How AI will help marketers understand the ‘why’ behind engagement rates

OpenAI executive Ed Baker’s TED talk outlines how artificial intelligence will transform business engagement analysis by automatically identifying and adapting to cultural nuances and user behaviors that affect conversion rates.

The evolution of engagement metrics: Ed Baker’s extensive experience at major tech companies like Facebook and Uber has provided unique insights into how businesses measure and optimize user engagement.

• Baker’s career spans from Harvard in the late 90s through leadership roles at Facebook and Uber, where he developed expertise in viral growth and user conversion
• His early projects included social apps and dating sites that helped pioneer engagement metrics like the K-factor and lifecycle activity analysis
• These metrics enable businesses to track how effectively their products and services convert initial users into engaged customers

Cultural adaptation case studies: Real-world examples demonstrate how understanding cultural contexts can dramatically improve engagement rates.

• Facebook faced low invitation rates in Japan until research revealed cultural stigmas around invitations, leading to successful copy adjustments
• Uber’s India expansion struggled until the platform adapted to local payment preferences by introducing cash payment options
• These examples highlight how cultural awareness and willingness to adapt can transform underperforming markets into success stories

AI’s role in optimization: Artificial intelligence can automate the process of identifying and responding to engagement barriers without human intervention.

• AI systems can continuously test new approaches and analyze results, similar to traditional A/B testing but at a much larger scale
• Unlike human decision-makers who may hesitate to implement dramatic changes, AI can objectively evaluate and implement optimizations
• The technology can identify complex patterns in human behavior and cultural preferences that might not be immediately apparent to human analysts

Automation of engagement analysis: The future of business intelligence will rely less on traditional market research and more on AI-driven insights.

• AI can replace manual processes like focus groups and market surveys with continuous, real-time analysis
• The technology can simultaneously test multiple approaches across different markets and user segments
• Businesses will need to focus more on effectively implementing AI tools rather than conducting manual market research

Looking ahead: While AI promises to streamline engagement optimization, its success will depend on businesses’ ability to properly implement and trust these automated systems while maintaining awareness of ethical considerations and potential biases in algorithmic decision-making.