Timeline
Aug 2021
Role
Senior product designer
Context
Ada is a tool that helps companies talk to their customers automatically, without needing to code. Big names like Zoom and Facebook use it to make sure every customer feels special. It started in Canada but now works with brands all over the world, making conversations easy and personal business requirements and policies.
The challenge
Despite Ada's sophisticated conversational capabilities, users struggled to navigate and make sense of extensive chat logs. This made it difficult to track customer inquiries, identify common issues, and uncover opportunities for bot improvement.
Goals
1.Deep Understanding: Enable clients to gain in-depth insights into customer conversations.
2.Efficiency: Streamline the analysis process to quickly identify and address common queries and issues.
3.Continuous Improvement: Provide a framework for ongoing enhancement of chatbot responses and user interaction.
Research & Insights
My comprehensive research involved client interviews, session observations, experimental sessions, and quantitative data analysis.
I discovered that both bot builders and support leaders/managers yearned for deeper insights into customer conversations.
They aimed to enhance customer experience, reduce costs, drive revenue, and increase loyalty by understanding and addressing their customers' needs more effectively.
Exploration of Solution Paths
During the exploration phase, I focused on understanding user needs and technical options. my aim was to create a scalable solution that directly caters to users.
Bringing the Team Along
1.Brainstorming Sessions:
I brought together designers, developers, data scientists, and customer support reps to brainstorm ideas. This diverse approach encouraged creative thinking, evaluating ideas based on feasibility, impact, and user alignment.
2.User Journey Mapping:
I created detailed user journey maps to visualize the experiences of bot builders and managers. These maps pinpointed workflow pain points, especially in data navigation and insights extraction, helping us identify areas for improvement.
3.Feature Prioritization:
Based on brainstorming sessions and user journey insights, we focused on developing three key features:
User-Defined Topics: Users can customize analysis by selecting specific topics of interest.
Topic Suggestions: Machine learning suggests popular topics to uncover new insights.
Anomaly Detection/Alerting: Real-time alerts notify users of unusual spikes in conversations for proactive issue resolution.
This approach ensured my design and development efforts were deeply rooted in solving real user problems, supported by our technological capabilities.
Streamlined Design & Iteration Overview
This phase focused on transforming insights and ideas into features. We prioritized efficiency, user feedback, and close collaboration with engineering to ensure our solutions were both innovative and practical.
Prototyping: Developed high-fidelity prototypes for key features, including user-defined topics, topic suggestions, and anomaly detection. This process was crucial for visualizing potential solutions and preparing them for user testing.
User Testing and Feedback: Conducted extensive testing with stakeholders and customers to gather insights on usability and functionality. Feedback informed immediate refinements, ensuring our designs were in line with user needs.
Refinement: Iterated on designs based on user feedback, enhancing flexibility and adding requested functionalities. This iterative process ensured that our final designs were user-centric and ready for implementation.
Collaboration for Implementation: Worked in tandem with the engineering team throughout the process, balancing innovation with technical feasibility. This collaboration was key to achieving a scalable and robust final product ready for development.
Converging to Focus on Feasibility
Following the expansive phase, I converged, focusing on refining and selecting ideas that were practical and aligned with our goal of rapid development:
Feasibility Analysis: Evaluating each idea based on technical feasibility, potential impact, and alignment with user needs. This helped us prioritize ideas that could be implemented quickly and would offer significant value to users.
Simplification for Speed: For chosen features, I simplified the designs and scoped them to essential functionality. This approach ensured that we could move swiftly from concept to development, avoiding unnecessary complexity.
Some of Takeaways and Learnings
Client Feedback is Invaluable: Integrating direct feedback from users was crucial. It not only helped in identifying the most pressing issues but also in prioritizing feature development to address those needs effectively.
Iterative Development Enhances Productivity: The iterative approach to development, powered by continuous user testing and feedback, ensured that each feature not only met but exceeded user expectations. This process of refine, test, and implement was key to achieving meaningful improvements.
Collaboration Across Teams is Crucial: The success of this project underscored the importance of cross-functional collaboration. Working closely with the development team and aligning technical implementations with user feedback ensured that the final product was both effective and user-friendly.
Flexibility in Strategy: Being open to changing our approach based on user feedback and testing results was crucial. This flexibility allowed us to adapt quickly and effectively to user needs, leading to better outcomes.
