AI-powered chatbots, while advanced, are restrained by the data they are trained on. Their effectiveness depends on real-time access to timely information and protection of proprietary data. Brands must ensure that their confidential information is managed correctly by employing tools like retrieval augmented generation (RAG), which can help integrate brand-specific data into AI models. As the marketing landscape evolves, demands for more control in retail media and inclusivity in industry initiatives are also becoming key focal points for marketers.
AI-powered chatbots are intelligent but rely heavily on the quality of their training data, which must be timely and secure to work effectively.
Retrieval augmented generation (RAG) provides a solution for companies to securely input proprietary data into their chatbots, ensuring relevant responses.
Hugo Loriot emphasizes that there's a distinction between public data and proprietary brand information, which requires specific handling in AI training.
Marketers are advocating for enhanced real-time bidding capabilities in retail media to gain better control over their advertising strategies.
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