Revolutionizing how frequent flyers compare and redeem travel points.

Autopilot is a browser extension that helps frequent flyers maximize their travel points.

During spring of 2024, I had the opportunity to collaborate with a product manager and two developers to bring their vision to fruition. We scoped out the problem space, conducted in-depth research, and built an intuitive extension that compares travel prices and advises whether to pay with cash or points.

The result is a seamless, visually engaging tool that simplifies price comparisons and speeds up travel planning for frequent flyers.

The team
John Miranda
Product Manager
Antoni Ngo
Product Designer
Ethan Harrington
Full Stack Developer
Andrew Capaldo
Back End Developer
Browser Extension
Spring 2024 (8 weeks)
Figma, FigJam, Zeplin, Trello, Loom
Lead Product Designer - Research, User Stories, Feature Backlogging/Acceptance Criteria, Interaction Design, Visual Design, User Testing
What’s the problem?
Travel has become a lifestyle, and maximizing flight points is tough.
 Airlines often devalue points without warning, making it hard to use them efficiently. With travel on the rise post-pandemic, travelers need a simple way to redeem points. Autopilot solves this, helping users optimize their rewards and improve their travel experience.
The research speaks for itself

Through a series of 40 survey participants, user interviews and market research, we discovered…

of travelers that take multiple flights are also members of reward programs.
…out of those travelers,
of their flights are redeemed with points.
of travelers take steps to calculate the value of their travel points...
of travelers aiming to maximize their points if possible.
of travelers are aware that their points can lose value.
…out of those travelers,
are affected by them.
Quotes from research participants:
"It’s challenging finding good deals for my travel dates."
"Should I save my points for a better value later, or use them now?"
"Securing availability for specific routes is difficult."
"Searching for good redemptions is tough."
We found that
At least 1 in 3* travelers express a desire for a product that shows the best time to book with points.
37.5% to be exact*
With research conducted, we asked ourselves..
How can we make it easier for travelers to maximize their travel points so they can fly more for less?
Constraints and opportunities
There were three main problem areas that travelers faced...
Too much work to find good deals
Point-savvy travelers are busy, and have to spend a lot of time calculating and comparing to figuring out how to make the most of their points.
Travel points can lose value at any time
The value of travel points fluctuate day-to-day, across different flights. Travelers struggle to maximize their points since their value can rise or fall without notice.
Flights that accept points aren’t as available
Award seats are often limited, especially on popular routes or during peak travel times. This makes it difficult for travelers to find flights where points can be used.
Moreoever, there were additional things we had to consider:
Mobile or web app, or browser extension?
Almost 80% of users in North America prefer to use a desktop or laptop when booking a flight. We decided to design for Google Chrome, since it holds a majority of the browser market share worldwide.
We had a deadline to make.
With only 8 weeks to build an MVP, the team had to continuously revisit the proposed features that would make Autopilot functional. This meant focusing on only one airline for the sake of an MVP, and deprioritizing features for future builds in order to stay within scope.
We had limited manpower and a dream.
Our entire team consisted of 4 of us; a product designer, a product manager, a front-end developer and a back-end developer.  Although communication was tighter, we had to consider each team member’s technical limitations.
With all this in mind, our goal…
Create a browser extension that calculates and compares the point value of flights, allowing busy travelers to quickly make smart travel decisions
An assistive booking tool that can compare flights, provide real-time insights, and make recommendations on which flight to book, will help users make the most of their travel points. This ultimately enhances their overall travel experience.
Understanding our users and their stories
We needed to better understand who we were building Autopilot for, and what features travelers would need in the first place.
As a frequent traveler, I want to maximize my points for a specific flight route, so that I can save the most money with my points.
As a frequent traveler, I want real-time point value insights for my current flight route, so that I know whether it’s better to pay with points or cash.
Laying out the traveler’s flow
Documenting the happy path gave us an idea of how Autopilot would fit in a traveler’s experience.
With these considerations in mind, we drafted out user flows and documented the screens travelers would land on when booking a flight to get a sense of when travelers would likely use Autopilot and where it would be most appropriate to engage with.
Ideating on the design
Seeking inspiration
Inspiration for the design came from popular extensions, such as Honey, as well as individual components from features such as Google’s log in. In tandem, I also explored ideas for Autopilot’s branding. This includes the logotype, logomark, and favicon.
Creating options for redemption value indicators
There was a lot of back and forth over how the redemption value for each flight would be displayed on the flights results page. I designed three variations, and we decided to move forward with the middle option, as we all agreed that it appeared to provide the most clarity for travelers.
Building the recommendation tooltip
As I continue to develop the design more, I adopted Jakob’s Law and I leaned towards a visual style that was simple and familiar to the design found on many popular airline websites. Leaning towards function and simplicity, the point calculation when the tooltip expands eventually evolved to be a vertical operation, rather than an embellished visual look.
Changes based on feedback
Travelers had a lot to say with how information is displayed.
Throughout the design process, I frequently tested and collected feedback from 6 user test participants. Participants also gave a considerable amount of feedback, which gave much specific insight into the expectations of a frequent flyer. This led to the following changes:
Making the extension menu a little more helpful.
As I continued on designing, a priority item in our backlog was a help guide. Due to the interest of staying within scope, we opted to have this be first shown to flyers when they click on the extension icon near the address bar of Chrome.
Travelers need more clarity on what the badges meant.
During user testing, some participants found the badges shown on each flight to be confusing and didn’t provide enough context  at first. To alleviate this and reduce time on task, the unit CPP (cost per point) was added and the design was further refined.
Travelers want to see how much money they’re saving on a flight.
A major insight I discovered was how most participants instinctively look at the point prices and quickly compare, even before opening Autopilot. On top of that, many of them didn’t find the information being shown as useful as other values shown when expanding the tooltip. Users want to quickly make a decision on choosing a flight,  and the design was updated in order to reflect that.
The calculation breakdown needed to look more familiar to frequent flyers.
Most participants spent considerable time trying to understand the calculation breakdown when expanding the tooltip. They found the former version of the calculation breakdown to be jarring, and opted for a design that was more familiar to other services they’ve used before.
With the deadline coming up, clear documentation was important to ensure a smooth handoff.
In order to ensure a handoff process with little hiccups, I moved the required assets to Zeplin, a well-known and reliable handoff platform. I stayed in close touch with our developers, Ethan and Andrew during this time. The product manager and developers appreciated the handoff process.
What do users think?
Autopilot makes every point count
Travelers are excited for the launch of Autopilot. When testing and collecting feedback from users, we measured the participant’s task success rate, a 1-5 rating of the usefulness of Autopilot, as well as a 0-10 rating on their likeness to recommend Autopilot to other colleagues.
Users on average gave Autopilot a usefulness rating of
of users would highly recommend Autopilot to their friends.
boost in task success rate when identifying the best deal
What’s next for Autopilot?
We plan on continuing development of Autopilot in the future.
We’ve received much support for Autopilot! Although the team decided to deprioritize Autopilot in order to focus on other commitments, there are a few key takeaways that we’ve learned:

Dissecting the product launch strategy. During this time, I spent a significant chunk of my working time with John, our product manager. Teaming with him helped me better understand the vision behind Autopilot, and variables that go into launching it. Had we had more time, I would have designed a user journey map to better understand at a whole how Autopilot can support travelers.

Adapt and accommodate. Working closely with our product manager and developers helped me better understand the importance of their roles. Being present and supporting their responsibilities, such as making designs easier to access or communicating to them using non-technical language allowed us to work more effectively as a team.

Take into account realistic considerations. Although the design faced a series of hurdles throughout the process, the development of Autopilot has been challenging as well. Pulling flight data consistently and in an affordable manner brought into question the scalability of the app, and is something we plan on considering in future builds.

Monitor usage analytics on launch. User testing uncovered a lot of user behaviors that I didn’t expect. On launch, I would like to monitor usage of Autopilot, such as how often the extension is used and tracking reward points utilization before and after installing the extension. This will help determine if we’re on the right track.

Thank you for reading!
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