Mobile First · Neighborhood Finder · Research
NextBlock is a premier tool that helps match movers to their ideal neighborhoods. Its mission is to empower individuals and families with the insights needed to find the perfect community.
NextBlock aims to make moving an exciting, low-stress experience through comprehensive analytics and personalized discovery.
Sign up and researching a specific neighborhood
Can information be too abundant? When disorganized, it can definitely be overwhelming.
Neighborhood information is scattered across various sources, creating a chaotic landscape that leads to confusion and frustration for those seeking their ideal place to relocate. Moving is already a big task—let’s simplify the research phase.
My overarching objectives were:
Build an analytics tool that consolidates data into one user-friendly source.
Develop a product that eliminates the guesswork in finding the perfect neighborhood.
In April 2023, I led the design of NextBlock, collaborating with Praveen Naga and a team of seven who had relocated within the past two years. My role included research, interviews, wireframing, prototyping, and usability testing.
The team had diverse backgrounds, including a product manager, data scientist, program manager, educator, UX researcher, recruiter, and IT consultant. This diversity ensured a well-rounded approach and comprehensive success for NextBlock.
KICKOFF
Recognizing the abundance of existing neighborhood information, our goal was not to compete but to leverage it effectively.
Our initial research focused on understanding how people decide on a neighborhood when relocating.
This entailed one key research goal:
Identifying the factors people consider when assessing a neighborhood's desirability.
Two pivotal research questions naturally emerged:
What motivates people to relocate?
What resources do people use to decide where to live?
USER FOCUSED RESEARCH
Using the collected data, I created two user personas that encapsulate the key traits and behaviors of the research participants. These personas help understand the needs, goals, and pain points of the target audience, guiding the product's design and development.
Michael, looking to buy his first home, is thorough and plans to consider factors like school districts and walkability to make an informed neighborhood choice.
Dori, new to New York City, is navigating the challenge of neighborhood selection. She prefers vibrant "10-minute neighborhoods" where essentials are within a 10-minute walk.
THE DISCOVERY
The interviews showed that many participants relied on local insights when evaluating neighborhoods. They sought guidance from family, friends, colleagues, and community forums.
Participants expressed a strong desire to understand the local lifestyle and culture of prospective neighborhoods before relocating. In response, a neighborhood assessment or verification system was proposed. While quantitative data is important, participants emphasized that insights from locals were often the most influential factors in their decisions.
A key objective was to simplify the neighborhood discovery process, making it user-friendly and intuitive. This led to the concept of a tool that matches users with neighborhoods based on their inputted preferences.
The solution aimed to provide data-driven insights while considering users' personal priorities, guiding them toward neighborhoods that align with their unique needs. This user-centric approach combined data analytics with personalization to enhance the experience of finding the perfect place to live.
DEEPER INSIGHTS
Before starting the design, I analyzed competitors to understand how they structured and presented information, and whether they offered tools for matching neighborhoods to users' preferences.
This competitive analysis was crucial for identifying industry best practices, user expectations, and gaps or opportunities. By assessing the strengths and weaknesses of existing offerings, I informed design decisions to ensure our product effectively addressed user needs.
The competitive landscape revealed an opportunity: existing platforms either lacked standardized ways for users to crowdsource neighborhood info (e.g., Best Neighborhood) or offered chaotic, unstructured data (e.g., City-Data). While rich in content, these platforms often overwhelmed users or restricted access with paywalls. This gap presented an opportunity to create a product that aggregates comprehensive data while offering a user-friendly, organized platform for user contributions and easy access—free from barriers.
To centralize neighborhood information and improve the discovery experience, I formulated the following problem statement and product goals:
How can we streamline gathering neighborhood information from diverse sources and transform how users explore and choose new neighborhoods?
By pursuing these goals, I aimed to enhance how people access and contribute neighborhood information, making it informative, enjoyable, and fostering community engagement.
A FRESH APPROACH
As the concept of using a questionnaire to match users with neighborhoods developed, I realized it resembled the approach used by dating apps: collecting preferences to suggest matches. Though not a perfect analogy, it similarly helps users quickly eliminate options that don't meet their criteria, streamlining decision-making and improving the chances of finding a suitable match. This comparison highlights the potential for a more user-friendly, efficient neighborhood discovery process.
In my pursuit of innovation and setting my product apart from competitors, I conceived two distinctive concepts:
Community Validation: Recognizing the universal appreciation for third-party validation, I envisioned a platform where prospective residents could vet reviews from informed locals to validate potential neighborhood experiences.
Neighborhood Matchmaker: Envisioned as a user-friendly, dating-inspired questionnaire, this feature intelligently matches individuals with their ideal neighborhoods. It simplifies the quest for the perfect place to live, creating a personalized journey akin to finding a partner.
Many individuals possess an innate sense of what resonates with them but face challenges in articulating these preferences. The product would be designed to facilitate the articulation and understanding of user's desires.
Community Validation
Review form
Report card
Neighborhood Matchmaker
Questionnaire
Results
BRINGING IT TO LIFE
In brainstorming product names, I generated a list of 10 options and narrowed it down to two: "Neighbarometer" and "NextBlock." While "Neighbarometer" had appealing wordplay, "NextBlock" was ultimately chosen for its clarity, simplicity, easy pronunciation, and direct descriptiveness, effectively conveying the product's purpose and aligning with the brand's identity and values.
In the initial stage of product development, I mapped out user flows, focusing on key interactions like signing up, logging in/out, and using neighborhood search tools. This foundational work set the stage for a user-centric experience.
OKCupid has gained recognition for its effective matchmaking algorithm and questionnaire, which have proven successful for various compelling reasons:
In depth questions
Algorithm-based matching
User-friendly interface
Transparent compatibility scores
Inclusivity
Initially, I planned to present all questionnaire categories on one page. Inspired by OKCupid, I instead adopted a one-question-at-a-time approach, starting with non-negotiable parameters and then exploring preferences. This sequential format reduces overwhelm, making the process more manageable and user-friendly.
OkCupid's questionnaire layout
PRODUCT DEVELOPMENT
The NextBlock logo was inspired by two fundamental icons: the location pin and the search icon. By superimposing, rotating, and scaling these circular forms, I crafted the final silhouette, effectively symbolizing the brand and product.
NextBlock's color palette centers on teal and its cyan relatives, conveying friendliness, freshness, stability, and harmony. Teal balances warmth with cleanliness, avoiding the sterility of some clean tones.
Inspired by Mint's calming color scheme, which makes financial planning feel simple, I aimed for a similar effect with NextBlock. The goal is to offer a calm, inviting experience for users exploring and choosing their ideal neighborhoods.
FROM PROTOTYPE TO FINAL PRODUCT
Following the development of high-fidelity wireframes, usability testing was conducted with a sample group of five adults to evaluate the ease of performing critical tasks, including:
Account Creation and Accessing the User Dashboard
Researching a Place to Live
Locating Comparable Neighborhoods
Completing the Questionnaire to Discover Ideal Neighborhood Matches
This testing phase was essential in assessing the user-friendliness and efficiency of the product's interface and functionality.
The testing process yielded valuable insights, leading to key improvements in the product's design and usability:
Questionnaire Verbiage: Key wording in the questionnaire was clarified to enhance user comprehension and streamline information gathering.
Enhanced Accessibility: Accessibility to the neighborhood analytics and finder tools has been improved, making them more user-friendly and easily available.
User interface: The user interface was refined to improve aesthetics and usability, providing a more appealing and intuitive experience.
These improvements optimize the user experience, helping users feel confident when choosing a new neighborhood. By streamlining processes, enhancing usability, and providing accessible tools, the product empowers users to make informed decisions and approach their move with greater assurance.
Before
After
accessibility
Improved accessibility on the profile page to the two main features of the product:
Neighborhood analytics
Neighborhood finder
Before
After
VERBIAGE
Clarified ambiguous and confusing wording throughout the questionnaire. Provided more multiple choice options.
Before
After
USER INTERFACE
Refined the visual design and navigation experience. Reinforced the primary color scheme and improved overall visual consistency.
The design
NextBlock is your all-in-one solution for finding the perfect neighborhood. By aggregating comprehensive data into a single, accessible source, NextBlock simplifies neighborhood discovery. Our user-friendly interface makes exploring neighborhoods effortless.
What sets NextBlock apart is our unique questionnaire, tailored to your preferences, helping you find neighborhoods that match your lifestyle. Whether you want a vibrant urban center or a tranquil suburban haven, NextBlock empowers you to compare neighborhoods easily. Say goodbye to the stress of searching and hello to your ideal community with NextBlock.
Filling out neighborhood matching making questionnaire
FINAL THOUGHTS
Due to time constraints, I primarily focused on the data analytics and neighborhood finder features. With more time, I’d like to develop the profile dashboard and design the activity log and feed components, which could significantly enhance the user experience. Potential features for these components include:
Activity Log:
User Activity: Display a log of the user's recent actions within the app, such as neighborhoods they've explored, ratings and reviews they've provided, or neighborhoods they've saved to their profile.
Notifications: Notify users of important updates, such as when a neighborhood they follow receives new reviews or when there are changes in the neighborhood rankings.
Feed Component:
User Posts: Allow users to share their experiences and thoughts about neighborhoods through posts. These posts could include photos, written reviews, and rankings of specific features within a neighborhood.
Trending Neighborhoods: Highlight neighborhoods that are currently trending or gaining popularity among local residents, based on recent user activity and reviews.
Featured Content: Showcase particularly insightful or popular user-generated content, helping users discover the best recommendations and insights from the community.
By incorporating these features into the activity log and feed components of NextBlock, users can engage with the platform more effectively, discover new neighborhoods, and tap into the collective knowledge and experiences of the local community, making their neighborhood exploration journey more informative and enjoyable.
