Mobile First · Neighborhood Finder · Research
Nextblock is a premier tool, matching movers to their ideal neighborhoods. At NextBlock, the mission is to empower individuals and families with the features and insights they need to discover their ideal neighborhood.
Moving to a new area should be an exciting and minimal stress experience, and the comprehensive analytics and personalized discovery tool are designed to make that a reality.
Sign up and researching a specific neighborhood
Can information ever be too abundant? In disorganized states it can certainly be overwhelming.
In the realm of neighborhood information, there's a wealth of data scattered across sources, creating a chaotic landscape. This disarray often results in confusion, frustration, and an overwhelming experience for individuals seeking their ideal place to relocate. Moving is already a substantial task; let's simplify the research phase.
My overarching objectives were:
Construct an analytics tool that seamlessly consolidates data into a single, user-friendly source.
Create a product that removes the guesswork from finding the perfect neighborhood match.
In April 2023, I spearheaded the design efforts for Nextblock, collaborating closely with Praveen Naga and a dynamic team comprising seven individuals, all of whom had undergone residential relocations within the previous two years. My leadership role encompassed various aspects, including research, interviews, wireframing, prototyping, and conducting usability testing.
Among the participants, we had a diverse range of backgrounds and expertise, including a product manager, a data scientist, a program manager, an educator, a UX researcher, a recruiter, and an IT consultant. This collective wealth of experience and skills allowed us to approach the project from multiple perspectives and ensure the comprehensive success of Nextblock.
KICKOFF
From the outset, it was crucial to recognize the abundance of pre-existing neighborhood information. Rather than engaging in direct competition with this wealth of data, the product seeks to leverage it to its advantage.
The primary focus of our initial research was to gain a deep understanding of people's decision-making processes when selecting a neighborhood for their relocation.
This entailed one key research goal:
Uncovering the factors that individuals consider when evaluating the desirability of a neighborhood.
Two pivotal research questions naturally emerged:
What motivates people to relocate to new areas?
Which resources do individuals typically rely on to inform their choices about where they want to reside?
USER FOCUSED RESEARCH
Drawing upon the data collected, I proceeded to craft two user personas. These personas were constructed to encapsulate the key characteristics and behaviors exhibited by the individuals who had been the subjects of the research studies. These personas serve as invaluable tools for understanding and empathizing with the needs, goals, and pain points of the target audience, ultimately guiding the design and development of the product.
In his quest to purchase his first home, Michael is thorough and intends to consider previously overlooked factors such as school districts and walkability in order to make an informed decision about the neighborhood.
Dori, venturing into the unfamiliar territory of New York City, navigates the daunting task of neighborhood selection, guided by her preference for vibrant "10-minute neighborhoods" where most essential needs are met within a 10 minute walk.
THE DISCOVERY
The interviews revealed that a significant portion of the interviewed individuals heavily relied on insights from locals when evaluating neighborhoods. They sought guidance and information from various sources within the local community, including family members, friends, colleagues, and community forums or boards.
When it comes to potential product features, participants expressed a strong desire to understand the local lifestyle and culture of prospective neighborhoods before making a commitment to relocate. In response to this preference, the concept of a neighborhood assessment or verification system emerged as a valuable feature. While quantitative data certainly holds importance, participants emphasized that the most influential factors in their decision-making process often stemmed from the experiences shared by locals about a particular place.
Another key objective was to streamline and simplify the neighborhood discovery process, making it as user-friendly and intuitive as possible to facilitate an effortless research experience. This is where the concept of a tool that could take user-inputted neighborhood preferences and match individuals with new places began to take shape.
The idea was to create a solution that not only provided data-driven insights but also took into account the personal preferences and priorities of users, ultimately guiding them towards neighborhoods that align with their unique needs and aspirations. This user-centric approach aimed to enhance the overall experience of finding the perfect place to live, combining the power of data-driven analytics with the personal touch of individual preferences.
DEEPER INSIGHTS
Before diving into design, I conducted a thorough analysis of the competition to gain insights into how they structured and presented information. Additionally, I assessed whether these competitors offered any tools or features designed to assist users in discovering neighborhoods that closely matched their personal preferences.
This competitive analysis was a crucial step in the design process, as it allowed me to identify industry best practices, understand user expectations, and pinpoint gaps or opportunities where our product could offer a distinct and valuable solution. By examining the strengths and weaknesses of existing offerings in the market, I could better inform the design decisions and feature development for our product, ensuring that it addressed user needs effectively and efficiently.
The competitive landscape highlighted a significant opportunity. Existing competitors either lacked standardized methods for users to crowdsource neighborhood information, as was the case with platforms like Best Neighborhood, or offered a chaotic and unstructured approach, like City-Data. Moreover, these platforms, while containing a wealth of information, faced challenges such as presenting data in a manner that could be overwhelming for users or implementing paywalls that restricted access to valuable content. This gap in the market presented a clear opportunity to develop a product that not only aggregated comprehensive data but also offered a user-friendly and organized platform for users to contribute and access neighborhood information effectively and without hindrances.
To enhance the aggregation of neighborhood information into a centralized platform and improve the experience of discovering new neighborhoods, I formulated the following problem statement and product goals:
How might we streamline the process of gathering neighborhood information from diverse sources and transform the way users explore and choose new neighborhoods?
By addressing these goals, I aimed to improve the way people access and contribute neighborhood information, making the process both informative and enjoyable while fostering a sense of community engagement.
A FRESH APPROACH
As the concept of using a questionnaire to match individuals with neighborhoods took shape, a parallel revelation emerged: the process of matching people to neighborhoods based on personal preferences bears a striking resemblance to how dating apps collect user preferences and then suggest potential matches. While not a perfect analogy, it shares similarities in allowing users to quickly eliminate options that don't align with their non-negotiable criteria, streamlining the decision-making process and increasing the likelihood of finding a suitable match. This comparison highlights the potential for a more user-friendly and efficient approach to neighborhood discovery.
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 an enjoyable and 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 the process of brainstorming product names aligned with the brand values, I initially generated a list of 10 potential options. After careful consideration, I narrowed down the choices to two strong contenders: "Neighbarometer" and "NextBlock."
While "Neighbarometer" was appreciated for its wordplay, the final decision leaned towards "NextBlock" for several compelling reasons. "NextBlock" emerged as the chosen name due to its clarity, simplicity, ease of pronunciation, and direct descriptiveness. This name effectively conveys the product's purpose and aligns seamlessly with the brand identity and values.
The initial stage of product development had me charting out user flows, with a primary emphasis on key interactions. These included the processes for signing up, signing in, logging in and out, and utilizing neighborhood search tools. This foundational work laid the groundwork for the user-centric experience that the product aims to deliver.
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
The initial vision was to present all the questionnaire categories on one page. However, inspired by OKCupid's methodology, my product's questionnaire adopted a similar approach which itemizes questions one at a time. It initially establishes non-negotiable parameters and subsequently poses questions to explore further preferences. This sequential format minimizes user overwhelm, making the process more manageable and user-friendly.
OkCupid's questionnaire layout
PRODUCT DEVELOPMENT
The creation of the NextBlock logo drew inspiration from two fundamental icons: the location pin and the search icon. Both circular forms were perfect for superimposition. Through a series of rotations and scaling adjustments, the final silhouette of the NextBlock logo was created, symbolizing our brand and product.
The color palette for NextBlock was carefully chosen, with teal and its cyan relatives taking center stage. These hues carry a host of positive associations, including friendliness, happiness, freshness, stability, and harmony. Teal, in particular, strikes a balance between cleanliness and warmth, avoiding the sterility often associated with some clean tones.
The inspiration for this color theme drew from the company Mint, known for its financial planning tools. While financial planning can be a stressful process, Mint successfully transforms it into a calming and straightforward experience through its soothing color palette. Much like planning a move to a new neighborhood, financial planning can benefit from an aesthetic that conveys simplicity, freshness, and a sense of ease. This choice of color palette for NextBlock aligns with the brand's goal of offering users a calm and inviting experience when 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 has been clarified to improve user comprehension and streamline the information-gathering process.
Enhanced Accessibility: Greater accessibility has been provided to the neighborhood analytics and neighborhood finder tools, making them more readily available and user-friendly.
User interface: The user interface has been refined to enhance visual aesthetics and usability, ensuring a more appealing and intuitive experience.
These improvements are instrumental in optimizing the user experience. A more efficient product plays a pivotal role in bolstering users' confidence when it comes to making the significant commitment of choosing a new neighborhood. By streamlining the process, enhancing usability, and providing clear and accessible tools, the product empowers users to make informed decisions and embark on their journey to a new neighborhood with greater assurance and peace of mind.
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 to call home. By aggregating comprehensive neighborhood data into one accessible source, NextBlock simplifies the complex task of neighborhood discovery. Our user-friendly interface presents this data in an easily digestible format, allowing you to explore neighborhoods effortlessly.
What sets NextBlock apart is our unique questionnaire that delves into your personal preferences, helping you uncover neighborhoods that align with your lifestyle. Whether you're seeking a vibrant urban center or a tranquil suburban haven, NextBlock empowers you to compare and contrast neighborhoods, making the process both informative and enjoyable. Say goodbye to the stress of searching for neighborhoods and say hello to your next ideal community with NextBlock.
Filling out neighborhood matching making questionnaire
FINAL THOUGHTS
Given time constraints, I had time to mainly focus on the data analytics and neighborhood finder features of the product. With more time, I would like to develop the profile dashboard and spend time on designing the activity log and feed components. The activity log and feed components can play a crucial role in enhancing the user experience and providing valuable information. Here are some potential features and content that could be featured in these components:
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.
