Xaxis-人工智能时代的数字化战略：广告中如何利用人工智能（英文版）-2018-8页-2mb

Digital Strategy in the Age of Artificial Intelligence

Core Content

The document explores how artificial intelligence (AI) is transforming digital advertising strategies. It emphasizes that AI, particularly through machine learning, offers powerful tools to enhance marketing effectiveness by optimizing toward business outcomes rather than just traditional metrics. AI can be applied in both supervised and unsupervised learning modes, each offering distinct advantages in advertising.

Main Points

AI in Advertising

AI is being used to:

• Define and find audiences
• Refine creative messaging
• Generate audience personas
• Develop bidding strategies aligned with client goals

Supervised vs. Unsupervised AI

• Supervised AI is trained with known correct answers (e.g., determining the best bid price to win an impression).
• Unsupervised AI learns from data without predefined answers (e.g., identifying common traits among users who click on an ad).

AI in Programmatic Advertising

Programmatic advertising is ideal for AI due to the high volume and complexity of real-time decisions. AI helps in:

• Determining optimal bidding strategies
• Conducting extensive real-time testing
• Optimizing for cost-effectiveness and business outcomes

Designing Media Strategies for an AI World

AI enables more precise targeting and optimization by:

• Identifying prospects without bias or assumptions
• Focusing on cost-to-sales ratios rather than traditional metrics
• Making counter-intuitive decisions, such as prioritizing lower-cost clicks over high-CTR targeting

Key Information

AI-Powered Strategy Execution

To implement an AI-powered advertising strategy, marketers must:

• Design: Create a plan based on desired outcomes and parameters
• Implement: Use data sets to generate performance predictions and customize bidding strategies
• Optimize: Improve AI performance and achieve better results
• Analyze: Evaluate outcomes through custom reports to understand algorithm effectiveness

Importance of Talent

Success in AI-driven advertising requires:

• Skilled data scientists and engineers
• Customization of algorithms to fit specific business needs
• Expertise in handling both AI and marketing data

Partnering with AI Providers

Marketers should evaluate AI partners based on:

• Their experience with machine learning models
• Demonstrated revenue growth from AI installations
• Performance comparisons with manually traded campaigns
• Ability to handle multi-geography and multi-language requirements
• Customization of algorithms to integrate with client data and KPIs

Case Studies

Case Study 1: Telco (Telecom Company)

• Challenge: Managing 2,000+ campaigns with manual optimization
• Solution: Xaxis used Copilot AI to implement a "Segment Recency" strategy
• Outcome: Conversion rate more than doubled, and viewability goals were achieved

Case Study 2: Luxury Retailer

• Challenge: Achieving a unique ROAS (Return on Ad Spend) goal
• Solution: A customized regression algorithm and Xaxis' Predictor Strategy were used to identify high-performing impressions
• Outcome: Two flights showed improved performance, with increased conversion rates and clickthrough rates

Conclusion

AI is reshaping the advertising industry by enabling more efficient and effective strategies. It allows for deeper audience insights, better creative optimization, and more precise bidding. However, to fully leverage AI, advertisers must shift their mindset, invest in talent, and collaborate with AI providers that can deliver customized, data-driven solutions. The future of advertising lies in integrating AI into core strategies to drive real business results.