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Zillow Places

UI Design
Prototyping

Cheryl Chan
Fran Breden
Sumeet Anand
Armina Foroughi

Renting is frustrating.

With housing prices on the rise, renting is becoming a reality for more and more people. Yet the process of renting hasn’t changed much in the past few years, it’s still a shot in the dark for most people and it’s only getting harder. Zillow is the most visited real estate site in the US, but home ownership is trending down. It’s critical to capture the rental market because eventually most renters become buyers. 

Getting to know our audience

Our approach was to target the extreme use case of people moving from city to city. If we could design a solution that resolved very stressful experiences then casual users would also find it easier. We conducted some guerrilla user interviews and asked people questions like:

How long did you expect this process would take? How long did it actually take?
How did you verify a posting?
What were the requirements that dictated your ideal choice?
If you could change one thing about renting, what would it be?

"Finding this place was a lot of searching on Craigslist, and emailing, and hearing nothing back"
"I kept track of [listings I emailed] with a google spreadsheet."
"I had no idea about neighbourhoods. Would I be close to a grocery store, bar, park?"

9 people were recruited for interview in Facebook housing groups.

Taking a page from Maslow

If we think about product within the context of Maslow's hierarchy of needs, Craigslist fufills the pyramid at the most basic level. It's a specific type of tool for fufilling a specific type of task: searching for listings. Yet this is only a small part of a much larger goal: finding a home. To innovate, we can't just make a better version of Craigslist. 

User goals become more qualitative once basic needs are met.

A better experience means understanding people's aspirations beyond just needs.

Lessons from other domains

Dating apps have a sense of emotional depth and already laid the groundwork for finding people or places within very specific parameters. They take all the work away from finding someone and just focuses on picking the right one. Why don’t we take out all the manual work of finding a home and focus on creating a more personal experience? 

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Early ideas I mocked up ranged from reading, machine vision to news apps.

Building a product that understands people

The personalization process extends across the user journey.

The core concept is that the app uses machine learning to curate a selection of places that best match your profile. However the challenge is that this system relies heavily on user input, which can increase cognitive overhead. To address this, the app progressively collects data in three stages:

1. First time sign up
During onboarding we strike a balance between time-to-value and gathering enough information.

2. Favourites
Favouriting a place will narrow the home feed parameters over time. 

3. Updating parameters
Users can change their answers at any time within the context of a detail view.

Focus on photography

Photography is so important in evaluating a listing so I designed the interface to really feature imagery. Most competitors put images in a gallery view but research shown here, here & here suggests scrolling is easier than clicking. In addition to that, browsing becomes faster in a much more visual way. 

Neighbourhoods in context

Personalization extends to map views which show things most relevant to you. I designed this with a human-centred mindset, showing distances in walking time versus in kilometres. 

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I designed a flow for listing a place with a focus on making it fast and easy.

Relationships that last

This idea of personalization can be applied across Zillow’s suite of apps. Log into Zillow Real Estate and it can tailor the service to provide value immediately. This tight integration of product can ultimately create a continuous experience and serve people at every step of their customer journey. 

More relevant ads

Zillow Places can help make ads more relevant and meaningful. Advertisers can now target to specific groups of people based off their profile which in turn drives higher engagement and profit. 

Thinking about real world use cases

We created this very image-heavy experience, but in the real world most users aren’t going to upload professionally shot images. This is actually a really hard problem, how do you maintain quality when you can’t control the content? I think a place to start is creating some automatic photography tools to guide users to take the best picture possible. 

Data is there to inform, not define the design.

We interviewed a few people and while the feedback was very insightful but it was clear that we couldn’t implement every feature they requested. A great quote I heard a few years ago went “users can tell you you’re wrong, but they can never tell you how to be right”. 

James Wang © 2018