Project details
Client:
IG Group
Tool:
Figma, Adobe Illustrator, Maze, Hotjar, Google Analytics
Figma, Adobe Illustrator, Maze, Hotjar, Google Analytics
Personalised Feed + AI Content
Challenge
Building on the foundation of the Explore Hub, we identified a significant opportunity to revolutionize how traders consume financial news. With only 6% of users engaging with news features, we recognized that the traditional approach of providing generic Reuters feeds wasn't meeting the sophisticated needs of modern traders. The challenge was to create a truly personalized, AI-powered content experience that would deliver relevant, actionable information tailored to each user's specific trading interests and portfolio.
Problem
Generic Reuters news feed that wasn't relevant to individual traders
Basic personalization
Content overload leading to decision paralysis
Lack of actionable insights from news consumption
Missing connection between news consumption and trading activity
Users struggling to find information relevant to their specific trading strategy
Research insights
Through user interviews, competitive analysis, and data science collaboration, we identified key opportunities:
Personalization Gap - No existing financial platforms offered truly personalized news experiences, creating a significant competitive advantage opportunity.
Content Consumption Patterns - Users wanted different types of content at different times - pre-market summaries, real-time updates, and post-market analysis.
Interactive Engagement - Users desired more engaging, interactive content beyond traditional article consumption.
AI-Powered Summarization - Traders needed quick, digestible summaries rather than full articles to make time-sensitive decisions.
Context-Aware Filtering - Users wanted content filtered by their actual positions and watchlists, not just general market categories.
Solution
1. Content Strategy & AI Integration
Working closely with Data Science, I developed a comprehensive personalization strategy:
Heuristic Model Integration:
User portfolio analysis for content relevance scoring
Trading behavior patterns for content type preferences
Time-based content delivery optimization
Social sentiment integration from community trading patterns
AI Summarization Framework:
On-demand article summarization with clear AI attribution
Personalized "For You" content generation based on portfolio
Global news snapshot with high-impact financial news focus
Market pulse summaries with sector-specific insights
2. Information Architecture Redesign
I restructured the Explore Hub into main content pillars:
Newsfeed section
Enhanced filtering system:
All news (comprehensive feed)
Opened positions (portfolio-specific news)
My watchlists (interests-based content)
AI summarization CTA on every article
Interactive Stories Framework
Three distinct story types addressing different user needs:
Market Pulse Stories
Pre-market summaries with sector breakdowns
Market overview with interactive sentiment voting
Broker ratings with actionable insights
Market wrap with performance analysis
Trending Now Stories
Biggest risers/fallers with social sentiment
Corporate highlights with immediate impact assessment
Unusual market activity with volume analysis
Interactive prediction polls on trend continuation
Major Events Stories
Economic calendar events with market impact ratings
Earnings reports with forecast vs. actual comparisons
Market focus summaries with expert analysis
Insights Section
Consolidated trading intelligence tools:
Economic calendar with personalized event filtering
Top 100 Traders with position transparency
Trade of the Day with detailed analysis
Top stocks with TipRanks integration
Expert analysis from IG analysts
3. AI-Powered Content Generation
"For You" Personalized Feed
Tailored news based on watchlist and positions
Portfolio impact analysis for each story
Personalized timing for content delivery
Trading behavior-based content recommendations
Global News Snapshot
Broad, high-impact financial news
Geographic and sector-based categorization
Impact scoring for market-moving events
Curated by AI with editorial oversight
Market Pulse Integration
Real-time market sentiment analysis
Interactive elements for user participation
Social trading insights integration
Predictive content based on market patterns
4. Interactive Elements Design
Sentiment Voting
Market direction predictions with community results
Individual stock trend forecasting
Real-time results showing trader sentiment
Social Trading Integration
Transparency into successful trader positions
Community-driven market insights
Performance-based credibility indicators
Solution
1. Content Strategy & AI Integration
Working closely with Data Science, I developed a comprehensive personalization strategy:
Heuristic Model Integration:
User portfolio analysis for content relevance scoring
Trading behavior patterns for content type preferences
Time-based content delivery optimization
Social sentiment integration from community trading patterns
AI Summarization Framework:
On-demand article summarization with clear AI attribution
Personalized "For You" content generation based on portfolio
Global news snapshot with high-impact financial news focus
Market pulse summaries with sector-specific insights
2. Information Architecture Redesign
I restructured the Explore Hub into main content pillars:
Newsfeed section
Enhanced filtering system:
All news (comprehensive feed)
Opened positions (portfolio-specific news)
My watchlists (interests-based content)
AI summarization CTA on every article
Interactive Stories Framework
Three distinct story types addressing different user needs:
Market Pulse Stories
Pre-market summaries with sector breakdowns
Market overview with interactive sentiment voting
Broker ratings with actionable insights
Market wrap with performance analysis
Trending Now Stories
Biggest risers/fallers with social sentiment
Corporate highlights with immediate impact assessment
Unusual market activity with volume analysis
Interactive prediction polls on trend continuation
Major Events Stories
Economic calendar events with market impact ratings
Earnings reports with forecast vs. actual comparisons
Market focus summaries with expert analysis
Insights Section
Consolidated trading intelligence tools:
Economic calendar with personalized event filtering
Top 100 Traders with position transparency
Trade of the Day with detailed analysis
Top stocks with TipRanks integration
Expert analysis from IG analysts
3. AI-Powered Content Generation
"For You" Personalized Feed
Tailored news based on watchlist and positions
Portfolio impact analysis for each story
Personalized timing for content delivery
Trading behavior-based content recommendations
Global News Snapshot
Broad, high-impact financial news
Geographic and sector-based categorization
Impact scoring for market-moving events
Curated by AI with editorial oversight
Market Pulse Integration
Real-time market sentiment analysis
Interactive elements for user participation
Social trading insights integration
Predictive content based on market patterns
4. Interactive Elements Design
Sentiment Voting
Market direction predictions with community results
Individual stock trend forecasting
Real-time results showing trader sentiment
Social Trading Integration
Transparency into successful trader positions
Community-driven market insights
Performance-based credibility indicators
Solution
1. Content Strategy & AI Integration
Working closely with Data Science, I developed a comprehensive personalization strategy:
Heuristic Model Integration:
User portfolio analysis for content relevance scoring
Trading behavior patterns for content type preferences
Time-based content delivery optimization
Social sentiment integration from community trading patterns
AI Summarization Framework:
On-demand article summarization with clear AI attribution
Personalized "For You" content generation based on portfolio
Global news snapshot with high-impact financial news focus
Market pulse summaries with sector-specific insights
2. Information Architecture Redesign
I restructured the Explore Hub into main content pillars:
Newsfeed section
Enhanced filtering system:
All news (comprehensive feed)
Opened positions (portfolio-specific news)
My watchlists (interests-based content)
AI summarization CTA on every article
Interactive Stories Framework
Three distinct story types addressing different user needs:
Market Pulse Stories
Pre-market summaries with sector breakdowns
Market overview with interactive sentiment voting
Broker ratings with actionable insights
Market wrap with performance analysis
Trending Now Stories
Biggest risers/fallers with social sentiment
Corporate highlights with immediate impact assessment
Unusual market activity with volume analysis
Interactive prediction polls on trend continuation
Major Events Stories
Economic calendar events with market impact ratings
Earnings reports with forecast vs. actual comparisons
Market focus summaries with expert analysis
Insights Section
Consolidated trading intelligence tools:
Economic calendar with personalized event filtering
Top 100 Traders with position transparency
Trade of the Day with detailed analysis
Top stocks with TipRanks integration
Expert analysis from IG analysts
3. AI-Powered Content Generation
"For You" Personalized Feed
Tailored news based on watchlist and positions
Portfolio impact analysis for each story
Personalized timing for content delivery
Trading behavior-based content recommendations
Global News Snapshot
Broad, high-impact financial news
Geographic and sector-based categorization
Impact scoring for market-moving events
Curated by AI with editorial oversight
Market Pulse Integration
Real-time market sentiment analysis
Interactive elements for user participation
Social trading insights integration
Predictive content based on market patterns
4. Interactive Elements Design
Sentiment Voting
Market direction predictions with community results
Individual stock trend forecasting
Real-time results showing trader sentiment
Social Trading Integration
Transparency into successful trader positions
Community-driven market insights
Performance-based credibility indicators
User Testing & Validation
Comprehensive testing validated our personalization approach::
28 users participated across different experience levels
89% success rate for finding relevant, personalized content
73% improvement in content relevance ratings
82% of users engaged with AI summarization features
91% positive feedback on interactive story elements
Conclusion
Personalization drives engagement - Context-aware content dramatically increased user participation
AI augmentation, not replacement - Users appreciated AI summaries but wanted human editorial oversight
Interactive elements create stickiness - Voting and prediction features significantly increased session duration
Portfolio integration is crucial - Filtering by actual positions was the most valued featureTime-sensitive delivery matters - Content relevance varies significantly by market session and user schedule
User Testing & Validation
Comprehensive testing validated our personalization approach::
28 users participated across different experience levels
89% success rate for finding relevant, personalized content
73% improvement in content relevance ratings
82% of users engaged with AI summarization features
91% positive feedback on interactive story elements
Conclusion
Personalization drives engagement - Context-aware content dramatically increased user participation
AI augmentation, not replacement - Users appreciated AI summaries but wanted human editorial oversight
Interactive elements create stickiness - Voting and prediction features significantly increased session duration
Portfolio integration is crucial - Filtering by actual positions was the most valued featureTime-sensitive delivery matters - Content relevance varies significantly by market session and user schedule
User Testing & Validation
Comprehensive testing validated our personalization approach::
28 users participated across different experience levels
89% success rate for finding relevant, personalized content
73% improvement in content relevance ratings
82% of users engaged with AI summarization features
91% positive feedback on interactive story elements
Conclusion
Personalization drives engagement - Context-aware content dramatically increased user participation
AI augmentation, not replacement - Users appreciated AI summaries but wanted human editorial oversight
Interactive elements create stickiness - Voting and prediction features significantly increased session duration
Portfolio integration is crucial - Filtering by actual positions was the most valued featureTime-sensitive delivery matters - Content relevance varies significantly by market session and user schedule