Search

Search is a crucial aspect of any product, and as such, the search functionality of our product must be carefully designed and implemented to ensure optimal user experience

Responsibility

As part of my responsibilities, I conducted user interviews and workshops to gather insights into user needs and pain points. Using this information, I created both low-fidelity and high-fidelity designs for the search function, which were refined through collaboration with the tech team during real-time usability testing. Throughout the design process, I remained dedicated to creating a search function that was truly user-centric and aligned with users' behavior and real-life scenarios.

Problem Statement

The current search function in the platform is creating a poor user experience due to its lack of compatibility with user behaviour and real-life scenarios. Users are finding it difficult and time-consuming to locate assets, which is negatively impacting the overall usability of the project. As a result, there is a need for user research to improve the search function and create a more user-friendly experience.

Double Diamond Research Method

User interview & workshop to identify pain points

As a UX researcher, I was tasked with investigating the issues surrounding the search feature of the platform. To gain insights into users' experiences with the search function, I conducted in-depth interviews with a diverse group of users. Through these interviews, I learned that many users struggled to find the assets they needed, often resorting to using external search engines to locate them.

To further explore these issues and gather additional feedback, I organized a workshop with a subset of users. During the workshop, users were given various search scenarios to complete and asked to provide feedback on their experiences. The workshop revealed that the search function was not aligned with users' behaviour, and its design did not match real-life scenarios.

Based on the insights gathered from both the interviews and workshop, it became clear that the search function was creating a poor user experience. Users were spending an excessive amount of time searching for assets, which was leading to frustration and negatively impacting their overall experience with the platform. Current search function was difficult and time-consuming for users to locate assets.

Key points

• Users lacked trust in the current search function and resorted to using external search engines.

• The current search function was not aligned with users' behaviour and real-life scenarios.

• The new search function needed to be more intuitive, with natural language search and speed optimization.

• Testing revealed a significant improvement in the user experience with the new search function.

Ideal Solution

I have used the insights gathered from user interviews and the workshop to identify the key pain points and challenges users faced while searching for assets. They then worked to create a solution that would address these issues and provide a better user experience.

Drawing on the insights gathered from user research, I incorporated a natural language search feature into the design, allowing users to input their queries in a way that felt more conversational and familiar. This approach made it easier for users to find the assets they needed, without requiring them to learn complex search syntax or keywords.

I also focused on optimizing the search function for speed, ensuring that users could quickly find the assets they needed. This was achieved through careful design choices, such as autocomplete suggestions and a responsive search results page.

Questions for interview

• How do you typically search for assets online? Can you walk me through your process?

• What search terms do you typically use when looking for a specific asset?

• Can you describe a recent search experience that you found particularly frustrating or challenging?

• Are there any terms or industry jargon that you use when searching for specific types of assets? Can you give me an example?

• Can you walk me through a recent successful search experience on this platform? What made it successful?

• How important is speed when it comes to finding the asset you're looking for? Would you prefer a faster search experience or a more accurate one?

• Are there any search features or functionalities that you wish were available but currently aren't?

• Have you used any search engines or platforms that had a natural language search feature? If so, what was your experience like?

Usability testing

After the design process, I collaborated with the tech team to usability test the new search function with 200 real assets and users. The results were overwhelmingly positive, with users reporting a significant improvement in their search experience. The team was thrilled to have created a search function that truly addressed the pain points identified in the user research, and they were confident that the new design would lead to greater user satisfaction and engagement on the platform.

Impact

Following the launch of the new search function, there was a remarkable increase of 240% in the use of search on the digital platform. In addition, users were able to find the desired asset with much greater ease, as demonstrated by a 60% reduction in the time taken to complete a search. These impressive results signify a significant improvement in the user experience, indicating that the new search function was well-received and successfully addressed the previous pain points identified by users. These positive impacts also suggest that the platform is likely to benefit from increased engagement and user satisfaction going forward.

Future Actions

To continue improving the search function, we have added metrics and analytics to track the performance of the new search feature. This data will allow us to identify any remaining pain points and areas for further optimization, enabling us to continue to enhance the user experience. We remain committed to delivering a search function that is truly user-centric and aligned with users' behavior and real-life scenarios.

Produced at Everledger

Design team: Ankit Jhanwar

Collaborator: Siddheshwar rajadhyax, David Orr, AJ, Alma Schalen, Soupayan Datta