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Immersive AI for Boliga

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Immersive AI for Boliga

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Immersive AI for Boliga

Immersive AI for Boliga

Using the Continious Discovery framework, three fellow designers and I created AI experimentation for Boliga - one of the largest real estate sites in Denmark. The collaboration was done as part of our thesis project.

Using the Continious Discovery framework, three fellow designers and I created AI experimentation for Boliga - one of the largest real estate sites in Denmark. The collaboration was done as part of our thesis project.

Using the Continious Discovery framework, three fellow designers and I created AI experimentation for Boliga - one of the largest real estate sites in Denmark. The collaboration was done as part of our thesis project.

Company

Boliga

Role

Product Design

Date

Jan 2024 — May 2024

Teal Flower
Teal Flower
Teal Flower

Boosting the Boliga experience with AI

Boosting the Boliga experience with AI

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.

Prototyping anno 2024

Prototyping anno 2024

Building on our exploration of AI's potential, we decided to dive into the latest design trends shaping the industry. Continuous Discovery emerged as a key theme through interviews we conducted with leading design teams in Denmark, including experts from Novo Nordisk, Mærsk, and Valtech.


Several design teams are moving to more experimental product-led ways of working. Here are some of the interesting trends:


  • De-risking: A recurring theme in our conversations was the emphasis on de-risking product development. Several teams use Continuous Discovery as a way to promote learning and exploration, minimizing the risk of launching features that miss the mark.


  • Quick low-cost experiments: Several teams would create bi-weekly prototypes - allowing for faster iteration and learning.


  • Continuous User Involvement: Integrating user feedback throughout the design process ensures solutions truly address user needs.


  • Opportunity Solution Trees: This framework provides a visual roadmap for experiments, fostering clear decision-making.




Building on our exploration of AI's potential, we decided to dive into the latest design trends shaping the industry. Continuous Discovery emerged as a key theme through interviews we conducted with leading design teams in Denmark, including experts from Novo Nordisk, Mærsk, and Valtech.


Several design teams are moving to more experimental product-led ways of working. Here are some of the interesting trends:


  • De-risking: A recurring theme in our conversations was the emphasis on de-risking product development. Several teams use Continuous Discovery as a way to promote learning and exploration, minimizing the risk of launching features that miss the mark.


  • Quick low-cost experiments: Several teams would create bi-weekly prototypes - allowing for faster iteration and learning.


  • Continuous User Involvement: Integrating user feedback throughout the design process ensures solutions truly address user needs.


  • Opportunity Solution Trees: This framework provides a visual roadmap for experiments, fostering clear decision-making.




Building on our exploration of AI's potential, we decided to dive into the latest design trends shaping the industry. Continuous Discovery emerged as a key theme through interviews we conducted with leading design teams in Denmark, including experts from Novo Nordisk, Mærsk, and Valtech.


Several design teams are moving to more experimental product-led ways of working. Here are some of the interesting trends:


  • De-risking: A recurring theme in our conversations was the emphasis on de-risking product development. Several teams use Continuous Discovery as a way to promote learning and exploration, minimizing the risk of launching features that miss the mark.


  • Quick low-cost experiments: Several teams would create bi-weekly prototypes - allowing for faster iteration and learning.


  • Continuous User Involvement: Integrating user feedback throughout the design process ensures solutions truly address user needs.


  • Opportunity Solution Trees: This framework provides a visual roadmap for experiments, fostering clear decision-making.




Validating more ideas in less time with Continuous Discovery

Validating more ideas in less time with Continuous Discovery

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.

  • There is actually a lot I don't know about buying a house.

    Man, 27

    On being a first-time buyer

  • Is all this advertisments?

    Woman, 29

    On visual noise

  • Why aren't there more pictures?

    Woman, 27

    On inspiration.

  • The site looks a bit old.

    Woman, 28

    On the design of the site.

  • Why is the button hidden away?

    Man, 27

    On placement of CTA

  • Wow, there is a lot of stuff here.

    Woman, 26

    On number of features

  • There is actually a lot I don't know about buying a house.

    Man, 27

    On being a first-time buyer

  • Is all this advertisments?

    Woman, 29

    On visual noise

  • Why aren't there more pictures?

    Woman, 27

    On inspiration.

  • The site looks a bit old.

    Woman, 28

    On the design of the site.

  • Why is the button hidden away?

    Man, 27

    On placement of CTA

  • Wow, there is a lot of stuff here.

    Woman, 26

    On number of features

  • There is actually a lot I don't know about buying a house.

    Man, 27

    On being a first-time buyer

  • Is all this advertisments?

    Woman, 29

    On visual noise

  • Why aren't there more pictures?

    Woman, 27

    On inspiration.

  • The site looks a bit old.

    Woman, 28

    On the design of the site.

  • Why is the button hidden away?

    Man, 27

    On placement of CTA

  • Wow, there is a lot of stuff here.

    Woman, 26

    On number of features

Early insights & the currenct Boliga experience

Early insights & the currenct Boliga experience

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.

We began ideating. Here is a look at our design values.
We began ideating. Here is a look at our design values.

Exploring Conversational AI: The First Experiment

Exploring Conversational AI: The First Experiment

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.

Building a Warmer Welcome

Building a Warmer Welcome

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.


Interactive Onboarding with User Choice

Interactive Onboarding with User Choice

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.

A Glimpse into the Future - Image AI

A Glimpse into the Future - Image AI

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.

Future Exploration and Reflections

Future Exploration and Reflections

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.


Contact me at

@2024 Philip Bostrup

Contact me at

@2024 Philip Bostrup

Contact me at

@2024 Philip Bostrup

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