Price Transparency, a Design Love Story
Old version of our price quote box—users needed to scroll halfway down the page before seeing the total price
Why share this study?
This is one of my favorite cases to share because it represents a special time at Evolve when product, design, and research were in a smooth, collaborative rhythm. As people began returning to the Denver office, I decided to dedicate time each week to in-person brainstorming.
It wasn’t just about discussion—we wanted to put pen to paper (or more often, marker to whiteboard) and get all our ideas out. I called it Wednesday Whiteboard Sessions. Each week, I looked forward to the lively discussions, sketches, and inevitable laughs that made these sessions so enjoyable. The solution for this case study came out of this time together.
User interviews Workshop facilitation Roadmap prioritization Prototyping A/B testing
The quick take (tldr version)
Company
Evolve is a property management company specializing in short term rentals, responsible for all the digital aspects of management such as dynamic pricing, listing maintenance and 24/7 guest support.
Problem
Price was a key factor for our guests, as confirmed by guest interviews. However, issues like inconsistent pricing hierarchy and excessive, distracting information in the display created confusion and uncertainty. This likely caused shoppers to leave Evolve altogether.
Solution
I created three new designs for A/B testing of the price display component on the listing page. Due to scope constraints, the team developed two of these designs for testing.
Result
Both variations outperformed the control, with the top-performing design achieving a 7.3% increase in booking conversion. We rolled out the winning design to 100% of traffic and saw a significant revenue boost.
A still from a zoom interview with a guest. When asked what builds trust in a brand, “Again that upfront price makes me feel like you’re trustworthy.”
The full length version (tldr)
Broad concepts to focused solutions
As a way to inform our roadmap, our team conducted five moderated guest interviews. We asked participants to walk us through their decision-making process when shopping for vacation homes. Unsurprisingly, price emerged as one of the biggest themes. From there, we brought this key question to our Wednesday whiteboard session: How might we optimize pricing data for guests? Our goal was to strike a balance between transparency and brevity.
After the session, my PM and I walked around the whiteboard, selecting ideas to move into the next phase—channeling our inner Tim Gunn and Heidi Klum with phrases like, "You're in!" or “Auf Wiedersehen!”
Photos from a brainstorm session on price transparency
Next, we recorded our favorite ideas as sticky notes in Miro and plotted them on an impact matrix. This was an effective way to prioritize solutions without getting lost in hypotheticals. To refine further, the lead developer and I assigned a "t-shirt size" (small, medium, or large effort) to each idea. As you can see from the screenshot, there were plenty of ideas to sort through!
After assessing the design and development lift, my PM and I selected five ideas to execute for the quarter. Each was suitable for an A/B test, and we hypothesized that they could significantly improve cart conversion. To keep things fun and aligned with our pricing theme, we named each test after a currency.
For this case study, I’ll focus on one project, dubbed Franc, where I optimized the price display container on the property page.
Emmanuel approves
Designing in Figma
Starting with simple wireframes, I incorporated elements of ideas proposed during our whiteboard sessions and developed the end-to-end functionality. The primary challenge in designing this interface was determining the optimal amount of information to display. Providing too much detail risked overwhelming users with a flood of numerical data, while revealing too little could lead to doubts about Evolve’s trustworthiness. Additionally, each calculation introduced potential performance risks to the page.
Wireframing ideas from Figma—some made the cut, others shaped the direction
I used our company watercooler Slack channel to gather qualitative data on the tax display
At the conclusion of the wireframe process, I selected three distinct designs for testing, each with varying levels of exposed data:
1 - Close-to-Current, this design closely resembled the existing interface but removed superfluous content and simplified the styling for clarity.
2 - Tabbyville, Inspired by United Airlines’ price breakdown, this design displayed high-level price information with the option to click or tap a "total price breakdown" tab for more detailed data.
3 - Leftside, this design incorporated the detailed price breakdown directly within the main content section of the page. Advantages included fewer required clicks, more space for viewing the price table, and exposed tooltips for additional clarity
To validate the designs before handing them off to developers, I conducted a quick usability test through UserTesting.com. The results revealed a near-equal split in preferences, with no significant opposition to any single design.
Final polish focused on a table-heavy display. Left to right: Close-to-current, Tabbyville, Leftside
A/B testing results
Given our limited development bandwidth, only the Close-to-Current and Tabbyville designs were implemented. After running the test for a few weeks, we collected enough data to establish statistical significance. (Drumroll...) Both variations outperformed the Control group! Close-to-Current emerged as the favored approach for the primary metric of completed bookings out of total visitors.
Key results
Total visitors: 322,369
Conversion metrics (listing to completed purchase):
Control: 1.23% (1,316 / 107,315)
Close-to-current (C2C): 1.32% (1,416 / 107,458)
Tabbyville: 1.27% (1,370 / 107,596)
Additional insights / secondary metrics
Close-to-Current had substantially stronger mobile performance compared to Tabbyville. However, both variations showed a lower listing-to-cart conversion rate on mobile. For Close-to-Current, this was -19.68% relative to the Control. This drop is likely attributable to the mobile footer experience, which displayed the total price upfront. By showing more price information earlier, we likely filtered out less serious "lookie-loo" shoppers.
Tabbyville demonstrated a 28% increase in listing-to-cart conversion on desktop. This suggests that the simplified experience with tabs effectively guided users further down the funnel. However, it wasn’t as effective in converting users through to checkout compared to Close-to-Current.
What I learned
Reaching the cart doesn’t always indicate a strong intent to purchase. Watching users on Hotjar jump in and out of the checkout flow has made me recognize this behavior in my own online shopping habits.
At the time this feature was developed, Airbnb—being the most popular booking platform—did not display the total price until the payment page. This made me hypothesize that users are conditioned to this pattern, and even if we show the price earlier in the process, people may still assume it isn’t final.
My biggest takeaway from this experience is realizing I’ve only scratched the surface of understanding how people perceive pricing. However, I’m pleased that by implementing our Close-to-Current variation, we’ve taken a small but meaningful step in providing guests with greater peace of mind regarding price transparency.