CAPSTONE W/ GOOGLE
APARTMENTS ON
GOOGLE MAPS
Reimagining the apartment searching experience with Google Maps
Timeframe
1.2020 - 6.2020
Role
Product Designer, Researcher
Team
Ivy Zhang, Yuan Yuan, Joyce Lu
Background
Why do we have to switch between so many tools when apartment searching?
With so many tools online, however, apartment hunters are still struggling. We have observed that a lot of people having Google Maps and many other tabs open when they start their initial searching online. What information is people looking for and is missing from Google Maps? Why can't we have a one-stop service on Google Maps, supporting by Google's powerful ecosystem to optimize apartment searching experiences?
Research Approach
A combination of research methods
Google Maps serves a variety groups of customers. To understand better about the rental market, apartment-rental oriented online services, as a team, we have conducted extensive Market Research, Competitive Analysis, followed by User Interviews to learn about the user group, their tool using and apartment searching experience:
Target User
Incredibly mobile young millennials
Based on market research, young millennials (age 25 -29) is the most impactful target user group in the rental market. They have the highest moving rate (45.3% move into their place less than 2 years) and low home ownership (33%).
Different Needs at Different Stage
Based on user interview insights, I have mapped out the apartment searching experience into 4 stages after synthesizing our data. After evaluating our time and prospective impact, as a team we decided to focus on the Information Gathering and Touring phases.
Defining MVP
Apartment Searching on Google Maps
After scoping down the problem space, as a team, we have identified two critical use cases to map user pain points to actionable and impactful design directions below. I took the lead in the designing of this part of the MVP experience:
1. Know more about the city and the neighborhood to decide where to live
2. Refine apartment searches based on commute and more
1. Know more about the city and the neighborhood to decide where to live
2. Refine apartment searches based on commute and more
Goal #1: Know about the city and neighborhood
A dedicated neighborhood page
To meet the first goal of giving apartment searchers just enough information about the surrounding and the area, I ideated and created several draft proposals for the neighborhood page.
Rapid Iterative Testing and Evaluation (RITE)
Instead of waiting til the end for usability testing, we decided to conduct RITE (rapid iterative testing and evaluation) to receive early feedback and be able to iterate and improve on every rounds of feedback.We in total conducted 2 rounds of RITE with 3 participants for each round (6 participants in total!) and 1 formal round of usability testing with 5 participates.
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The Challenge #1
Discover what do people care about the neighborhood
I made my first assumption based on competitive analysis and user interview insights that there are four main information people care about are:
- Safety (No.1 most concerned among all participants)
- Commute Information ("...how easy to get around")
- Average Rental Market/Price ("...how expensive this area is")
- Surrounding business ("...I want to know about business activity around")
- Safety (No.1 most concerned among all participants)
- Commute Information ("...how easy to get around")
- Average Rental Market/Price ("...how expensive this area is")
- Surrounding business ("...I want to know about business activity around")
CONS:
- Sections are stacked together, it's hard to scan at a glance.
- Some detailed information we chose under each section is reported as not understandable or helpful (details below).
- Sections are stacked together, it's hard to scan at a glance.
- Some detailed information we chose under each section is reported as not understandable or helpful (details below).
Visual Design For Neighborhood Page
In order to maintain the visual design consistency between Google products on neighborhood related information, I took the inspiration from Google Hotel and re-organized all the sections:
SAFETY SECTION
In order to maintain the visual design consistency between Google products on neighborhood related information, I took the inspiration from Google Hotel and re-organized all the sections:
Version 1:
Originally, I picked two data points from the Seattle Police Department website for an area:
- Total number of cases in Offense Court
- Crime Density per sq mi
Originally, I picked two data points from the Seattle Police Department website for an area:
- Total number of cases in Offense Court
- Crime Density per sq mi
CONS:
Though data points are coming from official government website, they did not create a lot of meaning and prompted actions among the audience.
Though data points are coming from official government website, they did not create a lot of meaning and prompted actions among the audience.
Final Design:
More understandable safety terms
Thus, I conducted a quick research to understand what about safety that makes the most sense to residents. I came back with below sub-concepts under Safety:
- How busy the street
- If the street has sidewalks and street lights
- How safety for females to walk at night
- ...
After consulting on other safety data provider (e.g. trulia) and considering the data that Google has been collecting or has the potential to collect, I came up with 3 concepts to convey the level of safe which makes more sense to users.
TRANSIT SECTION
In order to maintain the visual design consistency between Google products on neighborhood related information, I took the inspiration from Google Hotel and re-organized all the sections:
Version 1:
To maintain the visual consistency of presenting information about bus lines, I adopted the same visual style to present a specific bus line, and all its stops within this neighborhood. Additionally, users can put in the work address and see work related transit information.
To maintain the visual consistency of presenting information about bus lines, I adopted the same visual style to present a specific bus line, and all its stops within this neighborhood. Additionally, users can put in the work address and see work related transit information.
CONS:
However, based on the RITE feedback, the above information I tried to convey was not being understood by users. Users view the bus card as bus schedule, rather than bus line/stops overview.
However, based on the RITE feedback, the above information I tried to convey was not being understood by users. Users view the bus card as bus schedule, rather than bus line/stops overview.
Final Design:
Better visual representations
Thus, I did a few rounds of iterations and did following incremental changes:
- Bringing the Highway sub-section out from the Public Transportation dropdown to bring visibility.
- Reorganized bus information by bus lines, and using the accordion design to show specific bus stops.
- Not replacing, but showing both general and work related transit information after work address has been put in.
Better visual representations
Thus, I did a few rounds of iterations and did following incremental changes:
- Bringing the Highway sub-section out from the Public Transportation dropdown to bring visibility.
- Reorganized bus information by bus lines, and using the accordion design to show specific bus stops.
- Not replacing, but showing both general and work related transit information after work address has been put in.
The Challenge #2
WHERE and HOW do we introduce the neighborhood page
During RITE, I have found that version 1 with the separate entry point, the neighborhood guide has low discoverability and it doesn’t align with users’ mental model.
With version 2, though it increased the visibility, its visual representation is not making enough different from an apartment listing, along with its intrusive format.
With version 2, though it increased the visibility, its visual representation is not making enough different from an apartment listing, along with its intrusive format.
In the final design, I decided to update the entry point of neighborhoods to incorporate it in every single apartments. Therefore, it could not only provide contextual information about which neighborhood this apt belongs to, but also provide an easy entry point to detailed neighborhood page. We also updated the user flow to apartment - neighborhood page - neighborhood guide.
Goal #2: Don’t want to live too far from work
A Powerful Commute Filter
12 out of our 13 interview participants mentioned that "commute is important", "I want to see how long it takes to go to the office.". Therefore, I decided to utilize the Google Maps transportation data to best support our users' apartment searching experience.
Challenge
If the commute filter panel is easily understandable
During the design exploration, I aimed to have the filter to filter on 3 areas:
- By commute type (e.g. bus, drive)
- By commute time
- By rush hour data
Thus, I did a few rounds of iterations on the interaction patterns as well as the copy for the option to use the "Rush Hour" data instead of current time data.
- By commute type (e.g. bus, drive)
- By commute time
- By rush hour data
Thus, I did a few rounds of iterations on the interaction patterns as well as the copy for the option to use the "Rush Hour" data instead of current time data.
Reflection
Key Learnings and Process Improvements
Designing for scalability
Current design for neighborhoods is targeted around apartment searching experience, however, in real scenario, people are searching for neighborhoods for multiple purposes. it's a question for us to think how can we design for scalability.
Striving for the entire user journey
Searching for apartments is a long long journey. Indicated from my user research, users not necessarily start from Google Maps. The entry point could vary from Google search, other rental sites or simply from the physical ads on the streets. Therefore, when designing for apartment searching experience, I need to consider not only how users search on Maps, but how they start, how they proceed to how they actually decide.
Designing within the Google Ecosystem
Beyond this MVP product, we want to explore more integration between maps and google productivity tools like drive, calendar, gmail to design for more scenarios, including the ones we identified but couldn't accomplish in this project, for example co-searching experience with a partner/roommate.
Current design for neighborhoods is targeted around apartment searching experience, however, in real scenario, people are searching for neighborhoods for multiple purposes. it's a question for us to think how can we design for scalability.
Striving for the entire user journey
Searching for apartments is a long long journey. Indicated from my user research, users not necessarily start from Google Maps. The entry point could vary from Google search, other rental sites or simply from the physical ads on the streets. Therefore, when designing for apartment searching experience, I need to consider not only how users search on Maps, but how they start, how they proceed to how they actually decide.
Designing within the Google Ecosystem
Beyond this MVP product, we want to explore more integration between maps and google productivity tools like drive, calendar, gmail to design for more scenarios, including the ones we identified but couldn't accomplish in this project, for example co-searching experience with a partner/roommate.