Profound
Designed the core product experience for Profound — an AI search intelligence platform helping brands understand and optimize how AI agents like ChatGPT, Perplexity, and Copilot talk about them.
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The Problem
AI answer engines are changing the way people discover products. Instead of typing keywords, people are asking AI assistants conversational questions. Traditional SEO tools have no way of showing what is actually being asked.
This shift created three big challenges for marketers:
No visibility into trending prompts and emerging topics
No clear sentiment analysis or share of voice for AI results
No way to see which competitors dominate AI conversations
Early users told us they did not want raw data dumps. They wanted clarity, trends, and actionable insights.
Role and Team
I worked closely with engineers and data scientists, leading design from start to finish. My responsibilities included research, UX flows, UI design, and building a scalable design system. I also worked with the founders on product strategy, deciding which insights mattered most and how to present them in a way marketers could act on.
Approach
User Research
I spoke with growth teams, content strategists, and AI researchers using Profound's early prototype. We found that AI search patterns often had little overlap with Google, that AI conversations covered the entire marketing funnel, and that marketers wanted the ability to group related prompts, track sentiment, and see which websites influenced AI answers.
Competitive Research
I analysed leading SEO and keyword-tracking tools including Semrush, Ahrefs, Ubersuggest, and Google Trends. While they excel at keyword rankings and backlink analysis, none could surface AI prompt-level insights or reveal how AI agents respond to real questions. This confirmed that Profound had a clear opportunity to lead in a new category.
Design and Development
Hierarchical Explorer allowed users to move from broad topics to specific prompts, making large datasets easy to navigate
Bulk Analysis let marketers compare up to 200,000 prompts with advanced filters for date, region, language, and AI platform
Answer Engine Insights provided dashboards with visibility scores, sentiment breakdowns, and share of voice trends
Agent Analytics gave human-readable visualisations of AI crawler activity across domains
Design System used modular Figma components to maintain consistency and speed up engineering
Challenges
Translating billions of real-time data points into a clear, usable interface
Designing around privacy restrictions by summarising and grouping prompts instead of showing raw text
Turning technical crawler logs and sentiment models into practical, actionable insights for marketers
Solution
Answer Engine Insights to track mentions, sentiment, and competitor share of voice
Agent Analytics to monitor AI crawlers and link their activity to traffic
Conversation Explorer to reveal trending questions and hidden AI search patterns
A scalable design system supporting both enterprise clients and a $499/month self-serve plan
Impact
Ramp increased AI visibility in the accounts-payable sector from 3.2% to 22.2% in one month
1840 and Company went from zero to 11% AI visibility in remote staffing, entering the top five in their category
Profound now processes more than 100 million queries per month across 18 countries and 6 languages
Early adopters reported a 25–40% lift in AI share of voice within 60 days
Reflection
Profound showed me how rapidly shifting industry trends can create entirely new product categories. I learned to design within data privacy and technical constraints while making complex AI insights accessible. The project reinforced the value of aligning user experience with evolving behaviours in how people search and consume information.