Locale Lens
Find streets that fit your life
Locale Lens turns guesswork into confidence.
Home-buyers spend a median 10 weeks searching, renters wrap up in just 27 days, yet 82% of recent movers admit they regret the neighbourhood they chose. Our app reverses that risk: filter streets by schools, transit, parking and local services so you land where life actually fits.
The problem
Neighborhood data lives in too many places. Movers spend hours hopping between Facebook groups, city sites and word of mouth to check schools, parking and transit, yet still make a pressured choice, unsure they’ve picked the right street.
Solution
Our app centralizes all essential information for finding a new neighborhood. Users can input an address or apply filters to access tailored data on schools, public transportation, parking, and local businesses.
This simplifies the search process, making the transition to a new home seamless and stress free.
Research
Research approach & key insights
We began with a mixed methods study to uncover how people actually choose a street, not just an apartment. First, we ran 15 semi-structured interviews with recent movers across Tel Aviv, Jerusalem and Haifa. Their stories shaped a 20 question survey that reached 146 respondents. We also audited five leading property apps to map feature gaps. Three themes emerged:
78%
Said commute time and nearby services outweighed square meter size in the final decision
61%
Pieced details together from forums, Facebook groups and city websites because no single app surfaced street level data
76%
Locked in a neighbourhood within two weeks of short listing, leaving almost no time to double-check their choice
These findings framed our product goal: surface verified, street level insights (schools, transit, parking, services) in one place and make them filterable in seconds, so users can decide quickly without post move regret.
Competitor
Research
Competitor Research
I benchmarked three reference products Zillow, Trulia, and Nextdoor by mapping their core flows, rating them against a 10 point heuristic checklist, and collecting basic usage stats:
- Zillow (≈ 200 M monthly visitors) gives Walk/Transit scores per listing but no way to compare whole streets side by side.
- Trulia (≈ 8 M monthly visits) adds neighbourhood photos and reviews, yet filters stop at price and bedrooms.
- Nextdoor (≈ 46 M weekly active users) offers hyper local chatter, but its posts are noisy and unstructured for first-time movers.
Key gap: none of the three lets users layer verified Street level essentials into one filterable map. That insight shaped Locale Lens’s goal: a single-tap, data driven view that turns neighbourhood guesswork into confident decisions
Persona
User Flow
Competitor Research
I benchmarked three reference products Zillow, Trulia, and Nextdoor by mapping their core flows, rating them against a 10 point heuristic checklist, and collecting basic usage stats:
Zillow (≈ 200 M monthly visitors) gives Walk/Transit scores per listing but no way to compare whole streets side by side.
Trulia (≈ 8 M monthly visits) adds neighbourhood photos and reviews, yet filters stop at price and bedrooms.
Nextdoor (≈ 46 M weekly active users) offers hyper local chatter, but its posts are noisy and unstructured for first-time movers.
Key gap: none of the three lets users layer verified Street level essentials into one filterable map. That insight shaped Locale Lens’s goal: a single-tap, data driven view that turns neighbourhood guesswork into confident decisions.
Wireframes
Design
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