Project details

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Client:

IG Group

Tool:

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:


  1. Personalization Gap - No existing financial platforms offered truly personalized news experiences, creating a significant competitive advantage opportunity.

  2. Content Consumption Patterns - Users wanted different types of content at different times - pre-market summaries, real-time updates, and post-market analysis.

  3. Interactive Engagement - Users desired more engaging, interactive content beyond traditional article consumption.

  4. AI-Powered Summarization - Traders needed quick, digestible summaries rather than full articles to make time-sensitive decisions.

  5. Context-Aware Filtering - Users wanted content filtered by their actual positions and watchlists, not just general market categories.

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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:

  1. 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


  2. 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


  3. 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:

  1. 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


  2. 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


  3. 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:

  1. 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


  2. 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


  3. 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


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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 feature

Time-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 feature

Time-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 feature

Time-sensitive delivery matters - Content relevance varies significantly by market session and user schedule

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