About the project

Goal

Generate trust for hosts to boost conversion and empower cleaners by using data to highlight their real value in a way that feels clear and credible

Impact

from 21.5% to 26.9%

Conversion rate lift

Context

The project started as a Preferred subscription giving cleaners badges and priority in searches. This aimed to build trust with hosts to improve conversion.

When mapping out the program, we realized it would be quite complex and impact many areas:

1st A/B Test

Instead of building the full program, we decided to test the assumption if a change like a Preferred badge on the cleaner would:

1

Increase the chances from a cleaner of being accepted by the host by having the Preferred badge

2

Increase host conversion when they are picking cleaners with the Preferred badge

1

Increase the chances from a cleaner of being accepted by the host by having the Preferred badge

2

Increase host conversion when they are picking cleaners with the Preferred badge

1

Increase the chances from a cleaner of being accepted by the host by having the Preferred badge

2

Increase host conversion when they are picking cleaners with the Preferred badge

The results

We saw cleaners with the badge were selected more often, but overall conversion dropped slightly (~1%) when looking at completed projects.

Control

7.32%

Accepted bids

21.84%

Conversion

Variant

8.67%

Accepted bids

20.88%

Conversion

Insights

  • The badge was not tied to real performance, which limited effectiveness.

  • The top cleaner was not always the first to bid, which meant lower performers were sometimes featured.

  • Hosts didn’t clearly perceive the badge value whether it was real or perceived

Showing the real value of cleaners with credible data was key to building host trust.

Showing the real value of cleaners with credible data was key to building host trust.

Gathering info for v2

Based on the insights, we explored what hosts truly value when selecting cleaners.

I worked with Data, Research, and Sales teams to define how to recommend cleaners in v2

Based on the insights, we explored what hosts truly value when selecting cleaners. I worked with Data, Research, and Sales teams to define how to recommend cleaners in v2

Research

UX Research helped us gathered some info by running a multi-select survey to know hosts' key factors when accepting cleaners bid.

Data

With the Data team, we explored what existing data could help us show cleaner value, without needing to track new events.

Benchmark

We compared how other apps were highlighting some specific elements of the UI to build trust and help user make decisions:

  • Airbnb: “Superhost,” “Guest Favorite”, “Rare finds”

  • Amazon: “#1 Best Seller”

  • Booking.com: “Highly rated”, “Most booked”, taking reviews up to the top

  • Netflix: Added trusted sources below titles like “Oscar winner”, “Top 10 this month”

  • Airbnb: “Superhost,” “Guest Favorite”, “Rare finds”

  • Amazon: “#1 Best Seller”

  • Booking.com: “Highly rated”, “Most booked”, taking reviews up to the top

  • Netflix: Added trusted sources below titles like “Oscar winner”, “Top 10 this month”

  • Airbnb: “Superhost,” “Guest Favorite”, “Rare finds”

  • Amazon: “#1 Best Seller”

  • Booking.com: “Highly rated”, “Most booked”, taking reviews up to the top

  • Netflix: Added trusted sources below titles like “Oscar winner”, “Top 10 this month”

2nd A/B Test

We tested a new way to highlight cleaner value using data-based cards. The goal was to make the information easy to understand and credible for hosts.

Results & Impact

The test improved across all key metrics, showing that hosts trusted clear information and felt more confident choosing cleaners with proven value

Control

7.32%

Accepted bids

21.52%

Conversion

Variant

11.67%

Accepted bids

26.88%

Conversion

Final Reflections

More Than Just Visuals

My role was about turning backend data into something users could trust. I worked with other teams to make information clear for hosts and empowering for cleaners

Don't be afraid of change

We invested a lot in the Preferred Cleaner program, but fresh perspectives could bring better paths. Finding constraints early could lead to stronger decisions!

Other Projects

Feature Onboarding

A new onboarding experience to reduce early churn, increasing by almost 9pp the cleaner searches created 

Quality Center

A dashboard to help hosts improve their Airbnb cleanliness rating, driving 3× more monthly integrations

Let's talk!

Made by Agus with

Let's talk!

Made by Agus with

Let's talk!

Made by Agus with