sender and recipient. Since my system also involves financial transactions, I realized that incorporating subtle, playful interactions would be important in making the payment process more engaging and enjoyable.

Sketches

I began sketching low-fidelity wireframes to visually brainstorm ideas and gather immediate feedback from potential users before committing further to them.
The data revealed that one person usually acts as the planner/booker, leading to stress due to accountability imbalance. Initially, I explored making the booking process more collaborative with group chats and shared booking systems. However, when I asked presented this idea to potential users, a great majority expressed that this was too complicated and didn’t , so I decided to cancel it.
For idea 2nd, I reiterate some of my ideas from before, but this time I was less focused on reinventing the wheel, and more focused on how it can fit into the current Airbnb app while also remedying some of the pain points addressed in my research.

Aim:

  • To relieve the sense accountability imbalance when paying for booking 
  • Make it easy for the booker to custom and keep tab off the payment distribution, while also it’s clear and transparent for the other guests too
  • To make the entire experience an in-app experience, without relying on 3rd party p2p-payment services

Feature:

  • To relieve the sense accountability imbalance when paying for booking 
  • Group payment distribution customizer/calculator
  • Flexibility for guest user to pay their customized share, based on either nights stayed or percentage
  • Filter for listing that allows group payment (room owners should have to option whether accept group payment or not, due it it’s reserve before pay nature)
  • Invite guest user via URL feature

User flow

In the first user flow, I mapped out the sequence of actions as they currently occur in the Airbnb app, including external operations like manually calculating uneven payment distribution and messaging friends about payments. I highlighted the steps that fall outside the Airbnb app and identified those prone to a high error rate.

In the second flow, I visualized the sequence of actions with my redesign, emphasizing how many of these steps are now integrated within the Airbnb interface, reducing reliance on external tools and minimizing potential errors.

Hi-fidelity prototype

We conducted one usability test with the first iteration of the high-fidelity prototype and below is the revised version.

Primary user booking UI

Guest user UI

User test and results

To evaluate the impact of my redesign on the booking experience for groups, I conducted a controlled user test with five participants. They were tasked with booking accommodations for a group of friends where the payment distribution was uneven due to varying lengths of stay. Initially, I observed how they completed these tasks using the current Airbnb UI, followed by testing with my redesigned interface. The key metrics observed were:

Completion time

Completion time reduced by
50
%
Current UI: On average, users took 7-8 minutes to complete all tasks, with the majority of time spent on manually calculating the uneven payment distribution due to the complexity of the math.
Redesigned UI: The introduction of a built-in distribution calculator allowed users to input the number of nights per guest, reducing the time to 3-4 minutes — a 50% decrease in overall task completion time.

Error rate

Errror rate reduced by
100
%
Current UI: Only 4 out of 5 users managed to calculate the uneven payment distribution correctly. Some users approximated the values, but they were not accurately proportional to the different lengths of stay.
Redesigned UI: The built-in distribution calculator eliminated errors entirely, with all users accurately distributing payments, resulting in a 100% reduction in error rate.

System Usability Scale (SUS) score

Increase in SUS score
32.2
%
Current UI: The SUS score averaged 59 points.
Redesigned UI: The SUS score increased to 78 points, reflecting a 32.2% improvement in perceived usability.

Conclusion

The redesigned payment splitting feature significantly enhances the Airbnb booking experience for groups, addressing key pain points identified through user research and testing. By integrating a built-in distribution calculator, the redesign simplifies the process of dividing costs, effectively reducing completion time by 50% and eliminating errors entirely. This improvement not only streamlines the booking experience but also ensures fairness and clarity in expense distribution. The increase in the System Usability Scale (SUS) score by 32.2% further underscores the positive impact on user satisfaction. Overall, this case study demonstrates the value of a well-executed UI/UX redesign in addressing user needs and improving functionality, ultimately leading to a more seamless and enjoyable group travel experience.