Turn this into a video / gif of someone tying into the chat box, it thinking about it and then spitting out text. (chat GBT, sora? Other gif maker ask for options)
Overview of the project
As the sole Product Designer on Ask Cait, I led the development of an ongoing AI-powered market research assistant project that transforms how businesses identify and engage target audiences at MRI-Simmons. Built on advanced natural language processing technologies, Ask Cait streamlines the audience discovery process within the MRI-Simmons Study platform, allowing users to leverage conversational AI to quickly identify ideal advertising demographics.
This tool represents a significant leap forward in market research capabilities, enabling businesses to upload data to refine search parameters and engage directly with identified personas. The project showcases my ability to integrate cutting-edge AI technology with intuitive user experience design while balancing technical sophistication, business requirements, and user needs.
The case study details my multifaceted approach to designing an innovative AI solution that not only addresses immediate pain points but positions the company at the forefront of AI-driven market research.
[Additional Design Artifact: Persona Development]Include 1-2 key user personas that guided your design decisions. These should highlight the primary users' goals, pain points, and attitudes toward AI assistance. This demonstrates your user-centered approach and understanding of the target audience.
The Challenge
Market researchers using the MRI-Simmons Study faced significant friction when attempting to identify ideal advertising audiences. The traditional process required specialized knowledge of research methodologies, creating time-intensive workflows that slowed campaign planning and execution. As AI adoption increased across the industry, there was mounting competitive pressure to innovate. Additionally, knowledge silos prevented efficient access to valuable audience insights, further hindering effective market research.
My Role & Responsibilities
As the only Product Designer on this initiative, I drove the entire product design process while collaborating across multiple disciplines. I created the complete user experience and interface, conducting rigorous user research through interviews and usability testing to validate solutions. Going beyond traditional design duties, I took on substantial product management responsibilities by developing the product roadmap and prioritizing features based on business impact, user needs and technical feasibility.
Throughout the project, I built comprehensive documentation for development teams, translating complex AI behaviors into clear technical specifications. My cross-functional collaboration skills proved essential as I partnered with engineers, data scientists, and business stakeholders to ensure alignment between technical capabilities and business goals. I created and prioritized development tickets based on business value, helping the team focus on high-impact features that would deliver the greatest return on investment.
The Design Process
Continuous Learning & Exploration
To design an effective AI assistant, I dedicated time each week to learning through collabrative AI bookclubs, Coursera courses, earning certifications, reading industry blogs, and AI research articles. This commitment to understanding emerging AI patterns enabled me to shape informed design decisions around:
♡ Large language model capabilities and limitations
♡ Trust and transparency in AI interactions
♡ Conversation design patterns and best practices
This dedication to continual learning earned me the additional role as AI Global Media Ambassador within NIQ.
Discovery & Business Alignment
[Design Artifact 2: User Research Synthesis]Include a research synthesis artifact showing key user pain points and needs. This could be a user journey map highlighting friction points in the current research process, an empathy map showing researcher frustrations, or an affinity diagram grouping common themes from user interviews. This demonstrates your ability to translate user research into actionable insights.
I facilitated workshops with stakeholders to understand market researchers' specific needs and aligned the assistant's capabilities with strategic business goals:
♡ User Interviews: Conducted in-depth sessions with researchers to identify pain points
♡ Business Workshops: Connected user problems to measurable outcomes
♡ Competitive Analysis: Evaluated existing AI solutions to identify opportunities
♡ Data Analysis: Utalized our data to ensure market need
Collaboration with Development
[Design Artifact 9: Technical Collaboration Artifacts]Include examples of technical documentation or specifications you created to communicate design intent to developers. This could be API behavior specifications, AI response guidelines, or conversation state management documentation. This demonstrates your ability to translate design concepts into technical requirements that engineers can implement.
From concept phase, I partnered closely with technical teams to ensure design feasibility:
♡ Weekly Technical Sessions: Regular meetings with our Dev Lead to explore implementation of core features
♡ Security Collaboration: Engaged with security architecture team to integrate compliance frameworks
♡ Technical Documentation: Created detailed specifications for AI behavior and functionality
Design Methods & Prototyping
Design Artifact 3: Conversation Flow Diagram]Include a conversation flow diagram showing the core interaction patterns between users and Ask Cait. This should visualize how the AI assistant handles different user intents, processes queries, and manages conversation context. Consider using a decision tree or state diagram format to show the complexity of conversation management.
[Design Artifact 4: UI Prototype Screenshots]Include 3-4 key screens from your Figma prototype showing the conversation interface, how results are displayed, and any unique interaction patterns you designed. These should demonstrate your ability to create intuitive interfaces for complex AI interactions.
My approach combined established methodologies with AI-specific design techniques:
♡ Jobs To Be Done (JTBD): Defined primary user goals and use cases
♡ Conversation Design: Crafted tone, user prompts, and assistant replies
♡ Interactive Prototyping: Created Figma prototypes tested with internal users
♡ Iteration Cycles: Refined designs based on feedback around clarity, trust, and usefulness
Iterative Feedback Loop
I maintained all documentation and decisions in shared tools like Confluence, ensuring transparency and alignment across teams through:
♡ Regular stakeholder reviews
♡ Usability testing sessions
♡ Technical feasibility checks
♡ Business value assessments
Technical Implementation
[Design Artifact 5: Technical Architecture Diagram]Include a system architecture diagram showing how the various AI components work together. This should visualize the relationship between the LLM, vector database, memory system, and frontend components. This demonstrates your technical understanding and ability to communicate complex technical concepts visually.
Ask Cait is ongoing with development but we are hoping to leverage a sophisticated AI architecture combining multiple technologies to deliver an intuitive yet powerful research experience. At its core, the system will use OpenAI's GPT-4 Turbo model, selected specifically for its superior reasoning capabilities and reliability when handling complex research queries. To enhance the AI's knowledge base, we will implement a Retrieval-Augmented Generation (RAG) pipeline via LangChain, creating seamless connections to internal knowledge sources including documents, FAQs, and research reports. For efficient semantic search capabilities, the system aims to utilize Pinecone as its vector database, enabling rapid retrieval of relevant information across large document collections. On the frontend, I we will be utalizing our React-based interface with specialized chat UI components that make the complex AI capabilities accessible through an intuitive conversation format. As this is an ongoing project this is subject to change.
Results & Impact
[Design Artifact 6: Impact Metrics Dashboard]Include a visual dashboard highlighting key metrics and projected impact. This could show both quantitative data (usage statistics, time savings) and qualitative feedback from user testing. Consider using charts or graphs to visualize the generational AI usage statistics you mentioned. This demonstrates your data-driven approach and ability to connect design decisions to business outcomes.
While Ask Cait is still in development, our research-led approach has already revealed compelling evidence of future success. Our analysis of generational AI usage trends shows remarkable adoption rates, with 60.77% of Gen Z and 58.89% of Millennials already using AI personal assistants. Even more promising is the strongly positive sentiment toward AI in the workplace, with 70.07% of Gen Z and 67.82% of Millennials expressing favorable attitudes—clear indicators of strong product-market fit among emerging workforce segments.
Stakeholder alignment has been equally positive, with leadership identifying Ask Cait as a strategic solution to address key business challenges: reducing time spent navigating documentation and improving researcher onboarding processes. Internal prototype testing has validated our design direction, with users expressing particular enthusiasm for features like document Q&A, memory capabilities, and preference learning. Testers specifically highlighted the potential for accelerating insight discovery and simplifying complex tool navigation.
From a technical implementation standpoint, we are in process with our critical security architecture reviews and technical planning, clearing the path for development. Our projections indicate a 30-40% reduction in documentation navigation time during the initial phase alone. As we roll out more advanced features in later phases—including personalized insights, natural language querying, and cross-project knowledge synthesis—we expect Ask Cait to fundamentally transform how market research is conducted within the organization.
I reviewed the 2024 MRI-Simmons October Digital Life Study (SP24 USA) to better understand U.S. attitudes toward AI and then on actual usage of AI tools. First I check by generation how many people were using AI assistants:
Within the past 30 days, I have used an AI personal assistant*
I reviewed the 2024 MRI-Simmons October Digital Life Study (SP24 USA) to better understand U.S. attitudes toward AI and then on actual usage of AI tools. To then see if this is trending positive, I checked this useage over time.
Positive Artificial Intelligence Usage and Attitudes in the Workplace*
Unique Challenges & Innovations
[Design Artifact 7: Design System Components]Include examples from your AI conversation design system showing specialized components for different conversation states (question handling, result display, error states, etc.). This should demonstrate how you adapted traditional UI patterns for conversational AI. Consider showing before/after iterations to highlight your design thinking process.
AI-First Product Strategy
Ask Cait was designed as a conversation-led assistant from first principles, not as an AI add-on to existing tools. This allowed us to fundamentally rethink how users interact with research data through natural language.
Shift in Design Mindset
Unlike traditional interfaces with structured UI elements, designing for conversational AI required:
♡ Invisible Complexity: Creating simple interfaces that mask sophisticated conversation management
♡ Anticipatory Design: Predicting diverse user intents and providing appropriate responses
♡ Fallback Handling: Designing graceful recovery paths when the AI encounters limitations
♡ Context Management: Maintaining coherent conversations across multiple interactions
Security + Innovation Balance
Designing for a regulated enterprise environment added unique constraints. I worked closely with security teams to ensure compliance without compromising the user experience, balancing:
♡ Data privacy requirements
♡ Authentication and authorization models
♡ Audit trail implementation
♡ Content filtering and safety measures
Skill Set for the Project
Technical Skills
As the sole designer on this AI-focused project, I leveraged and expanded my technical skillset significantly. My AI-literate product design approach required deep understanding of large language models, retrieval-augmented generation systems, memory architectures, and prompt engineering principles—knowledge I applied directly to create technically feasible yet user-centered AI features. Throughout the process, I employed data-driven decision making by analyzing internal generational usage data to validate demand and shape feature prioritization.
The project demanded prototyping and conversation design skills as I built Figma prototypes that modeled complex conversation flows, fallback logic, and contextual messaging patterns. Perhaps most importantly, I demonstrated security-aware design practices, collaborating closely with technical teams to integrate enterprise security and compliance requirements from the earliest concept stages rather than retrofitting them later.
Soft Skills
The complex, cross-disciplinary nature of Ask Cait highlighted my strengths in cross-functional collaboration. I regularly partnered with engineering, security, product management, and business stakeholders through weekly working sessions and asynchronous documentation. My strategic communication abilities proved essential in aligning user needs with business objectives and clearly articulating value propositions to leadership.
Throughout the project, I maintained a strong curiosity and growth mindset, continuously upskilling through Coursera courses and industry research to inform best practices in AI product design. This commitment to learning enabled me to anticipate technical challenges and identify innovative solutions that balanced user needs with implementation feasibility.
Conclusion
[Design Artifact 8: Product Roadmap Visual]Include a visual roadmap showing the phased implementation plan for Ask Cait. This should outline current features, near-term additions, and future vision. Consider using a timeline format with feature clusters. This demonstrates your strategic thinking and ability to plan feature development strategically.
The Ask Cait project demonstrates the transformative potential of conversational AI in market research. As the sole Product Designer, I successfully navigated complex technical constraints and business requirements while creating an intuitive user experience that delivers measurable value. By combining advanced AI technology with thoughtful design principles, Ask Cait is positioned to significantly improve how researchers identify and engage with target audiences, ultimately leading to more effective marketing strategies and better business outcomes.
This project exemplifies my unique ability to bridge the gap between emerging technologies and user needs. I led the end-to-end design for a sophisticated AI product, balancing technical feasibility with user-centered design principles throughout the process. My effectiveness in collaborating across technical and business functions ensured alignment between technical capabilities and business goals. Most importantly, I demonstrated how design thinking can translate emerging AI technologies into valuable user experiences that solve real business problems.
Through Ask Cait, I've shown not just technical proficiency in AI design, but a strategic understanding of how these technologies can transform business processes and create competitive advantage. My holistic approach—combining technical knowledge, design expertise, and business acumen—represents exactly the kind of multidisciplinary talent needed to lead successful AI initiatives in today's rapidly evolving technological landscape.
