UX/UI Design, UX Researchgo to site
Lichluchit is a social enterprise project that helps apartment seekers to overcome gaps in information in social media posts about potential apartments – even before visiting it.
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UX/UI Design, UX Research
Aug. 2020 - Nov. 2020
Nowadays, the most popular to search for a new home is sifting through many Facebook groups, sites like Yad2 or Win-Win. The inherent problem with these kinds of postings is that the renter is the one posting it.
This leads to huge gaps between the description of the apartments and the actual apartments. An apartment’s actual size, noise levels in the surrounding area, construction projects nearby are just some of the “concealed” details left out deliberately from the posting.
Today, these gaps are only filled when the seeker visits the apartment. These cause loss of time, money, energy, and frustration from an already intense process.
I started by familiarizing myself with the existing apartment search platforms like Yad2, Win-win, Doron, and Facebook groups.
My competitive analysis produced the following insights:
After seeing there isn’t any platform that tries to bring an objective, relevant information about apartments, I’ve built a survey using Google Forms to try and get a better understanding of the willingness of apartment seekers to use a platform such as this and to ratify their motivations, needs, gaps, and frustrations when seeking apartments.
Survey Statistics :
After reaching my goal of 15 participants, I began identifying and classifying participants' responses based on their answer to the question:
“During your last search for an apartment, what things did you discover about apartments only after visiting them? We will appreciate it if you describe as many reasons as possible in detail”
I’ve detected 16 different themes that eventually fell into 12 categories. Each of the categories represents the mains gaps in information this platform tries to minimize. These 12 categories will help the users to scan and sort the posts and failures about an apartment. When a user posts something new, he would be able to easily tag failures in any of the categories aforementioned, alongside a free-text description.
After detecting these 12 categories – I’ve created an online card sorting mission using the Optimal Workshop platform for 10 participants. Each participant was instructed to give priority to each category by sorting them from 1 (most important) to 12 (least important).
There were 2 objectives to this research phase:
Here is a sample of sorting by a few participants:
After reaching my goal for 10 participants, I’ve calculated the average importance score of all participants for each category, as can be shown here:
I had created a mini-system that allowed us to quickly access the exact font styles used across the site. Though it would be small, my mini-system would empower us to focus on the experience and usability, rather than having to guess at colors and font styles.
Keeping users’ needs and pain-points in mind, I settled on a final version of the design, creating a high-fidelity prototype.
This page contains a search section in the center of the page to attract the user’s attention and call them to action. Alongside it is an illustration of a city under construction, to emphasize the idea and purpose of this platform.
I decided to display the relevant anonymous “trash” posts in a 200-meterradius from the apartment as shown in the Google Maps frame to the left of theresults. This is relevant to describing the surroundings of any one apartment. Each post contains visual indicatorsabout its distance, categories and importance – all of which can be further filtered by.
For now, although importance isn’tinclusive and fixed for all the users I made an informed decision to use the average position from the card sorting mission of each category, to representits score because it's an MVP. I'm intending to give user's the ability to choose which categories are more relevant for them.
I'd like to say thank you to Yuval, our Software engineer, and Danit, our NLP specialist, for being awesome teammates!
Thank you for supporting my ambitions and craziness, I’m grateful for all yours feedback throughout the process, and for the supportive environment we’ve created to helped me to learnand grow as a designer!
I believe we’ve created a wonderful project and hope it will help people in their search for the perfect apartment :)
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