9 Harnessing context for an adaptive virtual assistant experience

 

This chapter covers

  • Applying context appropriately in virtual assistant interactions
  • Adapting conversational AI for different modalities
  • Identifying pain points caused by ignoring modality

Effectively applying context in virtual assistant interactions is imperative for delivering seamless and intuitive user experiences. Users expect virtual assistants to understand their queries and to do so within their contexts. This chapter focuses on the three critical sources of personalization in virtual assistant technologies: context, modality, and retrieval-augmented generation (RAG). Each of these enhances how virtual assistants understand and interact with users.

Context is about tailoring interactions based on the situational and historical data available about a user. For example, responding to a query about the weather by considering the user’s current location and time illustrates effective context usage compared to a generic forecast.

Modality refers to the user’s method of communication, such as voice, text, or visual interfaces. Each modality offers distinct advantages and challenges. Adapting virtual assistants to the chosen modality ensures seamless interaction, whether users are typing a message, speaking to their device, or interacting through a graphical interface.

9.1 Importance of context in virtual assistant performance

9.1.1 How context influences user interactions

9.1.2 What is contextual information?

9.2 Understanding modality

9.2.1 Comparing modalities

9.2.2 Importance of modality in designing virtual assistant flows

9.2.3 Examples of how modality affects user experience

9.2.4 Voice bot design considerations

9.3 Enhancing context awareness and improving the overall user experience with RAG

9.3.1 Designing adaptive flows with RAG

9.3.2 Strategies for retrieving and generating contextually relevant responses

9.3.3 Maintaining and updating adaptive flows

Summary