User Researcher AI Agent
This User Researcher AI Agent is designed to streamline the process of obtaining participant consent, registrations and surveys for research studies. The AI Agent engages participants in a friendly, conversational manner, ensuring they understand the research details and their rights before providing consent and participation. It collects vital information such as participant names, contact details, and signatures, making the consent process efficient and effective.
The purpose of the User Researcher AI Agent is to facilitate the collection of informed consent from participants in research projects. It presents the necessary information clearly, allowing participants to make informed decisions about their involvement. By using conversational AI, this agent enhances participant engagement and ensures compliance with research protocols.
This AI Agent is ideal for researchers, academic institutions, and organizations conducting studies that require participant consent. It can be used by:
The User Researcher AI Agent can be applied in various contexts, including:
This AI Agent collects essential data such as participant names, ages, contact information, and signatures. It can present research details, outline participant rights, and clarify the purpose of the study. The agent is customizable, allowing researchers to tailor the conversation flow and appearance to match their branding. Additionally, the agent can handle multiple forms and surveys, making it versatile for various research needs.
Creating a User Researcher AI Agent using Jotform is straightforward. You can start from scratch by describing the agent’s purpose, select an existing form, or clone a ready-made template. The agent designer allows you to customize the look of your agent, including colors and fonts, to align with your research branding. You can add multiple forms and actions to collect diverse data types and utilize conditional actions to enhance the conversation flow.
Training the User Researcher AI Agent is simple and effective. Researchers can interact with the agent to refine its responses, add a knowledge base with FAQs, and incorporate URLs or documents related to the research. By setting up questions and answers, the agent becomes context-aware, providing personalized responses that improve over time based on participant interactions.