Vrbo
Product design for MarketMaker
My Role
-
1 Design director
Tools
-
Figma
-
1 Product designer (me)
-
Jira
-
1 User researcher
As the product designer on the team, I designed MarketMaker's core experiences — including the rate strategy feature, the events integration, and the onboarding flow for new homeowners. I partnered closely with the design director on product vision and with the user researcher on synthesis, while independently leading all design execution, iteration, and handoff to engineering.
What needs to be solved
Vrbo homeowners are running small businesses — but most were pricing their properties based on gut feel, not data. Before MarketMaker, owners had little visibility into market rates, local demand, or upcoming events that could affect bookings. The result: underpriced properties, missed revenue, and disengaged owners.
My goal: Design a suite of tools that gave homeowners the market intelligence and rate strategy controls they needed to manage their properties confidently — without requiring them to become pricing experts.
Owners who don't use MarketMaker (935k)
45%
of browsings turn into bookings
Owners who use MarketMaker (700k)
68%
of browsings turn into bookings
26%
increase in revenue for owners who used MarketMaker strategy
33%
increase in booking for owners using MarketMaker
2
More bookings per user per month
What homeowners were telling us
We invited homeowners of all backgrounds into our research lab for usability testing and interviews. We wanted to understand what tools and data they actually needed — not what we assumed they needed. I sat together with the UX researcher in the UX lab, while we observed our users' interactions with the product. After numerous rounds of testing, three needs rose to the top consistently:
"I don't know if my rates are competitive — I'm just guessing. There is nothing that I can look at to know the right rates."
"I don't know what is the right rate to set. My rental is always empty and I'm not sure if it's because my rates are too high."
"I set my rates by browsing some of my neighbors' rates to get an idea of the price range."
"I wish I could see what events are coming up so I can adjust my prices. I'm not always updated with all the events."
"Setting rates day by day takes forever. When I do them myself, I lose focus."
How homeowners set their rates
We asked homeowners specifically how they set their rates, and here are what they told us.
Manual base rate setting
Owners set a base nightly rate when creating their listing and could update it at any time through the owner dashboard, but this was entirely manual with no data guidance.
Expense-based pricing
Some owners calculate rates to cover expenses, generating a list of fixed costs (mortgage, taxes, insurance) and variable costs (utilities, repairs). Essentially setting a floor price based on what they needed to break even.
Checking competitor listings manually
Owners would browse Vrbo.com or similar platforms, look at comparable properties in their area, and eyeball where their rates should fall. No automated comparison, just manual research.
The research pointed to a clear gap: homeowners didn't lack motivation — they lacked confidence. They needed tools that removed the guesswork, and provide them with answers.
What we realized
Vrbo had much of the data that our homeowners needed to make decisions, but we did not provide the right data when they needed them. Homeowners often had to get essential data from other tools, or they had to guess the right daily price to set. But when our homeowners did not set the optimal daily rates for their properties, Vrbo also lost businesses on our platform.
To answer the main question
I worked with our product managers and researchers to understand how owners set rates and what tools they relied on. A competitive audit revealed a consistent gap across the market: fragmented tools with no explanation behind them. Our homeowners needed us to provide trustworthy and relevant data to them, when they are setting their daily rates. They don't need to go elsewhere to look for those data, or go with their gut feeling.
Based on the findings, I summed up what homeowners need.
Values of surrounding properties
A homeowner should get an insight of what the rates are of surrounding properties. They should be able to compare their properties with those with similar attributes, such as number of bedrooms, bathrooms, and other attributes.
Neighborhood insights
A homeowner should have a complete picture of rates of neighborhood properties to help determine the right daily rates.
Special occasions
A homeowner should know how a special event nearby would affect traveler demands.
Revenue Strategy
The revenue strategy concept allows a homeowner to set an operating strategy, and the daily rates are automatically set for the year, based on seasonal trends.
Seasonal changes
A homeowner should know the repeating trends of 4 seasons, what time of the year is busy, and what time of the year is slow.
I started sketching ideas.
Vrbo had many of the data that homeowners needed to set their rates, from the properties that exist on the Vrbo platform. What I needed to know was which data would be useful to a user at a specific time. By collaborating with product managers, engineers, and researching on our data, I was coming up with ideas, drawing out wireframes, and exploring which ideas made the most sense.
Design explorations
Version 1
This was the first version of MarketMaker. While the essential functions are the same with the final product, and it looks similar to the one I ultimately went with, I later found out from our users that this view is quite busy. They found it hard to focus and comprehend this view. Even with a lot of data, it is busier than it can be. A few examples are:
Switches on graph items are on the right
All switches of the graphic items are on the right side of the line, making them far away from the labels. The users found it hard to read.
Your reservations & events
Reservations are all the past and future reservations of this property, but events are other events happening in this area. Having them together seems like events are about this property.
"Your search position" is confusing
While the users understand the term "Your search position", they find it hard to comprehend the search position for future dates, since those haven't happened yet.
Summary & Calendar tab is not necessary
Our users expressed that the summary and calendar tab are not really related. They are here to get to the actual data. Many of them expressed that they do not go to the summary tab.
Version 2
For Version 2, I addressed a lot of user feedbacks from Version 1. My primary focus was to make the main data easier to read, and I tried several methods to do that. I moved all switches of the graph items to the left, right next to the labels. I also added a hover state for each graphic item, highlighting the graph item when the label is hovered. Overall, I tried to make the complex data as easy to read as possible.
All labels under one category
A lot of users found that having the graph labels in 2 categories was busier and harder to read than having all labels under one category. They found it simpler and cleaner overall.
Updated upper sections
The upper sections are updated to bring more simplicity. The users were confused about reservations & events being together, and I moved events to its own section, and renamed it to "Events & holidays" to bring clarity.
Hover state with tool tip
I added a hover state to each label of the graph item, highlighting the graph item on the graph, while fading other graph items, to simply the data and make it easier to read for the user.
The final product
Here is the end-to-end design of MarketMaker's core experiences: rates strategy, reservations, competitive insights, and events integration.
Opportunities
MarketMaker uses Vrbo AI to inform the user if the rates that has been set is the best rate or not. If there are better rates that would increase the chance of getting bookings, Vrbo would inform the user that there is an Opportunity in certain dates. This concept addresses user feedbacks that they were not aware of the right rates to set.
"I don't know if my rates are competitive — I'm just guessing. There is nothing that I can look at to know the right rates."
This feature addresses the user feedback:
Recommended rates and current rates
An opportunity clearly displays recommended rates to use Vrbo's available data to provide optimal rates for the user, giving the user quick solutions.
In a date range
An opportunity is in a date range to display all dates affected by an opportunity.
Grabs user attention
Opportunity icon is displayed on the top of the page in a rocket icon to immediately grab the user's attention.
Highlights the affected date range
The affected date range is highlighted, while other parts of the graph are faded, to bring more simplicity in a lot of data.
Opportunity display on newsfeed cards
The MarketMaker opportunities are displayed on newsfeed cards, to drive more awareness of potential bookings with better rates, drive users to go to MarketMaker, and increase more activities on Vrbo.
The display of an opportunity on a newsfeed card is consistent with the display on MarketMaker.
After hearing the perspective of the engineers, I understood the development efforts involved, but I also understood how much value this feature would bring to homeowners. They were expressing the need to have a tool that informs them of the optimal rates to set for their properties. This feature not only informs them of the optimal rates, but also set future rates for the whole year for them, simply by asking them about their goals. I told this to our engineers, and stressed the helpfulness this feature would have for our users.
28%
Of the 350k owners (98k) we launched to, received MarketMaker positively.
72%
Of the 350k owners (252k) had 2 consistent concerns.
Rates strategy, and Vrbo AI
Rather than asking owners to set daily rates manually, I designed an overall strategy feature that lets homeowners choose their priority — more bookings, higher rates, or balanced revenue — and lets Vrbo's AI handle the rest.
The AI uses historical data and competitor activity to set daily rates automatically. Occasionally it spikes rates for specific days — reflecting nearby events, competitor pricing shifts, or high local demand — then returns to baseline. Owners can override any individual day, giving them control without the burden of managing every date manually.
This directly addressed the most common frustration: the exhausting, guesswork-heavy process of day-by-day pricing.
The user tells us the goal, and we set the rates.
Occupancy strategy
An occupancy strategy aims to get the most amount of bookings, without necessarily the most amount of revenue.
Revenue strategy
A revenue strategy aims to get the most amount of total revenue, without thinking about the most bookings, or highest rates per booking.
Top-dollar strategy
A top-dollar strategy aims to get the most amount of rates per booking.
Discussions with engineers on the Rates Strategy feature
When I initially presented the Rates Strategy feature to the engineers, there were some resistance to fully developing this feature. This feature was drastically different from previous designed that our team has handed of to the engineers. The amount of data it needs, and the way to utilize the data, was very different. Initially, our engineers had these feedback:
It needs a lot of data.
Setting a rates strategy would automatically set the rates of a property for a whole year. It would utilize the data of past rates, seasonal trends, surrounding activities, market conditions, to come up with optimal rates for the whole year.
It will take too long to build.
Building this feature would require starting new components, patterns, and animations. When the user adjusts the strategy on the bar, The animation of the graph needed to be built from the beginning.
Can we deploy it partially first?
Since this is a brand new design, with new data utilization, patterns, and animations, it takes a lot of development effort to achieve this feature fully.
Events integration
Local events drive significant demand spikes that many owners were missing entirely. I designed an events layer within MarketMaker that surfaces relevant nearby events — both owner-added and externally imported — so owners can adjust their strategy proactively rather than reactively.
"I wish I could see what events are coming up so I can adjust my prices. I'm not always updated with all the events."
This feature addresses the user feedback:
Showing only helpful information
I researched similar events panels, and brainstormed on the order name, address, time, description, etc. I landed on the layout you see above — focused only on the details most relevant to a homeowner's pricing decision. It doesn't have complex details about the event, just ones that are relevant for the homeowner.
Address
The location tells the user how far the event is from the property.
Dates
The dates tells the user which dates would the property rates be affected by the event.
Event added to which properties
This tells the user which of the user's properties are affected by this event.
Initial reactions upon release
After the initial release of MarketMaker, we tracked user feedbacks on MarketMaker. While there were all kinds of feedbacks, a majority of users shared similar concerns.
They don't know where to begin.
The users felt the MarketMaker interface was overwhelming to due to the excessive amount of data present. They had trouble interpreting where they were looking at.
They didn't know how to get to MarketMaker.
Most users we asked didn't even know how to get to MarketMaker from the dashboard.
Based on these feedbacks, I came up with 2 solutions.
1. Promote MarketMaker on the newsfeed.
Add MarketMaker opportunities to a newsfeed card. The user can conveniently see that Vrbo recommend certain dates to have lower rates. Interacting with the Opportunities in the dashboard can also get the user to get familiar with MarketMaker.
2. Onboarding tutorials
Early user testing revealed that MarketMaker's data-rich interface was intimidating to new users. I designed a step-by-step onboarding flow that introduced each feature progressively, reducing drop-off and building owner confidence from the first session.
Throughout the project I presented multiple design options at each stage, discussed tradeoffs directly with homeowners, and iterated based on their responses. The process was ongoing and collaborative by design.
Skill lessons or a tutorial?
The most common way for onboarding is a step by step tutorial to highlight product features. However, MarketMaker is essential for homeowner success, and I wanted to ensure that the homeowner becomes familiar with every feature of MarketMaker. While I designed an onboarding tutorial for first-time users, I also designed a Skills section that walks through every part of MarketMaker in detail. The Skills feature walks through every part of MarketMaker in detail, and is divided into 5 sections. The user can go through each part, and complete a section once every chapter of the section is completed.
The tutorial walks through the basic features for first-time users.
I also designed the tutorial for first-time users. The tutorial walks through basic parts of MarketMaker, and does the job of introducing the basics of MarketMaker. But for a user to be completely familiar with MarketMaker, the user would have to view the Skills feature.
Outcomes
Monthly active owners grew from 1.5M to 1.65M — a 10% increase. 33% of owners reported increased bookings after adopting MarketMaker's rate strategy tools. Owners saved an average of 18 minutes per session, and averaged 2 more bookings per month.
Owners who don't use MarketMaker (935k)
45%
of browsings turn into bookings
Owners who use MarketMaker (700k)
68%
of browsings turn into bookings
26%
revenue uplist for owners using strategy
18 min
saved per session
+2 more bookings / month on average
33%
more booking for MarketMaker users
52%
More self-reported success with bookings
10%
MAU growth:
1.5M → 1.65M active owners
What I'd do differently
Test the onboarding earlier with first-time homeowners. The Skills section came late in the process — a response to post-launch feedback that users didn't know where to begin. If I'd run usability testing with brand-new homeowners before launch, we likely would have caught the discoverability problem earlier and shipped a stronger first-time experience from day one.
Push for a mobile-first version. Most homeowners manage their properties on the go, but MarketMaker was designed desktop-first. In hindsight, I'd have advocated harder for a mobile experience from the start — the Opportunities newsfeed card we added later showed that owners responded well to timely, in-context nudges. That pattern should have shaped the whole product, not just one feature.
Question the data-first assumption sooner. We assumed that giving owners more data would give them more confidence. The real insight — that they needed less data, not more — only surfaced through the V1 feedback cycle. I'd push for that question in the research phase: "What would make you feel confident?" rather than "What data do you need?"
Define success metrics before designing. I learned the impact of MarketMaker through post-launch data, but the metrics weren't fully defined before I started designing. Aligning earlier on what "success" looked like — revenue lift, session time, booking rate — would have helped me prioritize features and make sharper tradeoffs.