Content
Introduction
This Applied Use Guide provides strategies for deploying AI in marketing campaigns—whether through generative ad content or automated audience targeting—in a way that respects user privacy, avoids misleading information, and champions fairness and diversity.
Reason Why
AI-driven marketing can amplify brand reach and tailor messages at scale. However, if algorithmic targeting inadvertently excludes certain groups, or generative ads spread unverified claims, companies risk public backlash and regulatory scrutiny. Upholding ethical guidelines fortifies credibility and fosters trust among consumers.
Key Principles
- Transparency: Clearly disclose how AI personalizes marketing messages or decides ad placements.
- Fairness: Prevent discrimination by not allowing algorithms to exclude or stereotype people based on protected traits (race, gender, etc.).
- Privacy: Collect the minimum viable data for targeted advertising, and comply with data protection regulations to preserve consumer trust.
- Accuracy: Use AI to provide factual, truthful information—especially when generating product descriptions or brand claims.
- Auditability: Maintain verifiable records of data sources, ad variations, and targeting parameters to ensure accountability and compliance.
Best Practices
- Maintain Transparency with Consumers: Let users know AI is powering personalized content or dynamic pricing, explaining the benefits and any data used.
- Protect Consumer Privacy: Implement strong encryption for data at rest and in transit. Honor opt-outs from data sharing and run routine privacy audits.
- Avoid Bias in Audience Segmentation: Periodically review how your AI segments audiences, ensuring no demographic is unfairly excluded or exploited.
- Regularly Audit AI Systems: Check for compliance with brand standards and ethical codes, removing any problematic ad campaigns or content promptly.
- Use Human Oversight: Even the best AI can produce off-brand or insensitive content. Marketers should approve final messaging, especially for sensitive topics.
Specific Techniques
Technique 1: Personalized Messaging
Default Prompt: Create personalized email content for our new product launch.
Updated Prompt: Create personalized email content for our new product launch. Make sure the AI respects user data preferences (e.g., unsubscribed categories), avoid stereotypes, and label AI-generated content so recipients understand how customization was derived.
Technique 2: Audience Segmentation
Default Prompt: Segment our audience for the upcoming marketing campaign.
Updated Prompt: Segment the audience responsibly for an upcoming marketing campaign, clarifying how AI uses data points like interests or purchase history without leveraging protected attributes. Provide rationale for each segment, and show steps taken to ensure fairness.
Technique 3: Performance Analysis
Default Prompt: Analyze the performance of our recent social media campaign.
Updated Prompt: Analyze the performance of our recent social media campaign. Discuss how AI calculated reach, engagement, and conversion metrics, noting potential biases (e.g., skewed user demographics on certain platforms). Suggest improvements or new tests to refine accuracy.
Technique 4: Ad Targeting
Default Prompt: Generate a targeting strategy for our online ads.
Updated Prompt: Generate a targeting strategy for our online ads that respects data privacy and avoids harmful stereotyping. Explain which data points are used (behavioral, contextual, etc.), how they’re validated, and what steps ensure no protected category is excluded or unfairly priced.
