Important Details Buried in Chats

Problem

iPhone users are not given efficient tools to search for important information received via text in iMessage. For example, in group chats where numerous messages are exchanged, it's common for important texts, like details of making plans, to become buried in the conversation. This often results in endless scrolling in search of those crucial details.

Suggested Events Detected with AI

Solution

Increased Convenience in Tracking Events

Impact

The Suggested Plans feature enhanced user efficiency in iMessage by simplifying event organization and providing easy access to key details.

  • Increased Efficiency: Users spent 40% less time scrolling to locate event-related information in chat threads.

  • Seamless Integration: 100% of users felt the feature aligned naturally with Apple’s interface, enhancing the iMessage experience.

  • Improved Coordination: Over 80% of users found it easier to track plans without needing additional apps or manual organization.


Competitors Do Not Utilize Automated Technology

Competitor Research

To understand how iMessage could improve, I assessed Apple’s primary competitors—Samsung, Google, and Facebook Messenger—in message organization. The analysis revealed that while competitors offer basic categorization, they lack automated event detection within chats, highlighting an opportunity for iMessage’s Suggested Plans to fill this gap.

What Users Utilize Search For

User Research

The objective of the research was to observe how iPhone users utilize iMessage search, and what they currently do to help them organize important information received via text message. 

Interviews revealed that over 80% of users rely on iMessage to plan events, but nearly all expressed frustration with searching for specific details in chat threads. Users often resorted to manual methods, like screenshots or notes, highlighting the need for an integrated organization feature.

How might we help search and manage plans discussed in iMessage conversations?

Feature Concepts Based to Improve Search

Ideating Solutions

To address user pain points, I explored three solutions for iMessage organization: Smart Search, Detected Events, and Pinning. After assessing each, I identified Detected Events and Smart Search as high-impact features. Due to its simpler implementation as an MVP, I chose to move forward with Detected Events, while AI Search remains a valuable future addition.

Iterations

Testing and Feedback

I began testing the chosen solution at low fidelity by asking participants to complete three tasks in observed usability tests via Zoom: accept the Suggested Plan banner, edit the plan time, and unpin the plan from the conversation screen. The following iterations were made based on feedback:

The Suggested Events Feature

Final Prototype

Putting it into action, the Detected Events feature for iMessage was created, covering three flows: accepting the suggested event, editing the plan, and removing the banner from the conversation screen.

Figma Protoype

Conclusion

Moving Forward

As an iPhone user who frequently uses iMessage to search old texts—whether for restaurant recommendations, cat advice, or coordinating with friends—I was inspired to take on this project. During user research, I found that many iPhone users shared similar experiences. This validation made the ideation phase engaging, resulting in the three options presented in this case study.

Since this is a conceptual project, some limitations and technical considerations include:

  • Fitting into Apple’s Ecosystem: The design prioritized a seamless integration within Apple’s existing brand and user flow, focusing on consistency with the iMessage and Calendar interfaces to support ease of use.

  • Technical Considerations: Implementing this feature would require addressing varied user flows and interactions, such as confirming plan changes, enabling organic chat updates, and ensuring only relevant conversations are flagged as plans. AI detection for the Suggested Event Banner would involve defining data points to identify events accurately.