Litespace Coffee Chat
Connecting hybrid teams authentically
Project Type
Professional
Timeline
Sep 2023
Worked with
Design Lead
1 Engineer
Contributions
Research
Prototyping
Testing
OVERVIEW
Bridging the gap between structured meetings and casual interactions
Litespace is an AI-powered enterprise platform that helps organizations improve engagement and satisfaction in hybrid and remote workplaces. It offers hybrid scheduling, event recommendations, and integrations with Slack, Outlook, and Google Calendar to support large teams.
Coffee Chat is an enterprise 0-to-1 solution designed to spark spontaneous, meaningful conversations across distributed teams. It turns routine meetings into casual yet purposeful interactions that strengthen culture. I led the design and experience iterations, adapting to evolving enterprise needs.
Impact
Through design and product iterations, Coffee Chat quickly proved its value by driving engagement and adoption across hybrid teams.
63%
Users opted into Coffee Chat within the first month, signaling strong early adoption.
200+
Chats generated in the first month through auto-matched pairings, with consistent weekly participation.
$4.5M
Company valuation reached alongside the Coffee Chat launch and other key feature rollouts.
PROBLEM
Remote teams lack casual social interactions
To improve team connection and collaboration in hybrid and remote environments, I identified key challenges through internal observations, feedback from enterprise customers, and seven teammate interviews across Product, Engineering, and Operations. Addressing these issues is essential to fostering meaningful interactions and stronger team cohesion.
Lack of Spontaneous Interactions
In hybrid and remote work environments, opportunities for spontaneous, meaningful conversations are limited, leading to reduced team cohesion.
Sense of Disconnection
Traditional work models often create a disconnect among team members, particularly in settings where remote and in-office work are mixed.
Ineffective Communication Channels
Existing meeting structures tend to be formal and rigid, making it difficult to foster casual, purposeful interactions that build stronger team relationships.
RESEARCH
Why existing tools fall short
To understand how others addressed casual interactions, I conducted a competitive analysis of Slack bots, virtual spatial platforms, and co-working tools.
Most focused on automating who to meet, but overlooked why the meeting should happen or what to talk about.
This gap inspired the vision for Coffee Chat: a lightweight feature that creates not just pairings, but conversations with context and purpose.
DESIGN GOALS
Ensuring seamless pairing, scheduling, and engagement
After conducting team interviews, analyzing competitive tools, and researching human behavior in workplace interactions, we established key goals to achieve during this MVP.
Automated Pairing with Purpose
Automatically match employees for coffee chats and provide context on why they are paired, fostering relevant and meaningful interactions.
Smart Scheduling
Allow users to select preferred times and automatically schedule chats within available time slots, ensuring flexibility and seamless integration into their workflow.
Cross-Department Matching
Enable connections between employees from different teams or departments to break down silos, encourage collaboration, and foster company-wide networking.
Conversation Starters
Suggest engaging topics or icebreakers to help participants initiate conversations, making interactions more comfortable and productive.
CONSRTAINTS
Launching a new feature ahead of the rebranding
The product was transitioning from a green-dominant identity to a more modern blue-focused visual system, but the rebrand was still in progress. We had just two weeks to design and release the coffee chat feature so it could become the first experience aligned with the new direction. This constraint pushed us to focus the MVP on enabling one meaningful chat per week, quickly validating core value while building a scalable foundation for future brand-consistent improvements.
EXPLORATION CHALLENGE 1
Creating meaningful pairings
After exploring ChatGPT-3’s potential, I proposed using it to make pairings more meaningful. The system now pulls data from onboarding forms, user profiles, quick post-chat feedback, and Slack integration that detects shared channels and participation patterns without accessing private messages. This context allows it to generate personalized, intentional matches.
EXPLORATION CHALLENGE 2
Mapping the user flow
A key challenge was mapping different user scenarios, as participants could see different screens based on their actions. To improve scheduling, I compared the traditional manual flow with the new Coffee Chat flow. The old process involved manual coordination and back-and-forths, while the new flow automates pairing, adds clear fallback options, and reduces user pressure by removing direct messages.
ITERATION CHALLENGE 1
Simplifying coffee chat's interface
Faced with a complex UI in Coffee Chat, I initially designed a multi-functional widget. User testing revealed its high cognitive load, leading me to divide it into two simpler widgets for availability and reasons, which received more positive feedback during internal A/B testing. I also added a mutual availability tool for easier scheduling in remote or hybrid environments.
Before
After
ITERATION CHALLENGE 2
Optimizing meeting format selection
I explored the option of letting users choose between virtual and in-person meetings, but A/B testing showed it caused delays and confusion without direct communication, and in-person meetings were rarely chosen in our remote and hybrid setting. Based on these findings, we removed the selection to simplify scheduling, reduce cognitive load, and improve efficiency by focusing only on availability.
Before
After
FINAL DELIVERABLES
Seamless scheduling with contextual matchmaking
The Coffee Chat feature automatically pairs users each week based on their availability, integrating with Google Calendar. Matches include context on shared interests and suggested topics to facilitate conversation. The chat is set to "Going" by default, ensuring a seamless scheduling experience. Users can reschedule or decline if needed. Upon both users' confirmation, the system generates a Google Meet link and adds it to their calendar, making it easy to connect and engage in meaningful conversations.
Handling chat declines without friction
If either participant declines the scheduled coffee chat, both users will see a notification widget informing them that the chat has been canceled. To reduce pressure and maintain a seamless experience, the system does not require a reason for declining. Users will simply be notified that their next coffee chat will be scheduled in the following cycle.
Flexible scheduling for better availability
If user wants to reschedule, he can choose from alternative time slots automatically recommended based on both users' availability. This simplifies the process by providing quick, pre-selected options, allowing for a smoother scheduling experience. Once both users agree on a new time, the chat is confirmed.
If the other user proposes new times, user can review and select a slot that works for both. This ensures flexibility while maintaining a structured approach, reducing the need for back-and-forth coordination and making it easier to finalize meetings.
If none of the other user's suggested times work, users can propose their own availability for the other person to review. This flexible approach simplifies scheduling and increases the likelihood of finding a mutually agreeable time.
What I’d do differently in 2025
In 2025, I focused on advancing AI-driven design through adaptive agents that create more human-centered interactions. Using Figma Make, I prototyped conversational flows that adapt to tone and context in real time. This approach improved usability and user engagement while establishing a scalable conversational framework for future platform features.
REFLECTION
The Coffee Chat feature was the first major project successfully launched after our rebranding, marking a significant milestone for the team. This process deepened my understanding of ChatGPT and its role in refining pair selection and generating meaningful match explanations. I was excited to propel the team forward in this direction, ensuring that AI-supported matchmaking felt more intentional and meaningful. Building and testing this MVP allowed us to assess its impact, explore future expansion, and evaluate its effectiveness in improving scheduling efficiency and user engagement.
Thanks for reading! 😊
© 2025 Chang Mou. Crafted with 💪 and ❤️