6 Steps to Build an AI Study Assistant (Research Chatbot) on Terapage: A Complete Guide for Modern Market Researchers

Terapage .ai

September 7, 2026 · 8 min read

6 Steps to Build an AI Study Assistant (Research Chatbot) on Terapage: A Complete Guide for Modern Market Researchers

Every researcher understands the feeling. The moment a research study goes live, the researchers' inboxes start filling up with basic questions. What does this study involve? How long will it take? What happens to my answers? Multiply that across a panel of hundreds of participants spread across different time zones, each asking individually.

Terapage's AI Chatbot Assistant is built for exactly this gap. It is a configurable, source-grounded chatbot that participants can talk to inside your study — one that answers using the materials you provide and cites where its answers come from.

What Is an AI Chatbot Study Assistant (Participant Support)?

A chatbot is a software application that behaves like an intelligent assistant when people interact with it via text or speech, using natural language processing (NLP) to understand one or more human languages. In its literal definition, a chatbot is described as "a computer program designed to simulate conversation with human users, especially over the Internet." They are also referred to as smart bots, interactive agents, digital assistants, or artificial conversational entities.

An AI Participant Support Chatbot is a specialised conversational application powered by Natural Language Processing and large language models, available on modern market research platforms for 24/7 virtual assistance to participants taking part in a study. Unlike rigid, menu-driven bots, it understands context, retains conversation history, and uses internally uploaded documents or the web to provide natural, human-like support.

Figure 1: Interactive AI Study Assistant interface on Terapage, enabling participants to have two-way conversations, ask questions, receive study-specific guidance, and interact with research resources in real time.

6 Steps to Build an AI Study Assistant (Research Chatbot) on Terapage

Creating an AI Chatbot Study Assistant on Terapage involves configuring several layers of the research experience. Here are the 6 steps to build an AI Study Assistant or research chatbot for your studies in Terapage workspaces.

Step 1: Select the Activity

Start by selecting the research activity where the AI Study Assistant will be used. The activity should have a clear purpose — for example, exploring participant experiences, providing guidance around study materials, supporting a research process, or facilitating a conversational research activity. The important thing is to define what the participant should accomplish through the conversation.

Figure 2: Researchers can create an AI Chat Assistant in Terapage by selecting it from the available research activities. The AI Chat Assistant can be configured to interact with participants and answer research-related questions.

Figure 3: Researchers can add custom instructions to the AI Chat Assistant by explaining what it is expected to answer and handle during conversations with participants.

Step 2: Configure the Assistant Settings

Terapage allows researchers to configure how their AI Study Assistant communicates, offering a wide variety of options to design an AI research assistant as per study requirements. For an HR research study it can be professional; for mental health research, the team can configure it to be supportive and empathetic.

1. Personality. Researchers can define the assistant's personality to match the study: Neutral, Friendly, Professional, Empathetic, Clinical, or Educational.

Figure 4: Researchers can configure the AI Chat Assistant's personality according to the study requirements.

2. Tone. The tone determines how the assistant communicates with participants and can be adapted to the research context. Available tones are Conversational, Formal, Supportive, Technical, and Simplified Language.

Figure 5: Terapage allows researchers to customize the AI Study Assistant's tone, helping create conversations that match the study's purpose and provide participants with a more natural and engaging experience.

3. Response Length. Researchers can determine whether responses should be brief and focused, or more detailed when explanations are required.

4. Citation Behaviour. Researchers can configure how the assistant references information from uploaded study resources — especially useful when participants need transparency about where an answer comes from. Terapage allows three citation behaviours: Cite when available, Always cite sources, and Never display citations.

Figure 6: At Terapage, researchers can also configure the AI Chat Assistant's citation behaviour, choosing whether or not to display sources.

5. Maximum Questions. Researchers can limit the number of questions asked during an interaction to keep the participant focused.

6. Maximum Duration. A maximum duration can be configured to establish a boundary for the participant's conversation.

7. Start and End Date. Researchers can specify when the AI Study Assistant activity should begin and when it should end.

8. Response Visibility. Researchers can determine how participant conversations and responses are made visible within the research workflow. Choosing Public visibility, for example, lets participants read each other's responses for basic details too.

Figure 7: Researchers can configure additional details in Terapage, including the activity's start and end dates and response visibility.

Step 3: Configure the Knowledge Settings

The AI Study Assistant doesn't answer randomly — it requires relevant knowledge to provide useful, study-specific answers. Terapage Knowledge settings let researchers define how the assistant will use knowledge during response generation, building a controlled knowledge environment around the study rather than expecting the AI to answer everything from general knowledge.

Figure 8: Researchers can configure external knowledge sources, including uploaded resources and internet search, to guide the AI Chat Assistant's responses.

For example, if a participant asks, "What does the study guideline say about this activity?" — the assistant uses the relevant uploaded study resource to answer. If the research team allows the assistant to use web sources, it can do so, and it will explicitly highlight that the generated response came from a web source.

Figure 9: AI Chat Assistant highlights web sources during conversations, allowing both researchers and participants to verify information and trace responses back to their original sources.

Step 4: Upload Knowledge Resources

Researchers can build the assistant's knowledge base by uploading relevant study materials. Terapage allows multiple document formats, including PDFs, Docs, TXT, CSV, audio, and video files.

Figure 10: Terapage lets researchers create multiple knowledge-source categories — such as Guidelines, FAQs, Onboarding, and Researcher Guides — to organize study resources during AI Study Assistant configuration.

Terapage allows researchers to organise resources into categories such as General, Guidelines, Onboarding, and FAQs. Resources can also be assigned different priorities — High, Medium, and Low — and researchers can control which resources are included.

Figure 11: Terapage allows researchers to assign High, Medium, or Low priority to knowledge documents, helping the AI Study Assistant prioritize relevant research resources when generating responses.

Step 5: Configure Notifications

Researchers can configure Notifications to inform their study participants about the creation of an AI research assistant. This is particularly useful when multiple participants are interacting with the AI Study Assistant. Instead of continuously sending details to every participant, research teams can use notifications to keep participants posted about relevant activity while letting the assistant handle participant interactions.

Step 6: Built-In Safety Controls for Responsible Research

Terapage AI Study Assistants include configurable safety controls during the design process that help researchers define clear boundaries for participant conversations. Researchers can add mandatory disclaimers, disallowed topics, and a refusal behaviour response. These controls help keep conversations focused on the research while giving participants clear guidance when a question falls outside the assistant's intended scope.

Figure 12: Terapage's Safety Controls allow researchers to define conversation boundaries, manage sensitive topics, add disclaimers, and guide how the AI Study Assistant responds when questions fall outside the study's scope.

Privacy Notice. Before beginning the activity, research teams add privacy details for the conversation with the AI Study Assistant. Participants can review this information before starting, including what information is collected, how conversations are used, whether files, images, or voice recordings are collected, who can review the conversation, and how the information is used within the study.

Figure 13: Terapage's privacy notice informs participants about conversation data, its use, and who can access it before they begin.

Participant Consent. Research teams can also add consent so participants can review the terms of participation and provide consent before entering the activity. The consent experience makes clear that participation is voluntary and explains what taking part in the specific research activity involves.

Figure 14: Terapage's participant consent screen clearly explains the study, voluntary participation, conversation review, and participant rights before they begin interacting with the AI Study Assistant.

Six Ways Research Teams Are Using Terapage AI Study Assistant Chatbots

1. Onboarding and FAQ for Longitudinal Studies

Daily diary or journal studies generate the same logistical questions on repeat. To avoid this, researchers can upload their onboarding deck and field guide once, and the assistant handles "how long does this take," "what am I supposed to log today," or "what the topic is about" without a researcher touching a single message.

Figure 15: Participants can ask the AI Chat Assistant questions related to the research topic and receive real-time, conversational guidance throughout their study participation.

2. Round-the-Clock Support Across Global Panels

Whether the fieldwork spans London, Lagos, or Toronto, participants aren't confined to specified working hours, because the assistant works 24/7 rather than to a person's calendar. Someone logging in at 2am local time gets the same quality of answer as someone logging in at 2pm.

Figure 16: Participants can access the AI Study Assistant around the clock for real-time guidance, answers, and support throughout their research participation.

3. Consistent, Source-Backed Guidance at Scale

With citation behaviour turned on, every participant receives an answer traceable to the same underlying document. This provides a detailed trail of exactly what the assistant told people and why, and shows which sources were used most and which gaps were identified.

Figure 17: Terapage AI Study Assistant provides source-referenced responses, showing external web sources used to support AI-generated answers for greater transparency and traceability.

Figure 18: Resource Utilisation provides an overview of the most frequently used resources and documents across Terapage, helping researchers identify which materials receive the highest engagement and usage.

4. A Safety-First Companion for Sensitive Subject Matter

Studies touching health, finance, or personal habits involve sensitive information. AI chatbot assistants are well suited to working with all kinds of participants by keeping responses private, and a request-support option is always one tap away if a conversation needs a human.

Figure 19: Participants can request support from a human moderator when they need additional guidance, ensuring timely review and assistance during the study.

5. A Qualitative Depth Booster

Participants can ask open, exploratory questions rather than sticking to scripted guidelines. This lets research teams collect richer context, follow-up reasoning, and clarifying questions, all captured and reviewable in the thread view.

Figure 20: The AI Chatbot provides participants with detailed, context-aware answers based on uploaded study resources, including references to the relevant sources for greater clarity and transparency.

6. Actionable Data and Visual Insights From Every Conversation

AI chatbot Study Assistants on Terapage do more than facilitate participant conversations — they turn those interactions into structured, reviewable research data. Researchers can monitor activity through dashboards showing total sessions, participants, questions, messages, average questions per session, and conversation trends over time. AI response-quality indicators can also highlight helpful, unhelpful, or out-of-scope interactions, while flagged messages draw attention to conversations that may need review. This gives research teams a quick visual snapshot of how conversations are going and helps them identify patterns, knowledge gaps, participant engagement, and areas for improvement without manually reviewing every interaction.

Figure 21: Terapage's AI Study Assistant dashboard provides a centralised view of participant engagement, questions, messages, conversation trends, and AI response quality, helping researchers monitor study performance and identify areas for improvement

AI Research Assistant: A New Layer of Conversational Research

The purpose of an AI Study Assistant or research chatbot is not to turn a research activity into a survey or replace researchers. Instead, it creates a conversational layer between participants, researchers, and study knowledge. Participants can ask questions, explore information, seek clarification, and share their experiences. Researchers can control the assistant's behaviour, knowledge, resources, and participant safeguards.

With Terapage, teams can move beyond static research materials and create a more interactive, conversational, and participant-centric research experience.

Select the activity. Configure the assistant. Build its knowledge. Add the resources. Set the controls. Protect participants. Then launch the conversation.