Domclick

Building an ML-Powered Real Estate Valuation Tool

One of the biggest challenges in real estate is accurate property valuation. Buyers and sellers often struggle to determine fair pricing, leading to lengthy negotiations and uncertainty.

To address this, we developed a machine learning-powered valuation tool that analyzes 40+ key property parameters (location, building condition, market trends, etc.). This allowed users to get instant, data-driven price estimates, improving transparency and decision-making.

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Key achievements:

• Built and launched the tool from scratch within a short timeframe.‍
• Successfully monetized the service, adding a new revenue stream to Domclick.
• Simplified property comparisons, reducing time-to-decision for buyers and sellers.

Optimizing for Mobile:
A Seamless User Experience

With an increasing number of users accessing Domclick via mobile, we needed to enhance mobile usability while ensuring stability and ease of access.

We focused on three key areas:

1. Improved navigation & responsiveness across devices.
2. ‍Stable online experience, minimizing crashes and downtime.
3. ‍Sharable PDF reports, allowing users to save and send property details effortlessly.

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Impact:

• Conducted 20+ user research studies to refine the experience.
• Achieved significant user growth among mobile-first customers.
• Enhanced cross-platform accessibility, making property transactions smoother.

Validating Hypotheses: Data-Driven Decision Making

We followed a data-driven approach, rigorously A/B testing hypotheses before implementing changes. By running structured offline experiments, we gathered insights into user behavior and validated design decisions before full-scale deployment.

Redesigning the Search Experience: Lessons from Failure

We aimed to simplify the search experience, making it more intuitive and increasing user engagement. However, after launch, we observed an unexpected 11% drop in search conversions.

Key Learnings:

• On mobile, users mistook the search icon for a static element, leading to lower engagement.
• A/B testing helped us recognize this design flaw within 3 weeks, allowing us to pivot quickly.
• This failure reinforced the importance of user behavior analysis before implementing major UX changes.

Improving Contact Methods: A Smarter Way to Connect

Users frequently encountered connectivity issues when calling sellers via the in-app telecom system, leading to frustration and lost opportunities. To fix this, we introduced a new dual-call system, allowing users to choose between:

1. In-app telecom (default)
2. ‍Direct phone call option (backup)

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Results:

• Gave users greater flexibility in communication.
• ‍Increased successful call rates, reducing frustration.
• Majority of users opted for the new calling option, validating our approach.