AWS re:Invent 2025 - Supercharge personalized experiences with Contentful and AWS (AIM296)

Supercharging Personalized Experiences with Contentful and AWS

The Content Collapse Challenge

• Marketers are faced with the ability to generate an infinite amount of content, but much of it is generic, boring, and fails to drive the desired customer behaviors.
• This "content collapse" is breaking marketers, who are asked to create more with fewer resources, while AI is supposed to solve these problems.
• However, AI is often implemented in the wrong part of the marketing stack, separate from the content layer, exacerbating the issue of generic, irrelevant content.

The Need for AI-Powered Personalization

• Personalization is not new, but it often fails due to siloed content, superficial personalization, inaccurate data, redundant experiences, poor measurement, and dependence on developers.
• Effective personalization requires:
  1. Structured content with a clear content model
  2. Automated guardrails to ensure brand and technical guidelines are met
  3. Context-aware content generation, considering user behavior, user characteristics, and marketing organization context
  4. An API-first delivery layer to distribute personalized content across channels

Integrating Contentful and AWS Bedrock

• Contentful partners with AWS to leverage the scalability and trust of the AWS platform, while AWS Bedrock provides the AI capabilities to power personalization.
• By integrating Bedrock directly into the Contentful content layer, marketers can access AI-powered content generation, localization, and user segmentation, all within the same platform they use to manage their content workflows and governance.
• This integration provides:
  • Speed, as content and AI work within the same platform
  • Safety, as governance and workflows are embedded in the content layer
  • Scale, leveraging the infrastructure and scalability of AWS

Implementing a Personalization Program

• Building a successful personalization program requires an iterative, data-driven approach:
  • Empower marketers to experiment and collect data on the impact of personalized experiences
  • Align personalization efforts with business goals and measure the results
  • Establish governance and control over the use of AI-powered content generation

Real-World Example: Craft Hind

• Craft Hind, a Contentful and AWS client, was able to unify their content portfolio, establish consistent governance, and leverage real-time personalization to drive business results:
  • 78% increase in conversion rates
  • 30% increase in engagement
  • Over 180 personalized experiences launched across their brand portfolio

Key Takeaways

• Integrating AI-powered personalization directly into the content layer, using a platform like Contentful and AWS Bedrock, can help marketers overcome the "content collapse" challenge.
• This approach provides speed, safety, and scalability, empowering marketers to create personalized, relevant experiences for their customers.
• Implementing a successful personalization program requires an iterative, data-driven approach, with a focus on governance and control over AI-powered content generation.
• Real-world examples, like Craft Hind, demonstrate the significant business impact of this approach to personalization.