About the client
RentSlam helps renters in the Netherlands and Germany find apartments faster by sending instant notifications on new listings, crucial in a market with high demand and limited supply. With over 40,000 users served since 2016, RentSlam turned to Genuisee to improve data speed, expand website coverage, and upgrade their user experience with AI-powered solutions.
Business context
In the Netherlands and Germany, the real estate market faces a significant challenge with the imbalance between the high demand for rental properties and their scarce availability. Renters often encounter lengthy queues and rapid turnovers in property listings, which makes securing a rental highly competitive.
Therefore, Genuisee’s goal was to create a platform to expedite the search process, offering users real-time updates on new rental properties. This enables potential renters to be among the first to know about new listings, significantly improving their chances of securing a property in a fast-paced market.
Data collection was slow
RentSlam needed to enhance the speed of its data collection to outpace competitors and provide users with timely information.
Website dynamics
Frequent updates and changes on real estate websites required continuous adjustments in data scraping techniques, making it challenging to maintain accuracy and reliability.
Poor UX/UI
The client’s web application suffered from suboptimal UX/UI design, resulting in a lacklustre user experience and diminishing the overall perception of their product and service.
Solutions we implemented
As strategic technology partners, we focused on overhauling the data scraping capabilities to ensure RentSlam could deliver real-time, accurate rental listings faster than ever.
- Broader platform coverage. We expanded the list of real-estate websites the system can parse, giving users a wider and more reliable search landscape.
- Smarter automation. We rolled out new internal tools that cut down manual scraping workflows and accelerate data processing end-to-end.
- LLM-driven extraction. By embedding advanced large language models, we improved how the platform interprets messy or inconsistent website structures, resulting in cleaner, more relevant data.
- Stronger stability. We upgraded error-handling logic and tightened the onboarding flow for new client integrations to ensure smoother platform adoption.
- Faster page delivery. Using reusable design-system components, we shipped new web pages quickly and supported the transition from the legacy app without disruption.
Multi-step user registration flow
A guided onboarding process that captures user preferences and verifies essential data points to personalize the apartment search experience from the start.
Functionality for setting apartment search criteria
Allows users to define specific parameters such as location, budget, size, and move-in date to tailor their rental alerts. This level of granularity ensures highly relevant listings.
Integrations with Stripe for payments and Mapbox for location services
Enables seamless subscription management and secure online transactions, improving conversion rates and operational transparency for RentSlam’s monetization model.
Also, users can visualize listings on an interactive map with filters by neighborhood, commute time, and proximity to landmarks, enhancing decision-making during the rental search.
Faster listings delivery
Automation significantly cuts down the time to deliver accurate apartment listings to clients.
Increased market coverage
Our team expanded the scope of operations to include more real estate websites, enhancing the comprehensiveness of the search results.
High user satisfaction
Our client achieved improvements in user satisfaction as evidenced by a dramatic reduction in complaints and enhanced engagement.
Top industry ranking
The client’s platform gained the first position in search accuracy and data comprehension as per independent auditors.
LLM implementation
Successfully deploying the language model resulted in a significant decrease in complaints, with 80% fewer issues reported post-implementation.
Enhanced scraping capabilities
After implementing AI technologies, the scope of scraping activities expanded to 3 times the previous capacity, including an increased number of websites and accommodation options available for data extraction.
Geographic expansion
The operations are set to extend beyond the Netherlands, including Germany, which indicates strategic growth in the European market.
Infrastructure development
The infrastructure supporting these operations has been doubled, indicating a significant resource and capability upgrade.
