Company
Boliga
Role
Product Design
Date
Jan 2024 — May 2024
Boliga, one of Denmark's largest real estate platforms, aims to improve the user experience with AI-driven solutions, making it easier for users to find their dream homes.
Our goal as designers was to generate concepts for doing so, exploring ways for Boliga to leverage AI.
This project explored the power of Continuous Discovery for rapid experimentation. Our goal was to build a strong foundation for Boliga's future AI development,
Our key goals were:
Generate a rich catalogue of AI concepts: We aimed to brainstorm and explore a wide range of AI concepts that could benefit Boliga's users.
Develop an insights toolkit: By gathering user feedback through experimentation, we would create a valuable toolkit of insights to guide future AI development at Boliga.
Test Continuous Discovery: This project served as a testing ground to assess the effectiveness of Continuous Discovery as a framework for driving rapid UX iteration.
We transitioned from exploring design trends to putting Continuous Discovery into action for Boliga. Our goal was to validate a wide range of ideas quickly and efficiently, ensuring we focused on concepts with the most user value.
Here's how we did it:
Defined the North Star: We began by establishing a clear North Star metric – how can AI improve the user experience for Boliga users? This guiding principle ensured all our experiments aligned with a user-centric goal.
5-Sprint Continuous Discovery: We then embarked on a 5-sprint Continuous Discovery journey with weekly user tests. This rapid experimentation cycle allowed us to test numerous ideas and gather valuable user feedback.
Opportunity Solution Tree: We used an Opportunity Solution Tree to visualize our experiments. This framework helped us brainstorm potential solutions, define success metrics, and prioritize testing based on user needs and impact.
Focus on User Learning:
Throughout this process, we prioritized user learning. We conducted weekly user interviews to gather real-world feedback on our prototypes. This data-driven approach ensured we were developing solutions that truly resonated with Boliga's users.
Before diving into experimentation, we prioritized understanding user needs at Boliga. Through user interviews, we gained valuable insights from participants across different age groups. In total, we gathered feedback from 8 participants.
Our main persona was first-time buyers: Young users entering the property market for the first time is a critical segment for a company such as Boliga. We wanted to test the hypothesis that the young segment (25-35 years old) would be more receptive to AI solutions.
Common Pain Points:
Our first discovery interviews revealed several recurring pain points that users faced on the current Boliga experience:
Lack of Onboarding: New users felt lost without a clear introduction to the platform's features and functionalities.
Navigation Challenges: The website navigation was perceived as complicated, making it difficult for users to find what they needed.
Hidden value: Users expressed frustration with valuable functionalities being hidden within the platform.
Anxiety of Buying a Home: The overall process of buying a home was perceived as overwhelming and stressful.
Opportunity Identified:
These insights presented a significant opportunity for us. We saw the potential for conversational AI to serve as a helpful "counselor" for users. By integrating this technology, we envisioned assisting users throughout their home buying or selling journey, ultimately helping them find their dream home.
These design values were top of mind when we began to ideate on prototypes.
We decided to start our journey with rapid experimentation. We aimed to understand user reactions to different implementations and identify opportunities to improve the user experience.
Our initial experiment explored a solution similar to ChatGPT. We wanted to gauge user response to AI chat functionality, considering its potential feasibility for Boliga. This experiment revealed a crucial insight:
User Bias Against AI Chatbots: While the concept intrigued some, many users (across age groups) expressed discomfort with AI chatbots. This highlighted the need for a more user-friendly and approachable approach.
Informed by user feedback, we pivoted to a more inviting conversational AI experience. This version incorporated the following elements:
Personalized Greetings: The AI introduced itself by name, creating a more personal interaction.
Visual Inspiration: Large image cards offered quick-start suggestions, visually guiding users towards their search journey.
This iteration received a more positive reception, but feedback indicated there was still room for improvement.
Building on the learnings from the previous experiments, we focused on improving the onboarding process, so the AI would already know user preferences before any chatting took place . This refined solution offered:
Interactive Onboarding Flow: Users could answer a few questions to personalize the AI's suggestions.
Opt-Out Option: Recognizing user preferences, the flow could be entirely skipped if desired.
Beyond conversational interfaces, we explored the potential of image AI. This experiment envisioned a feature that:
Visualized Renovation Potential: Using image AI, users could see the potential of a property in need of renovation.
While a bit of a "gimmick," this experiment highlighted the future possibilities of image AI in the real estate industry - something a number of startups are already looking into.
That was a look at a number of our concepts.
These experiments provided invaluable user insights and identified several promising avenues for Boliga's future development.
The project highlights the importance of continuous learning and user-centered design when exploring new technologies like AI.
Continuous Discovery can provide quality insights fast - and validate ideas. But it requires fostering a culture of innovation and experimentation. Designers need space (and ressources) to do this kind of work.
It’s still early for the implementation of AI at Boliga, but these concepts have created groundwork for future development.