Meeyland is a real estate platform for buying and renting properties, competing with sites like batdongsan.com and nhatot.vn. Its search and filter tools are key to keeping users engaged. Since mid-2024, I’ve been working on improving the filter system for the new version. Below, I’ll summarize how I tackled the problem, built solutions, and got results.
I used the Double Diamond Design Thinking model for this project.
The filter upgrades made a real difference—see the results here.
Quick research to discover what needs to be improved
1- Competitive Research – Reviewed direct competitors to understand their implementation strategies.
2- CEO Feedback – Held regular meetings with the CEO to align on direction and refine ideas
3- User Insights – Collected feedback from user forums, community chats, and prior research.
4 -Quick User Testing – Conducted rapid testing with a few real estate brokers to gather targeted feedback.
Base on Document from Research team and gather users insights
Analyze competitors and collect insights from app store reviews and user communities
Regular meets with CEO for feedbacks
There are 2 critical problems with the Search Functionality:
1 - Inaccurate Search Results – Keyword searches often return incorrect listings, with frequent mismatches in location suggestions.
2 -Fragmented Filter Experience – The filtering process is overly complex, making it time-consuming to select provinces, area preferences, price ranges, and other criteria.
The goal is to improve search accuracy and significantly reduce the time users spend finding relevant listings.
In the following section, each issue will be addressed along with its proposed solution.
Problem 1: City/Province Search Function
Issue: Internal research showed that users typically search within a single target area, rather than across multiple cities as required in the current version.
Solution: Prioritize the property address search field, highlight the top five most-searched cities in Vietnam with visuals, replace city/province checkboxes with an alphabetized list for easier scanning, and consolidate district/ward/street selection into the main search bar.
Issue 1: Filters for property type, price, and area are cluttered, overly long, and difficult to navigate, leading to inefficient searches.
Solution: Optimize data so all filter fields can be viewed within a single scroll.
Issue 2 : Similar issues occur with price and area selection. Additionally, project listings often share identical names across different regions, causing confusion.
Solution: Simplify price and area filters to single-choice options for more precise results.
Furthermore, add a slider for broader price ranges, reducing repetitive clicks.
Issue 3: Additionally, project listings often share identical names across different regions, causing confusion.
Solution: Enhance project selection by displaying region details and the number of listings under each project name.
User Testing overview
Participants: 5 users
Method: In-office sessions and remote testing via video call
Objective: Assess task completion time, ease of use, effectiveness, and user satisfaction with the new search features
of users completed tasks vs. 87% in the previous version
is the average time on task reduced compared to the old version.
of users rated search suggestions as accurate, up from 20% previously
of users expressed satisfaction with the search results
This enhancement is a key milestone in the new product version, benefiting both business goals and user experience. Going forward, I will track core metrics—active users, events volume, and retention rates—to continuously evaluate and refine performance.
