Quality Center
New Feature
tl;dr
Problem
Airbnb hosts were receiving cleanliness ratings on each review, but they couldn’t connect them back to specific cleaners who worked before the guest staying. Although the feedback was there, there was a lack of visibility to take action and improve the overall cleaning quality.
Goal
Leverage Airbnb’s API to connect cleanliness ratings to specific cleaning projects and cleaners to identify patterns, and improve their property’s cleanliness rating.
Impact
It became one of the most referenced features in onboarding and sales demos
Increased Airbnb integration growth from 2% to 6% monthly.
Quality center became one of the most used feature among users integrated with Airbnb
How it all started
Context
Hosts could see those ratings on Airbnb but they couldn’t do anything with them on Turno.
A 2-star cleanliness review might show up, but what could the host actually do with it?
Finding a clear path
During early explorations, the CEO made a comment that reframed the problem that started us thinking about how hosts could rely on to make decisions:
Opportunities
Technical Feasibility
To explore what was technically feasible and where the value might be, we collaborated with the integrations team to investigate Airbnb’s API.
We identified several key data points we could retrieve:
Guest cleanliness scores
Booking metadata (check-in/out dates, listing ID)
Review tags
Other category scores (e.g., value, location, accuracy)
This gave us a much clearer picture of what we could build: A full connection path between the review and the people responsible for the cleaning job
Architectural decisions
We mapped out the feature’s architecture based on the questions hosts needed to answer to improve their rating.
Overview Tab
See overall rating, spot cleanliness trends from all listings and cleaners
Cleaners Tab
Track individual cleaner performance and compare with historial trends
Properties Tab
Reviews Tab
Read, filter, and analyze every review that appears in one place
Properties Tab
This tab helped hosts see how each of their listings was performing in cleanliness.
Iterations
In the early versions, we explored giving hosts a lot of control:
But we quickly realized:
Too had much data, too many colors and difficult to scan
It was hard to understand where to focus
Tight deadlines meant we needed to find the core value fast and simplify the UX around it
Final version
We put the focus on helping hosts identify patterns and take action
For mobile, due to the amount information that the Property Tab has, we needed to split the screen into 3:
Cleaners Tab
Final version
Important edge cases
To protect cleaners from being blamed for issues that happened long after they worked, we decided that reviews will only be linked to cleaners if the cleaning happened within 14 days before guest check-in, as guests usually rate cleanliness based on the condition of the property when they arrive.
Cross-functional work
While I co-led the designs, this project was built by working with multiple departments:
Working with the Product Team (My Team):
Reviewing flowcharts, layout, copywriting and discussing about edge cases
Working with Engineers:
Mapping all possible constraints that may appear while working with the Airbnb API (e.g property being deleted, access permissions, etc)
Working with Stakeholders:
Weekly meetings to show progress of the overall project, refining what could be launched on the MVP and making sure we were following the big picture of what this feature could add value to hosts
Business Impact
Airbnb Integrations Took Off
Before QC
Jun - Aug 2023
2%
growth per month
After QC
Sep 2023 - Jun 2024
6%
growth per month
Why does integration matters for the business?
When a host connects their Airbnb account with Turno, it opens the door to revenue opportunities:
Daily favorite among users
Post-launch Mixpanel data revealed Quality Center ranked as one of the most visited pages by Airbnb-connected users (with at least one visit per user per day).
Final Reflections
Good UX isn’t always visual.
Sometimes it’s in the default logic, designing fair and invisible rules, aligning data with user expectations, or thinking about the edge cases that almost never happen.
Clarity is what makes data valuable.
It’s how the data is presented, and the context around it, that turns it into something people can take advantage of.
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