DEV Community: LAIBA CHAUHDRY

Understanding the Patient Journey: How Mobile Ethnography Captures Real-Life Experiences

LAIBA CHAUHDRY — Wed, 04 Nov 2026 08:14:37 +0000

Key takeaways
The patient journey covers everything from first symptoms and diagnosis to treatment, care visits and daily self-management, including what happens between appointments.
Mobile ethnography lets patients record that journey on their own phones, in text, photos, voice notes, videos and documents, as it happens.
The strongest patient journey studies combine a mobile patient diary (what happens) with a one-to-one live video interview (why it happens).
This guide walks through a real example: a 21-day asthma patient diary followed by a 30-minute deep-dive interview on Terapage.
AI summaries, sentiment analysis, excerpts and taxonomies turn patient stories into findings, translated into more than 130 languages.
A patient with asthma gets ten minutes with their nurse. The nights spent coughing on the sofa, the early exit from the bus and the worried child at home rarely make it into that conversation. Yet these are the moments that shape how patients manage their condition.

The scale is huge. The World Health Organization reports that asthma affected 363 million people in 2023, and under-treated asthma disrupts sleep, energy and focus. Mobile ethnography helps researchers see this hidden side of care. Patients record their experiences on their phones as they happen, and researchers follow up to understand the reasons behind them.

What Is the Patient Journey in Healthcare Research?
“The patient journey is the full experience of living with a condition, from first symptoms and diagnosis to treatment, care visits and daily self-management, including everything that happens between appointments.”

Most research only sees the clinic side of this journey. Surveys and one-off interviews depend on memory, so small but important moments, like a skipped inhaler or a new trigger, are easily forgotten. For healthcare and pharmaceutical research teams, these everyday details often hold the most useful insight.

Why Mobile Ethnography Works for Patient Journey Research
Mobile ethnography is a form of ethnography where participants record their own lives on their smartphones, in their own settings. Instead of asking patients to remember, it lets them show what happens as it happens. Learn more in our guide to mobile ethnography. For patient research, it:

Captures moments in real time, so symptoms and feelings are recorded while they are fresh.
Shows real-life settings, such as home, work and the daily commute.
Gives patients a voice, letting them share emotions they may not mention in a clinic.
Fits around daily life, with no travel or clinic visit needed.
How to Set Up a Mobile Ethnography Study to Map the Patient Journey
The strongest studies combine two methods. A patient diary captures what happens in daily life, and a live video interview explores why it happens. Our example is a 21-day asthma diary followed by a one-to-one interview, both run on Terapage.

Create a Patient Diary Activity
Start by creating a new research activity and selecting Journal Research Activity. This lets each patient submit multiple diary entries over the study period, building a clear picture of their journey over time.

Figure 1: Selecting the Journal Research Activity on Terapage to set up a mobile ethnography patient diary study.
Write Simple, Patient-Friendly Instructions
Clear instructions help patients know exactly what to share. Our diary explains the purpose, the 21-day duration, the minimum of three entries, what to record and how privacy is protected. Health data is sensitive, so Terapage keeps it on a secure, GDPR-compliant platform.

Figure 2: Patient-friendly diary instructions explaining the study purpose, 21-day duration, entry requirements and privacy guidance.
How Mobile Ethnography Captures Real-Life Patient Experiences
Once the diary is live, patients take part from their own phone, on any device. They can add an entry whenever something happens and choose the format that suits the moment.

Tracking the Patient Journey Day by Day
The diary dashboard shows each patient their entries submitted, days remaining and when their next entry is due, with the study instructions always in view. If a patient forgets, daily reminders prompt them to log their entry, and unfinished entries are saved as drafts they can resume anytime. This means fewer drop-outs and richer data.

Figure 3: A patient’s mobile diary dashboard showing entries submitted and days remaining, helping patients stay engaged.

Capturing Patient Experiences in Their Own Words
Text entries let patients describe what happened and how it felt, and they save automatically as patients type. In this entry, a patient shares how hard it was to talk about broken nights and work shifts with their nurse.

Figure 4: A text diary entry where a patient describes their care visit, broken nights and work shifts in their own words.

Seeing Real-Life Context Through Patient Photos
A photo with a short note shows what words can miss, like where a patient keeps their inhaler. This photo voice method gives researchers a direct view into the patient’s world.

Recording In-the-Moment Symptoms With Voice Notes
After a coughing fit or on a busy commute, typing is the last thing a patient wants to do. Voice notes let them simply tap and speak, capturing the moment while it is still fresh.

Figure 6: A patient recording an in-the-moment voice note about their symptoms directly from their phone.

Patients can add a short note to each recording. Here, a patient describes leaving the bus early after a coughing fit, a detail often forgotten at appointments.

Figure 7: An uploaded voice note with a written description of a coughing episode during the patient’s commute to work.

Showing Daily Health Routines Through Video and Documents
Videos show routines in action, such as how a patient uses their inhaler or prepares for bed. Patients can record in the app or upload a video from their phone.

Figure 8: A video diary entry showing how patients can record or upload daily health routines from their phone.

Documents add another layer. Patients can upload their asthma action plan, a prescription leaflet or their own notes, helping researchers compare medical advice with what patients actually do.

Figure 9: A document diary entry where patients share action plans, prescription leaflets or symptom notes.

Bringing Every Patient Story Into One Feed
All entries come together in one feed that can be filtered by text, image, audio or video. AI also describes each photo, so visual entries can be analysed alongside written ones. This entry shows how asthma affects the whole family, as a patient’s daughter notices him sleeping on the sofa. See how real-time patient narratives are transforming healthcare.

Figure 10: All patient diary entries in one filterable feed, with an AI-generated description of each photo for analysis.
Going Deeper Into the Patient Journey With Live Video Interviews
Diary entries often raise new questions. Why does a patient not follow their action plan? What stops them from seeking help sooner? A one-to-one video interview lets researchers explore these answers directly. Learn more about AI-powered live video interviews.

Scheduling One-to-One Patient Interviews
Our follow-up, the Asthma Journey Deep-Dive Interview, is a 30-minute session. The overview shows the scheduled date, duration, status and completion points in one view.

Figure 11: Live video interview overview showing the scheduled date, session duration, status and completion points.

The Calendar menu gives researchers everything they need to run the interview, from scheduled meetings and in-meeting tasks to participants and the Interview Brief.

Figure 12: The Calendar menu for managing scheduled meetings, in-meeting tasks, participants and the Interview Brief.

To book a session, researchers choose a time slot, select a patient who completed the diary and assign a moderator from the research team.

Figure 13: Scheduling a one-to-one patient interview by selecting a time slot, diary participant and research team moderator.

Once saved, the slot is marked as Upcoming and can be cancelled if plans change.

Figure 14: A booked patient interview slot marked as Upcoming, with the option to cancel if plans change.

A Mobile-First Interview Experience for Patients
Patients see the interview details on their phone, including what the session will cover and how it builds on their diary entries.

Figure 15: Interview details on a patient’s phone, explaining what the session covers and how it builds on their diary entries.
Before joining, they can check their camera and microphone, or choose to join with audio only.

Figure 16: The mobile join screen where patients check their camera and microphone before the live interview.

During the call, simple controls for the microphone, camera, chat and live transcript make it easy to take part. Joining from home helps patients feel relaxed and speak openly.

Figure 17: A live one-to-one video interview on a patient’s phone, with simple controls for chat, camera and transcript.

In-Interview Tasks That Reveal Real-Life Behaviour
Researchers can send questions, images and polls into the chat during the interview. An open question lets patients tell their story, from diagnosis to how asthma affects them today.

Figure 18: An open in-interview question where a patient shares their asthma journey from diagnosis to daily life today.

Image tasks help patients react to something concrete. When shown an asthma action plan, this patient admitted they don’t follow it closely and often stay in the amber zone too long, revealing a clear gap between advice and real behaviour.

Figure 19: An image task using an asthma action plan, revealing the gap between medical advice and real patient behaviour.

Figure 20: In-interview polls capturing quick, structured answers on symptom management and daily impact.

Guided Moderation With Interview Briefs and Live Transcripts
The Interview Brief sits beside the video and holds the session purpose, key questions, expected outcomes and meeting notes. It keeps the moderator focused and the conversation on track.

Figure 21: The Interview Brief panel guiding the moderator with the session purpose, key questions and meeting notes.

Live transcription captures every word as it is spoken, so moderators can focus on listening instead of taking notes.

Figure 22: Live transcription capturing the patient interview word for word, so moderators can focus on listening.
Turning Real-Life Patient Experiences Into Insights
Collecting patient stories is only half the job. Terapage’s AI-powered insights turn diary entries and interview answers into clear findings, so researchers can see the patterns across the whole patient journey without reading every entry by hand.

Tracking Patient Diary Participation at a Glance
The activity dashboard shows how many patients are taking part, how many have completed the diary, who is in progress and who has not started yet. Researchers can filter by status, include or exclude patients from reports and open each person’s insights in one click.

Figure 23: The patient diary dashboard showing total participants, completed submissions, entries in progress and awaiting responses.
Reviewing Each Patient’s Journey
Every patient has their own page with all their diary entries in one place. AI automatically describes each photo, picking out details such as an inhaler on the nurse’s desk or symptom notes on a phone screen.

Figure 24: A patient’s submitted journal entries, with a written note and an AI-generated description of their photo.

Voice notes are transcribed automatically and documents are summarised by AI. Here, the transcript reveals that a strong fragrance on the bus triggered the coughing, a detail the patient said they would usually leave out at appointments.

AI Summaries That Connect Patient Stories
The AI Summary brings all responses together into one report, covering cross-participant themes, areas of agreement and differences between patients. In this study, it shows a shared frustration with getting inhalers from the pharmacy on time. Researchers can highlight, comment and save key excerpts directly on the summary.

Figure 26: An AI summary of the asthma patient diary, highlighting cross-participant themes and areas of consensus.

Summaries can also be translated into more than 130 languages, which makes it easy to share findings with global healthcare teams or run patient studies across different countries.

Figure 27: The AI summary translated into Urdu, showing multilingual reporting for global patient research.
How Does Sentiment Analysis Reveal the Emotional Side of the Patient Journey?
Living with a long-term condition is emotional, and sentiment analysis shows how patients really feel. In this study, concern and frustration were the strongest moods, mostly linked to delays in getting medication and booking appointments. Each mood comes with its key statement, strength and number of responses. Learn more in our beginner’s guide to AI sentiment analysis.

Figure 28: Sentiment analysis of patient diary responses, showing concern and frustration as the leading moods.
Uncovering Patient Journey Themes With AI Excerpts and Taxonomies
AI excerpts rank the topics patients mention most, such as health concerns, communication with care teams and emotional impact. This shows researchers where to focus first.

Figure 29: AI excerpts ranking the most discussed topics in the patient diary, led by health concerns and communication.
Taxonomies organise these findings into categories and subcategories, each linked to real patient quotes. For example, Emotional Impact breaks down into anxiety and worry, relief after communication and embarrassment about symptoms. Findings can then be shared through branded insight reports.

Figure 30: Taxonomies grouping patient experiences into categories, with Emotional Impact expanded into subcategories.
Map the Real Patient Journey With Mobile Ethnography on One Unified Platform
Patients live with their condition every day, not just on clinic days. Terapage brings every step of patient journey research into one place. Terapage Asynchronous captures real-life moments through journal, diary and mobile ethnography studies, Terapage Live explores the reasons behind them in one-to-one interviews, and a long-term insight community keeps patients engaged across months, not just one study.

Every product is powered by shared platform features, including AI-powered insights, e-consents, security and compliance, native mobile apps for participants and support for 30 languages. See how Allied Care improved its care services with Terapage.

Open vs. Guided vs. Flexible: How to Choose the Right Method of Journal or Diary Study in Market Research

LAIBA CHAUHDRY — Wed, 04 Nov 2026 07:43:51 +0000

Key takeaways
Choose an open journal when you are exploring and don’t yet know what matters; it gives rich stories that are harder to compare.
Choose a guided journal when your questions are defined and you need comparable answers across participants, segments or time periods.
Choose a flexible journal when you need both: scheduled prompts for consistency plus room for unexpected insights.
Five questions decide the method: what your team already knows, how much you need to compare, how well-defined your questions are, how often participants should record, and how much guidance they need.
Setting up a journal study on Terapage takes nine steps, from defining objectives to sharing AI-powered findings with stakeholders.
Your research team has set up a journal or diary study. Participants are recruited, the schedule is ready, and then they hit the first big question.

Should the journal or diary study be open, guided, or flexible?

If they pick the wrong one, the problems show up fast. An open journal or diary study gives them rich stories, but they are hard to compare across participants. A guided journal gives neat, comparable answers, but may miss the unexpected moments that matter most. A flexible journal can do both, but it isn’t always the simplest fit for their study.

The right method is not the one with the most features. It is the one that fits the research question, the stage of research, and the analysis the team needs to deliver. So, before making the final decision, research teams should take a deeper look at how open, guided, and flexible journal or diary studies work, along with their use cases and benefits, in our earlier article on journal or diary studies in market research.

Open journal: participants decide what to record and when, in their own words. Guided journal: researchers set scheduled tasks and prompts that every participant answers. Flexible journal: scheduled, guided tasks combined with open entries in one continuous diary.

Once that’s clear, research teams can work through the following steps to select the right journal-writing method for their study.

How to Choose Between Open, Guided and Flexible Journal Studies: 5 Questions
Step 1: How Much Does Your Research Team Already Know?
Open Journal: If they are exploring an experience and do not yet know what matters, an open journal is a good starting point, as it allows research teams to gain detailed, rich insights. Participants express their experiences, choices and reactions openly without any guidance or restrictions.

Figure 1: Terapage’s Open Journal diary study gives participants the freedom to record their experiences, thoughts, and observations in their own words.

Guided Journal: If they have defined questions or hypotheses and need to measure the same things across everyone, they can choose a guided journal. It helps them get rich insights in a controlled environment defined by their prompts.

Figure 2: Terapage’s Guided Journal lets researchers schedule daily entries with predefined prompts, helping participants provide structured, focused feedback.

Flexible Journal: If they have some defined questions but also expect surprises, they can choose a flexible journal. It is a mixed-method approach, allowing them to gain the richest insights.

Modern research platforms like Terapage bring all three journal or diary study formats (open, guided, and flexible) together, allowing research teams to choose the approach that best aligns with their study objectives and requirements.

Figure 3: Terapage’s Flexible Journal combines guided prompts with open-ended entries, allowing participants to respond to scheduled questions while adding their own thoughts and experiences.

Figure 4: The researcher explains the journal study requirements in detail before creating the activity, ensuring participants have clear instructions and an easy start.

Step 2: How Important Is Comparing Participants?

Open Journal: If your research team’s goal is rich description rather than direct comparison, an open journal gives participants the freedom to show you what matters to them.

Figure 5: Open journal entries by participants in the Terapage workspace.

Guided Journal: If they plan to compare two audience segments on the same measure, or report differences between two time intervals, they can choose a guided journal where they can run a controlled study. This helps them conduct a comparative analysis of groups based on demographics such as age, gender, geography and income.

Figure 6: Guided journal studies help researchers compare experiences and preferences across different demographic groups using structured tasks and prompts.

Flexible Journal: If your team needs both consistency and freedom to explore unexpected insights, a flexible journal offers a balanced approach. Researchers can provide common prompts or activities for all participants while allowing them to add their own observations, experiences and multimedia entries. This makes it possible to compare responses across audience segments or time intervals without missing individual experiences that may reveal new research opportunities.

Figure 7: Participants upload photos or videos to document changes over time in a Flexible Journal, helping researchers track evolving experiences and observations throughout the study.

Question 3: How Much Does Your Team Trust Its Research Questions?
Open Journal: If your research questions and objectives are broad or exploratory, your team can choose an open journal. For example, “Do language-learning apps help children learn foreign languages?” is a broad question, because there are many language-learning apps, and learning itself can mean different things depending on children’s ages, backgrounds and nationalities. An open journal can help researchers discover what children experience while using these apps and what aspects of learning matter most to them, a common need in education research.

Figure 8: Participants can upload supporting documents in open journal entries to provide additional context and evidence for their responses.
Guided Journal: If your research questions are clearly defined and your team knows what it wants to investigate, a guided journal may be a better choice. Researchers can give participants specific questions or tasks to complete, making it easier to focus on particular aspects of the research.

Figure 9: A prompt-based activity for a guided journal in Terapage.
Flexible Journal: If your team has specific research questions but also wants to discover unexpected insights, a flexible journal offers both structure and freedom. Researchers can schedule entries at daily, weekly or activity-based intervals, provide specific prompts, and allow participants to share other experiences or challenges they encounter.

Figure 10: Terapage’s Flexible Journal combines open-ended entries and polls, allowing participants to log their responses through different activity formats within a single study.

Question 4: How Often Should Participants Record Their Experiences?
Open Journal: If your team wants participants to share experiences whenever something meaningful happens, an open journal lets them record observations in their own time without following a fixed schedule. For example, users testing a new shopping app can write about any problems they encounter while shopping.

Figure 11: Participants making multiple entries in a single day using different formats, such as text and voice recordings, in an Open Journal study in the Terapage workspace.
Guided Journal: If your team needs regular feedback or wants to compare experiences over a defined period of time, a guided journal allows researchers to schedule entries daily, weekly or after specific activities, using the same questions or prompts. For example, modern platforms like Terapage allow research teams to schedule their tasks in two ways:

Custom and manual dates, which involve setting start and end dates individually for each task.
Sequential, where tasks are released one after another from the start date, for example every day or every week.

Figure 12: In Terapage’s Guided Journal, researchers can schedule each task individually or choose a sequential release, making tasks available to participants daily or weekly.

Figure 13: Participants are clearly informed when a guided journal task is not yet available and are shown the exact date and time it will be released.

Flexible Journal: If your team needs both scheduled feedback and spontaneous observations, a flexible journal offers both options. Researchers can schedule regular entries while allowing participants to record additional experiences whenever something important happens or they miss a scheduled task. For example, participants can complete a missed task alongside their scheduled entry for the day, ensuring that no important feedback is lost.

Figure 14: Participants can complete entries for missed tasks alongside their current activities in a Flexible Journal, ensuring their feedback is not lost.
Question 5: How Much Guidance Do Participants Need?
Open Journal: If participants are familiar with the topic and can describe their experiences independently, an open journal lets them record their thoughts without specific prompts or instructions for each entry.

Guided Journal: If participants need clear instructions on what to observe, evaluate or record, a guided journal provides specific tasks and interactive activities to guide their responses. For example, researchers studying a baby swing can ask participants to sort product features into categories such as safety and comfort or convenience and functionality. Participants can also use image review activities with tags to highlight specific product features, describe what they notice, and rate their experience. These activities help researchers understand what participants value most and why.

Figure 15: Participants receive detailed, task-specific instructions in Guided Journal activities, helping them understand what to do, what to observe, and how to submit their responses.

Figure 16: Terapage’s Guided Journal combines card-sorting and image-tagging activities, allowing participants to categorise product features, highlight specific details, and share their feedback through ratings and written responses.
Flexible Journal: If participants need some guidance while still having the freedom to share their own experiences, a flexible journal combines scheduled tasks with open-ended activities. For example, researchers studying a baby swing can ask participants to complete specific activities, such as reviewing product features or sharing feedback, while also allowing them to add spontaneous observations about their baby’s experience or any features they find particularly useful.

Figure 17: The researcher combines scheduled, prompt-based tasks with open reflection activities in a Flexible Journal, giving participants both structured guidance and the freedom to share additional observations in their own words.

Figure 18: Participants can add open reflections alongside their scheduled tasks in a Flexible Journal, sharing additional thoughts and experiences in their own words.

Steps to Set Up Your First Journal Study
Terapage is an AI-powered digital ethnographic research platform that enables research teams to conduct journal studies in three formats (open, guided and flexible), making it a versatile, centralised solution for capturing, managing and analysing participant experiences.

Step 1: Define Your Research Objectives
Start by identifying what you want to learn from participants. Clear objectives will help you choose the right journaling method, whether open, guided or flexible, and keep the study focused on your research goals. See our best practices for designing research that works.

Figure 19: Journal or diary study activities in Terapage workspaces.

Figure 20: The researcher adds study-specific instructions when creating a journal diary study in Terapage, ensuring participants understand the study objectives and what is expected of them.
Step 2: Choose Your Journal Type
Select the journal format that best fits your research questions. Use open journaling for exploratory studies, guided journaling for focused questions and comparisons, or flexible journaling when you need both structure and room for unexpected insights.

Figure 21: The researcher selects the preferred journal format from the three available options in Terapage: Open, Guided, or Flexible Journal.
Step 3: Design Your Journal Activities
Decide what participants should record during the study. You can use open-ended prompts, specific questions or guided tasks, depending on your chosen journal type. Keep instructions clear so participants understand what to do and what information to share.

Figure 22: The researcher adds activities to the journal or diary study within Terapage workspaces.
Step 4: Set the Study Schedule
Determine when and how often participants should submit entries. Depending on your objectives, you might schedule daily or weekly entries, request responses after specific activities, or allow participants to record experiences whenever they occur.

Figure 23: The researcher sets the start and end dates for each activity to define when it becomes available and when participants can complete it.
Step 5: Decide How Participants Will Share Their Experiences
Choose the response formats that suit your study, such as written entries, photographs, audio recordings or videos, where supported by your research platform. Different formats can help participants explain experiences that may be difficult to describe in words alone, as in mobile ethnography.

Figure 24: The researcher adds multimedia-supported journal entry activities in Terapage workspaces, allowing participants to share their experiences through text, images, audio and video.
Step 6: Launch and Monitor Your Study
Before launching, review your instructions, activities, schedule and participant requirements. Once the study begins, monitor incoming entries and completion progress so you can identify unclear instructions or participation issues early.

Figure 25: Researcher reviewing the Guided Journal activity in the Terapage workspace before launching the study.
Step 7: Collect Journal Entries
Once the journal or diary study is launched, researchers can start collecting participant entries in real time through the Terapage workspace. They can review individual submissions, track participant progress and monitor responses as the study unfolds.

Figure 26: Terapage enables researchers to collect journal entries in real time, allowing participants to document their thoughts, feelings, behaviours and experiences through written responses, photos, audio and video.
Terapage also makes journal activities more interactive by allowing participants to engage with entries shared by their fellow participants. They can like, dislike and comment on these entries, creating opportunities for discussion and encouraging participants to share different perspectives and experiences.

Figure 27: In Terapage journal or diary studies, participants can engage with one another’s daily entries by liking, disliking and commenting on their fellow participants’ posts.
Step 8: Review and Analyse the Findings
After collecting entries, use AI-powered real-time analysis to identify recurring patterns, sentiments, themes and categories as responses come in. Combine these insights with individual participant examples to understand not only what people experienced but also why those experiences matter to your research objectives.

Figure 28: Real-time sentiment analysis of a journal activity in Terapage.

Figure 29: Detailed theme categories generated by AI-powered tools in real time in Terapage.

Figure 30: Terapage’s AI-powered analysis tools generate relevant codes alongside supporting response excerpts, helping researchers identify key themes and patterns in participant feedback.

Figure 31: AI-generated taxonomies organise journal study themes into categories and subcategories, with verbatim sources behind each one.

Figure 32: Terapage’s AI-powered Speech Map analysis converts recorded voice notes from journal entries into visual insights, helping researchers explore participants’ spoken feedback and identify key themes.

Step 9: Share Findings with Stakeholders
Present the key findings to stakeholders in a clear and actionable format. Highlight recurring themes, important participant experiences and insights that relate to your research objectives. Use relevant quotes, photos or other supporting evidence to help stakeholders understand the findings and make informed decisions about product improvements, customer experiences or future research, or publish them as branded insight reports.

Figure 33: Terapage generates share-ready reports with basic taxonomies from journal or diary studies, helping researchers present and share organised findings with stakeholders.

Figure 34: Terapage provides AI-powered summaries and exportable PDF reports, helping researchers review key findings and easily share their analysis with stakeholders.

Figure 35: PDF export of Terapage’s AI-generated journal summary, providing a concise overview of participant entries and key insights for easy sharing with stakeholders.

Figure 36: Nine steps to create a journal or diary study, from your first objective to insights you can share.

From Logging Entries to Understanding Choices: The Future of Journal Studies
The future of journal and diary studies is about much more than logging entries. A journal is no longer just a place where people write down what happened in their day. It is a living record of real moments, shared in the way that feels natural to each person, whether that is a few words, a photo, a voice note or a short video.

That is why the choice you make at the start matters. If you are still exploring, an open journal lets people tell you what matters to them. If you have clear questions and want to compare answers, a guided journal keeps things consistent. If you want both, a flexible journal gives you structure with room for surprises. The best method is the one that fits your question, your participants and the answers your team needs.

If you want to run a journal study that goes beyond collecting entries, Terapage can help. You can run open, guided and flexible journals in one place, gather text, photos, audio and video, and use AI-powered analysis to uncover themes and sentiment as responses arrive. Book a demo and see how everyday moments can become insights your team can use.

Figure 37: Terapage is an AI-powered, all-in-one platform for conducting journal and diary studies in modern market research.
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What Are Journal or Diary Studies in Market Research? Types, Use Cases, and Benefits

LAIBA CHAUHDRY — Wed, 28 Oct 2026 08:09:15 +0000

Key takeaways
A journal or diary study is a longitudinal qualitative research method in which participants record their experiences in real time over days, weeks or months.
Because entries are made as things happen, diary studies avoid recall bias and show how behaviour, satisfaction and emotion change over time.
There are three journal modes on Terapage: open journals for exploration, guided journals for structured tasks, and flexible journals that combine both.
Entries can include text, photos, videos and voice notes, giving researchers real context about where, when and how products are used.
AI-powered analysis on Terapage surfaces emerging themes, codes and sentiment across all journal entries.
Your research team conducted the study. The results came out clean. But when stakeholders and decision-makers asked one question, the team went blank.

But why did people stop using it by week three? What was actually going on that stopped them from using your serum?

To know the actual story, research teams prefer a daily journal activity instead of a one-off survey that only captures a single moment filtered through memory. Comparatively, a daily journal captures real-time emotions, feelings, experiences, frustrations, choices and preferences.

Modern market research platforms like Terapage allow research participants to record their experiences as they happen, in real time, over days or weeks. This enables research teams to unravel how a choice or behaviour has evolved over time. Modern markets are not static, so to study consumer behaviour, teams need journal studies to read between the lines.

What Are Journal or Diary Studies in Market Research?
In qualitative research, journal or diary studies are a longitudinal research method that allows participants to record their emotions, behaviours, choices, thoughts, experiences and reactions in real time over a set period, such as days, weeks or months.

It doesn’t depend on recall memory, making it the most authentic method to study human behaviour. For instance, instead of asking participants,

“How do you feel about your baby swing?”

journal or diary studies allow them to log their daily use experience, like what their child likes and dislikes, how the product fits into their daily routine and what challenges come up, as those things happen.

Moreover, journal entries are not limited to written reflections. Participants can also contribute photographs, videos and audio recordings to show what they encounter in their everyday environments.

Terapage supports this approach through its Journal Activity feature, where researchers can configure structured tasks or open-ended entries, set submission intervals, and collect multimedia feedback throughout a study.

The method is especially valuable for:

Habit and routine tracking: seeing how behaviours form, stick or fade.
Product and experience research: observing real usage in real environments, such as how people use and feel about a skincare serum, a baby product or a wearable device.
Behavioural studies: capturing the context, timing and triggers around decisions.
Learning and progress studies: tracking how skills, confidence or attitudes change over time, for example in education research.
Change over time: spotting shifts in satisfaction, emotion or opinion that a snapshot would miss.

Figure 1: Journal or diary studies in Terapage workspaces for market research exploring vocabulary app usage.
What Are the Types of Journal or Diary Studies?
Journal or diary studies are the most reliable method to study human behaviour, but the real challenge is design. How you structure the diary shapes everything you get back, and that is where the three journal modes come in.

Open Journal Open journal or diary studies give participants considerable freedom to decide what they record and how they describe their experiences. Researchers establish the study objectives and timeframe but avoid prescribing detailed questions for every entry. Participants can focus on the moments, observations and experiences they consider important.

Open journal or diary studies are particularly suitable for:

Exploratory market research: discovering unmet needs, emerging behaviours and unexpected customer experiences.

Consumer behaviour studies: understanding how people make everyday decisions without restricting them to predefined categories.
Early-stage product research: exploring how customers naturally interact with a new product or service, and building products people will buy.

Customer experience research: identifying frustrations and opportunities that researchers may not have anticipated.
Lifestyle and habit research: exploring routines, motivations and contextual influences on behaviour.

Trade-off: The cost is variability, because entries differ in depth, length, topic and format, which makes comparison harder. Therefore, research teams should communicate expectations clearly to encourage meaningful reflection without restricting participants’ choices.

Figure 2: A researcher selecting the Open Journal activity in the Terapage workspace.

Figure 3: Open Journal dashboard in the Terapage workspace displaying real-time participant counts and individual responses.

Figure 4: Participant submitting an open journal entry for the day in the Terapage workspace.

Guided Journal Guided or structured journal or diary studies use predefined questions, prompts or activities to direct participants towards specific aspects of their experiences. Researchers decide what information they need and design journal tasks accordingly. They also set schedules for when to complete a certain task and how many responses should be logged for that entry. For example, a company testing a mobile banking app might ask participants to record their experience after completing a transaction. Each entry could explore what they were trying to accomplish, how easy the process felt, whether they encountered difficulties, and whether they achieved their goal.

Guided journal or diary studies are suitable for:

Usability testing: identifying difficulties while completing specific tasks in an app, website or digital product.
Product testing: tracking product usage, perceived performance and satisfaction over repeated interactions, as in in-home usage testing.
Customer journey research: investigating defined stages such as product discovery, purchase, onboarding and post-purchase support.
Advertising and concept testing: recording participants’ reactions to campaign messages, creative concepts or brand communications at specified intervals.
Service evaluation: understanding particular interactions with customer support, delivery services or subscription platforms.
Behaviour-change studies: tracking progress towards a goal, such as adopting a new routine or changing consumption habits.
Trade-off: Too many questions can make journal or diary studies feel like a repetitive survey. Leading prompts can also influence what participants report. Researchers should keep tasks manageable, use neutral wording, and leave room for participants to mention experiences beyond the questions.

Figure 5: A researcher selecting the Guided Journal activity in the Terapage workspace.

Figure 6: A guided journal dashboard on Terapage displaying the number of participant responses, activity description and study duration.

Figure 7: A researcher adds scheduled daily tasks to a guided journal activity on Terapage to track participants’ experiences using a vitamin C serum.

Figure 8: A participant submits daily poll responses for scheduled tasks in a guided journal activity on Terapage.
In a guided journal, Terapage lets research teams decide whether participants can complete tasks they have missed. If late submissions are switched off, a participant cannot submit a task once its window has closed. This keeps responses within the defined period, so the feedback reflects what participants experienced at that moment and not what they remember later.

Figure 9: In Terapage, researchers set when each guided journal task opens and closes, then decide if participants can still submit a task they missed.

Figure 10: Terapage shows participants when a task has been missed. The response window is closed, so no answer can be added, while later tasks stay open.

Flexible Journal Flexible journal or diary studies combine guided and open journal or diary studies. Researchers define the main topics, tasks or reporting intervals but allow participants to contribute additional observations in their own way. In flexible journal or diary studies, researchers can control:

Task types: build the journal from forms, polls, ranking and sorting, media uploads, and image, video or audio reviews.
Scheduling: researchers can give each task its own start date and time, end date and time, and archive date and time, or leave the schedule blank so the task inherits the overall activity dates.
Required tasks: they can mark tasks as required so participants complete them before moving on.
Supporting evidence: they can ask participants to explain their answers and add evidence alongside ratings and polls.
Flexible journal or diary studies are particularly suitable for:

Longitudinal customer research: understanding how opinions, expectations and behaviours change over time, for example within insight communities.
Customer experience studies: combining feedback about defined interactions with unexpected observations.
Product adoption research: investigating how people learn to use a product and incorporate it into their routines.
Mobile ethnography: capturing experiences in participants’ natural environments through entries and multimedia.
Brand relationship studies: exploring how perceptions and preferences develop through repeated interactions.
Complex customer journeys: investigating experiences that vary considerably between individuals.
Trade-off: Flexible journal or diary studies require a thoughtful balance. If instructions are too broad, entries may be inconsistent; if the framework is too restrictive, participants may have little opportunity to introduce new themes.

Figure 11: A researcher selecting the Flexible Journal activity in the Terapage workspace.

Figure 12: Flexible Journal dashboard in the Terapage workspace displaying real-time participant counts and individual responses.

Figure 13: A participant submits responses to a step-up scale question in a flexible journal activity on Terapage.

Figure 14: A participant submits an open-ended reflection in a flexible journal activity on Terapage, combining structured questions with the freedom to share personal experiences in their own words.

Figure 15: In a flexible journal activity on Terapage, participants complete certain tasks according to a researcher-defined daily schedule, rather than submitting entries whenever they choose.

What Are the Benefits of Journal or Diary Studies in Market Research?

Captures In-the-Moment Behaviour Memory is selective. Journals record the moment itself, so research teams get the frustration at 9 pm on a Tuesday instead of a tidy summary a month later based on recalled memory.

Figure 16: A participant records a Day 1 journal entry on Terapage immediately after setting up the baby swing, capturing their experience in the moment rather than relying on later recall.

Captures Real-Time Patterns A survey gives you one data point. A journal shows how habits form, how satisfaction rises or fades and when enthusiasm drops. That is how you answer “why did people stop using it?”

Figure 17: AI-powered individual analysis on Terapage highlighting the reasons participants feel annoyed when using a product.

Reveals Real Context Written experiences do not provide the whole picture and context. Multimedia journal entries, such as photos, screenshots, videos and voice notes, show where, when and how people actually use a product. For instance, a parent can show you the swing in their living room, and a student can attach the feedback email that changed how they write.

Figure 18: A participant uploads a multimedia response to a journal activity on Terapage, documenting their experience using a baby swing.

Figure 19: Participants can record voice entries in open journal or diary study activities on Terapage, sharing their experiences and observations in their own words.

Unexpected Insights When participants share their everyday experiences in their own words, researchers can uncover unmet needs, workarounds and unexpected ways people use a product that they may not have thought to ask about in a questionnaire.

Figure 20: A researcher explores newly emerging themes from participants’ open-ended journal submissions in Terapage.

Collecting Emotions Along with Opinions Since journal or diary study entries are written close to the experience, they carry real feelings, frustrations and preferences. AI-powered sentiment analysis in Terapage helps you spot those emotional trends across all entries, so you can see where feelings shift and read the entries behind them.

Figure 21: AI-powered sentiment analysis of product use experiences in a Terapage Journal Activity.

Multi-Purpose Research Needs Journals suit habit and routine tracking, product and experience research, behavioural studies, learning and progress studies, and any question about change over time.

Journal or Diary Studies in Market Research Are More Than Submitting Entries
In market research, journal or diary studies are about turning everyday participant experiences into meaningful research insights. They explore how people think, feel, behave and interact with products in their everyday lives. From the small challenges they encounter to the workarounds they develop and the unexpected ways they use a product, journal studies help researchers discover insights that may never emerge through traditional questionnaires alone.

With Terapage, research teams can choose between open, guided and flexible journal or diary studies, capture experiences through multiple formats, and use AI-powered analysis to identify emerging themes, sentiments and patterns in real time. This integrated approach helps researchers uncover unmet needs, understand behaviours in context, and turn authentic participant experiences into actionable findings that inform better decisions.

Figure 22: Terapage, an all-in-one AI-powered journal or diary studies platform.

AI Study Assistants: How to Support Research Participants Beyond FAQs

LAIBA CHAUHDRY — Wed, 28 Oct 2026 07:54:26 +0000

Key takeaways
An AI study assistant is a participant-facing AI chatbot that answers questions about a research study using the study’s own materials.
FAQs only cover the questions researchers expect; an AI study assistant answers the ones participants actually ask, at any hour, with cited sources.
Setting one up on Terapage takes six steps, from choosing the AI Chat Assistant activity to uploading and prioritising study resources.
It supports participants in seven ways beyond FAQs: secure onboarding, grounded answers, verifiable citations, voice and image input, accessibility, human hand-over and transcripts.
Assistant analytics show what participants ask, how they feel, which resources are missing and whether answers are reliable.
Research has moved onto participants’ phones. According to the Pew Research Center, 91% of U.S. adults now own a smartphone, and many take part in diary studies, surveys and interviews from wherever they are, at any hour. Research teams, however, can’t be online around the clock. When a participant gets stuck on a task late at night, the questions go unanswered, responses come in incomplete, and some participants quietly drop out.

An FAQ page only answers the questions researchers expected. An AI study assistant answers the ones participants actually ask, in seconds, using your own study materials. It cites its sources, supports participants on any device and hands over to a moderator when a person is needed.

This guide explains what an AI study assistant is, how to set one up on Terapage, seven ways it supports research participants beyond FAQs, and how its analytics help research teams improve every study.

What Is an AI Study Assistant?
An AI study assistant is a participant-facing AI chatbot that answers questions about a research study using the study’s own materials. IBM describes a chatbot as “a software application that communicates with people through text or voice.” An AI study assistant applies this to research: it guides participants, explains tasks and answers questions at any time, within limits the researcher sets.

On Terapage, it is the AI Chat Assistant research activity. It works alongside every other activity, so participants can get help whether they are in a diary study, a multi-task activity, a focus group or a live interview. Read more about how AI research chatbots create more engaging participant experiences.

Why Can’t FAQs Alone Support Research Participants?
FAQs are a good start, but research participants need more than a static list of answers:

FAQs only cover expected questions. Participants ask in their own words, about their own situation.
Participants take part at any hour. Self-paced studies run across time zones, often on a phone, when no researcher is online.
Some questions need accurate, consistent answers. Questions about privacy, consent and rewards cannot be left to guesswork.
Unanswered questions lead to drop-out. Every participant who leaves weakens the quality of the results.
Support is moving the same way in other fields. Gartner expects self-service and live chat to overtake phone and email as the most valuable customer service channels by 2027.

How to Set Up an AI Study Assistant to Support Research Participants
Setting up an AI study assistant takes a few minutes. Here is a quick overview. For a detailed walkthrough, see our 6-step guide to building an AI study assistant on Terapage.

Choose the AI Chat Assistant Activity Create a new research activity and select AI Chat Assistant. Participants can then start an interactive chat, ask questions and upload files, while the AI uses semantic search to find answers in your uploaded resources.

Figure 1: AI Chat Assistant selected as the research activity type when creating a new research activity on Terapage.

Name Your Assistant and Choose an Avatar Give the assistant a name and pick an avatar, or upload your own, such as a study logo. A friendly name and face make participants comfortable asking for help.

Figure 2: Choosing an avatar for an AI study assistant from the default library or uploading a custom image.

Set the Personality, Tone and Response Length Next, shape how the assistant speaks:

Personality: neutral, professional, friendly, empathetic, clinical or educational.
Tone: conversational, formal, supportive, technical or simplified language.
Response length: short, medium or detailed.
An empathetic, supportive assistant suits healthcare and pharmaceutical research, while an educational tone works well for student studies in educational institutions. You can also add suggested prompts, such as “How long will this take?”, and set a limit on questions or chat duration.

Figure 3: Assistant personality options for an AI study assistant: neutral, professional, friendly, empathetic, clinical and educational.

Figure 4: Assistant tone options for an AI study assistant: conversational, formal, supportive, technical and simplified language.

Figure 5: Response length settings for an AI study assistant: short, medium or detailed answers.

Decide How Answers Cite Sources Choose whether the assistant cites sources when available, always cites them, or never shows citations. Always citing sources builds trust, especially when participants need to rely on what the assistant says.

Figure 6: Citation behaviour settings for an AI study assistant: cite when available, always cite sources or never display citations.

Control Where Answers Come From Choose whether answers come from your uploaded resources, the internet, or both. Using only uploaded resources keeps answers accurate and on-topic.

Figure 7: External knowledge controls for an AI study assistant: uploaded resources only, uploaded resources plus internet search, or internet only.

Upload and Prioritise Your Study Resources Upload PDFs, slides, spreadsheets or media (image, audio, video), or import files from the cloud. Sort them into categories such as Onboarding and FAQs, then set each file’s priority so the assistant always uses the right material.

Figure 8: Uploading knowledge resources and organising them by category and priority for an AI study assistant.

Figure 9: Organising study files in the knowledge resource library by category, priority and inclusion.

7 Ways AI Study Assistants Support Research Participants Beyond FAQs
Once it is live, the assistant does far more than repeat FAQs. Here are seven ways it supports research participants from the first message to the last.

Privacy-Driven, Secure Onboarding Chats Participants are welcomed with a task onboarding screen that explains the study, what they can ask and how the chat works. It also states clearly that every conversation is encrypted and private to their account, which matters when people share personal experiences. Together with Terapage’s streamlined onboarding and secure, GDPR-compliant platform, this gives participants confidence from the start.

Figure 10: Task onboarding screen introducing the AI study assistant to research participants.

Instant Answers Grounded in Study Resources Participants ask questions in their own words and receive structured, real-time answers grounded in the study’s resources. This is especially useful in self-paced studies, such as do-it-at-home research or product trials for consumer goods brands, where questions often come up outside office hours.

Figure 11: A research participant asking an AI study assistant a question on mobile and receiving a structured answer.

Cited Sources Participants Can Verify Answers include numbered citations. Tapping a citation opens the source with the exact quote highlighted, so participants can check it themselves. Participants can also rate or flag each answer.

Figure 12: An AI study assistant answer with numbered source citations and a participant follow-up question.

Figure 13: An AI study assistant giving a short answer with a citation to the study resource.

Figure 14: A source citation opened in the AI study assistant, showing the highlighted quote from the study document.

Ask by Voice or Share an Image Participants don’t have to type. They can dictate questions by voice, or attach images and files, such as a screenshot of an error or a photo of a product. This makes support easier on the go and suits digital ethnography and mobile ethnography studies, where participants are often away from a computer.

Figure 15: A participant using voice dictation to ask the AI study assistant a question on mobile.

Figure 16: A participant attaching an image to the AI study assistant chat on mobile.

Accessible Support for Every Participant From the chat menu, participants can enlarge the text, switch to high contrast mode and translate messages into their own language. Inclusive support like this helps ensure every participant’s voice is heard, on any device.

Figure 17: AI study assistant menu with options to download transcript, accessibility settings or request human support.

Figure 18: Accessibility options in the AI study assistant: larger text sizes and high contrast mode.

A Human Moderator When It Matters Participants can ask for a human moderator at any time. This matters in sensitive studies, such as employee engagement research for HR teams or case reviews for law firms.

Figure 19: A participant requesting human support from a study moderator inside the AI study assistant chat.

Transcripts and Chat History Participants Control Participants can download their chat transcript or start a new chat, and earlier chats stay saved in history. This keeps long studies, such as insight communities, easy to follow.

Figure 20: Downloading the AI study assistant chat transcript as a text file on mobile.

Figure 21: Starting a new chat with the AI study assistant while the previous conversation stays saved in history.
How Do AI Study Assistant Analytics Help Research Teams Support Participants Better?
Every conversation also tells research teams something useful. Terapage’s AI-powered insights turn assistant chats into analytics across question analysis, resource gaps, resource utilisation, and quality and safety.

What Participants Ask Most and How They Feel
The most common questions are ranked by frequency, alongside the sentiment behind them, such as concern, curiosity or scepticism. Questions that keep coming up show where study instructions need to be clearer.

Figure 22: Most common participant questions and question sentiment in AI study assistant analytics.

Emerging Questions and Trending Topics
Emerging questions highlight topics participants have only just started asking about, while trending topics show which subjects are growing. Each one links back to its source, so researchers can see the full context.

Figure 23: Emerging questions and trending topics from participant conversations with the AI study assistant.

Resource Gaps: What Your Study Materials Are Missing
Resource gap analysis shows which questions your files answered and which they missed. It then suggests documents to add, so future participants get better answers.

Figure 24: Resource gap analysis showing coverage, out-of-scope queries and recommendations for study resources.

Resource Utilisation: Which Documents Participants Rely On
A ranking of the most cited documents shows which resources participants rely on most, helping teams keep those files accurate and up to date.

Figure 25: Resource utilisation analysis showing which study documents the AI study assistant cited most often.

Quality and Safety: Ratings, Accuracy and Escalations
Research teams can track helpful and unhelpful ratings, hallucination risk, support escalations and AI confidence levels. These metrics show whether answers are reliable and when the assistant needs better resources or human review.

Figure 26: Quality and safety metrics for an AI study assistant: helpful ratings, hallucination risk, support escalations and AI confidence.

Sentiment Analysis of Participant Conversations
AI sentiment analysis groups participant messages into moods, showing each mood’s share, weight and strength alongside the key statement behind it.

Figure 27: Sentiment analysis of participant conversations with the AI study assistant, grouped into mood categories.

Figure 28: A sentiment table linking each emotion in participant conversations to key statements, share and strength.

Quotes, AI Excerpts and Taxonomies
Quotes analysis ranks the top themes, AI excerpts link each one to its sources, and taxonomies sort them into categories. Findings are then ready for reports and branded insight reports.

Figure 29: Quotes analysis ranking the themes participants mentioned most in AI study assistant conversations.

Figure 30: AI excerpts showing key topics from participant conversations, with the verbatim sources behind each one.

Figure 31: Taxonomies organising AI study assistant conversation themes into categories and subcategories.
Best Practices for a Trustworthy AI Study Assistant
An AI study assistant should earn participants’ trust. Follow these practices:

Be open about AI. Under the EU AI Act, people using chatbots “should be made aware that they are interacting with a machine.”
Keep answers grounded. Use uploaded resources and always cite sources in sensitive studies.
Keep a human in the loop. Make sure moderators respond quickly to human support requests.
Review analytics regularly. Fill resource gaps and check quality and safety metrics as the study runs.
Test before launch. Ask the assistant your participants’ likely questions first, in line with Terapage’s AI transparency principles.
If you need help planning or setting up your assistant, Terapage’s Premium Support team can guide you.

AI Study Assistants on One Unified Research Platform
The AI study assistant is part of Terapage Asynchronous, where it runs as the Chatbot Activity. Terapage Asynchronous is one of five products on one platform, alongside Terapage Live, the Long-Term Community, Synthetic Users and Data, and Terapage Pulse. Every product shares the same platform features, such as AI-powered insights, e-consent, notifications and native mobile apps. That means participants get the same secure support in every study, in more than 30 languages.

Figure 32: Terapage’s five research products and shared platform features, including the Chatbot Activity, on one unified platform.

What Is Pulse and How Does It Keep Research Connected to Market News and Trends?

LAIBA CHAUHDRY — Wed, 21 Oct 2026 13:11:15 +0000

Key takeaways
Terapage Pulse is an always-on market intelligence tool that checks what your participants say against what the market is saying.
Each Pulse run collects your research data, extracts topics, gathers external market and competitor signals, generates insights and forecasts, and sends an alert.
Setting up a Pulse takes five steps: details, research sources and weighting, markets and competitors, refresh frequency and tone, and alerts and recipients.
Pulse helps teams decide what to research next, reveal gaps in existing research, test insights and gut feelings, spot trends early and keep stakeholders informed.
Every finding separates internal mentions from your participants and external mentions from the market, so it can be traced back to its evidence.
Your research ends, but the market doesn’t stop. News breaks, competitors launch and opinions shift, and your findings start to age the day the report is delivered. Teams then fall back on gut feeling, even though a PwC-sponsored survey found that highly data-driven companies are three times more likely to see significant improvement in their decisions.

Terapage Pulse keeps your research connected to market news and trends. It checks what your participants say against what the market is saying, then tells you what to research next, where the gaps are, and whether your insights hold up.

What Is Terapage Pulse?
Terapage Pulse is an always-on market intelligence tool that keeps your research connected to market news and trends. Marketing intelligence is “the everyday information relevant to a company’s markets, gathered and analyzed” to support confident decisions about growth and new markets. Pulse compares what your participants say with what the market is saying, then turns both into clear, prioritised recommendations.

All Pulses sit in one workspace, where researchers can see which are active, scheduled or saved as drafts, along with each Pulse’s data sources and alert history. For an earlier look at the product, read how Pulse is moving market research from static reports to real-time intelligence.

Figure 1: The Pulse workspace, showing all active, scheduled and draft Pulses, their data sources and alert history in one place.
Behind every Pulse is Terapage’s Strategic Intelligence Engine, which is built on three ideas:

Always-on intelligence: your research stays connected to the market long after fieldwork ends, as Pulse links your research data with real-time news, market trends and industry shifts.
Actionable insights: raw information becomes clear recommendations that help teams refine products, improve services or explore new markets.
Context-aware analysis: every recommendation builds on what you already know and matches your research objectives.

Figure 2: Terapage Pulse, a strategic intelligence engine built on always-on intelligence, actionable insights and context-aware analysis.
How Does Pulse Work?
Each time a Pulse runs, the AI moves through five stages:

It collects data from your selected activities and files.
It prepares the data by extracting topics.
It gathers external market and competitor signals.
It generates insights, forecasts and priorities.
It saves the Pulse and sends an alert.

Figure 3: Pulse moving through data collection, data preparation, market context, AI analysis and finalizing.
Because Pulse builds on AI-powered insights from your own studies, its external findings are always tied to real participant evidence, not general web noise.

How to Set Up a Pulse in Five Steps

Add the Pulse Details Researchers start by giving the Pulse a name, a description and a cover image. The image can come from a device, the cloud or the Terapage library.

Figure 4: Adding a cover image and name when creating a new Pulse.
Next, they set the country, time zone, start and end dates, and tags that describe the topics the Pulse should follow.

Figure 5: Setting the Pulse timeline, time zone and topic tags.

Connect Your Research and Weight Your Sources Pulse works on top of your existing studies. Researchers choose a study and select the activities to include, such as journal and diary studies, focus groups, multi-task activities, document reviews and chatbot research.

Figure 6: Selecting the research activities that a Pulse will analyse.
Researchers can add a supporting file in DOCX, XLSX, TXT, CSV, MP4 or JSON format for earlier research or third-party data. Larger data flows can connect through the Terapage API.

Figure 7: A Pulse connected to multiple research activities and an uploaded reference dataset.
Source weighting then decides how much each signal counts, with a total of 100%. Researchers balance internal research against public opinion, social listening, behavioural data, competitor listening, academic sources and other external data.

Figure 8: Weighting internal research against public opinion, social listening, behavioural data, competitor listening and academic sources.

Choose Markets, Industries and Competitors Researchers set the geographic level (continent, country, state or city) and choose the regions that matter most. They can also add preferred industries and the competitors Pulse should watch.

Figure 9: Choosing the geographic level for a Pulse, from continent to city.
They then pick the regions that matter most and add the industries and competitors Pulse should watch.

Figure 10: Choosing preferred regions, industries and competitors for a Pulse.

Set the Refresh Frequency and Content Tone Pulse can refresh its data daily, weekly, bi-weekly, monthly, quarterly, bi-quarterly or yearly, depending on how fast the market moves.

Figure 11: Setting how often a Pulse refreshes its data.
Researchers also choose a content tone to suit the people who will read the results: academic, professional, industry, hybrid or technical.

Figure 12: Choosing the content tone for Pulse reports.

Choose Alerts and Recipients Finally, researchers choose which events trigger alerts, how often reports are published and who receives them. Recipients can include researchers, collaborators and observers.

Figure 13: Setting Pulse alerts, publication frequency and report recipients.
5 Ways Pulse Keeps Research Connected to Market News and Trends
Pulse is not just a monitoring screen. It changes three of the hardest decisions in research: what to study next, what your current research is missing, and whether your insights and instincts are right. Each capability below comes with examples from the industries and use cases Terapage supports.

Decide What to Research Next Pulse forecasts describe a likely market shift, its drivers, expected impact and opportunity window, and end with a recommended action and a confidence level. Instead of guessing the next study, teams get an evidence-based brief for it.

Figure 14: A Pulse forecast with the current trend, drivers, expected impact, opportunity window and recommended action.
For consumer intelligence teams, a forecast about a rising ingredient or product claim can become the next concept test. Online shopping and in-store shopping studies can then show how the idea performs at the shelf. Our guide to de-risking a launch with online concept testing shows how to run that next step.

In technology and media, a forecast about how audiences are reacting to a new feature can set the brief for the next round of user experience testing.

Reveal Gaps in Your Existing Research Pulse shows each topic’s internal mentions (from your participants), external mentions (from the market) and sentiment, side by side. When a topic has far more external mentions than internal ones, your study has missed something the market is talking about. For example:

Financial services teams may find fees or fraud trending in the news but rarely raised by customers.
Public and government organisations may spot a policy issue missing from citizen feedback.
Gaps also guide your next method. A do-it-at-home study or digital ethnography can explore real-life use, as our guide to mobile ethnography explains. A mixed-method study can add the quantitative numbers.

Figure 15: Topics compared by internal mentions, external mentions and sentiment, highlighting gaps between research and the market.

Back Up or Challenge Your Insights and Gut Feelings Pulse lets you test an insight against two kinds of evidence at once: what your participants said and what the market is saying. Open any topic to see how it holds up. For example, a product effectiveness topic shows:

its internal and external mentions
a mostly positive sentiment split
a market summary noting that consumers are still sceptical of product claims
the participant quotes behind the topic
This check is valuable wherever a wrong assumption is costly. Law firms can see whether a mock jury in an online focus group reflects public opinion. HR teams can test employee engagement findings against wider workplace trends.

Figure 16: A topic view comparing sentiment, external market context and internal participant quotes.
Pulse also checks your gut feeling about who your audience is. It groups the market into segments, such as skincare professionals, health-conscious consumers and tech-savvy shoppers. Each segment comes with:

its share of the conversation
a description and a behavioural insight
the external reports it draws on
A demographic summary and the industries involved sit alongside. Before planning a campaign, teams can confirm who really cares about the topic. Non-profit organisations, for example, can do this for their cause.

Figure 17: Audience segments with behavioural insights and the external sources behind them.

Spot Emerging Trends, Competitor Moves and Early Warnings The Trends tab charts total mentions and positive, neutral and negative sentiment across every Pulse run. Hover over any point to see the breakdown, so a rising topic or a turn in sentiment is easy to spot early. For example:

Healthcare teams can catch rising patient concerns.
Sports and psychology professionals can track fan sentiment around big events alongside their behavioural studies.
Insight communities get a running view of market change.

Figure 18: Mentions and sentiment tracked over time across Pulse runs.
When a change needs attention, Pulse sends an alert. The Alerts tab lists each one with its data source, status and date, ready to view or download. An alert volume chart shows how often changes have been flagged.

Figure 19: Pulse alerts with their status, details and alert volume.

Keep Stakeholders and Clients Informed Every Pulse run produces a report that can be emailed, viewed or downloaded. Stakeholders stay updated without waiting for the next study. Findings can also feed into reports and analysis or branded insight reports.

Figure 20: Sent Pulse alerts ready to view or download for stakeholders.
How to Read Your Pulse Results
The Pulse Overview at a Glance
The overview sums up each Pulse run on one screen:

Alert level: for example, Medium, which means “monitor closely”.
Total mentions: split into internal mentions from your research and external mentions from the market.
Dominant sentiment: with its positive, neutral and negative split.
Pulse timeline: how long the Pulse has left to run, plus the latest alert.

Figure 21: A Pulse overview showing the alert level, internal and external mentions, dominant sentiment and timeline.
Below it, a mention volume chart and an AI-written executive summary explain what changed and where to focus. The most-discussed topics are listed alongside, with their sentiment.

Figure 22: Mention volume over time, an executive summary and the top topics in a Pulse overview.
Internal vs External Mentions: Where the Evidence Comes From
Pulse separates two kinds of evidence:

Internal mentions come from participant responses in your connected activities, including live interviews, AI-moderated interviews and imported external interviews.
External mentions come from the market sources configured in your Pulse settings.

Figure 23: How Pulse counts internal mentions from participant responses and external mentions from market sources.
Researchers can open every source behind the analysis, so each finding can be traced back to its evidence.

Figure 24: The research activities and data sources behind a Pulse analysis.
Key Insights with Clear Next Steps
Each key insight is tagged with its topic and rated High or Medium priority. It follows a simple format:

Found: what participants and external sources showed.
Why: why it matters to your goals.
Implication: what to do next.
Each insight also links to its external sources.

Figure 25: Key insights showing what was found, why it matters and what to do next, each with a priority level.
Topic Breakdown and Audience Demographics
The Topics tab shows how many themes Pulse found and how many internal and external mentions sit behind them. A breakdown chart shows each topic’s share of the total conversation.

Figure 26: A topic breakdown showing total topics, internal and external mentions, and each topic’s share.
The Demographics tab splits the market into audience segments, each with its share. A geographic focus panel shows the regions you configured next to the ones the AI identified.

Figure 27: Audience segments and geographic focus identified by Pulse.
How Pulse Connects Your Research to Market Trends Across the Terapage Platform
Pulse is one of five products on the Terapage platform. Terapage Live runs real-time interviews and focus groups, and Terapage Asynchronous handles self-paced tasks and diaries. The Long-Term Community supports always-on research, and Synthetic Users and Data is for early testing. Pulse brings the findings from all of them together and checks them against market news and trends.

Shared platform features run across all five products, including AI-powered insights, reporting, e-consent and API integrations. Together, they take research from fieldwork to analysis to market context in one place.

Figure 28: Terapage’s five research products, including Pulse, with shared platform features on one unified platform.
Keep Your Research Connected After Fieldwork Ends
Research no longer has to stop when fieldwork ends. With Pulse, teams know what to research next, see the gaps their studies missed, and back up or challenge their instincts with market evidence. To see Pulse working on your own research, request a demo or start a free trial.

Market Research Templates: What They Are and How to Use Them to Design a Study

LAIBA CHAUHDRY — Wed, 21 Oct 2026 13:01:13 +0000

Key takeaways
A market research template is a pre-built study plan: the activities participants complete, such as interviews, surveys or short tests, with the questions already written.
Templates give teams speed with quality, a questionnaire that misses nothing and a solid starting point, even without a research methods background.
The five main types are interview, survey, user and product, market and customer, and mixed-method templates.
Designing a study with a template takes eight steps, from setting your goal to reviewing AI-powered analysis.
Templates work best when you define the objective first, edit the questions, check study settings and plan how you will use the findings.
Starting from a blank page is the slowest start.

You heard it right.

Research moves fast, and you can’t afford to spend most of your time designing surveys. Every hour spent building a study from scratch is an hour your competitors could spend learning what customers want.

That’s why smart teams now start with ready-made research templates. They pick a proven structure, adjust it and launch, driving rich insights before their competitors do. Modern research platforms like Terapage make this easy with a wide variety of templates, from customer surveys to interviews and usability tests. This guide explains what market research templates are, why they work and how to use them to design a study.

What Is a Market Research Template?
A market research template is a pre-built study plan. It includes the activities participants will complete, such as interviews, surveys or short tests, with the questions already written for each one.

Instead of drafting everything yourself, you pick a template that matches your goal, adjust it, and launch. Just think of it like a recipe. The ingredients and steps are laid out for you, and you can add your own flavour.

Clarification: A research template only provides an initial structure; it does not automatically determine every aspect of the research. Researchers use templates as an aid during research design by defining their objectives, selecting relevant participants, and adapting the activities to their specific context. In other words, market research templates are an aid to faster research and insights.

Figure 1: Terapage website showcasing 40+ research templates with pre-built surveys to help research teams set up and launch studies in seconds.

Figure 2: Research teams exploring individual research template details on the Terapage website before selecting a suitable template for their study.

Note: Do not mistake templates for a survey or questionnaire. A questionnaire focuses on the questions participants answer, while a research template provides a broader structure for organising study activities and related research settings.

Why Does Your Team Need a Research Template?

Speed with Quality
Earlier, research teams used to spend hours designing a research setup, drafting questions, planning tasks, and organising the research process. Research templates offer speed with quality, as they are already built by experts and research teams only need to adjust them according to their study requirements.
A Questionnaire That Misses Nothing
Researchers designing questionnaires often miss certain points for reasons such as time, resources or expertise. Research templates, however, are already approved and tested, so they contain questions covering every aspect of the study. Your team will never miss a question if it uses a research template already built by experts, following the same principles behind effective user research questions.
No Research Design Background Needed
Marketers, product managers and customer success teams can run solid studies without a methods background, because research templates bring the expertise of market experts in survey design.
A Solid Starting Point
Research teams are not bound to use research templates as they are. They can use them as a head start, then edit the questions, reorder the activities, and remove anything they do not find relevant to their research goals.

What Are the Different Types of Market Research Templates?
Templates come in different formats. The right template depends on what your organisation or team wants to learn. Here are the five main types that are crucial to understand before opting for a research template.

Interview Templates Interview templates help you understand experiences, motivations, needs and opinions in depth. Use them when you want to hear the “why” in people’s own words.

Examples include stakeholder interviews, customer discovery interviews and customer exit interviews. They help you uncover business priorities, learn how customers experience your product and understand why people make the choices they do. Focus group and contextual inquiry templates extend the same idea to group discussions and real-life observation.

Figure 3: Researchers reviewing the 48 available research templates in Terapage.

Figure 4: Researchers reviewing interview-based research templates available in Terapage.

Survey Templates Survey templates give you a structured way to collect responses from many people at once. They are ideal when you want comparable answers and clear patterns, on topics such as customer satisfaction, brand perception, loyalty and how you stack up against competitors.

Most include a short intro, screening questions to confirm the right people take part, the core questions, a few demographic questions and a thank-you message.

Closed questions (multiple choice, rating scales) give you numbers you can compare.
Open-ended questions give you the reasons behind those numbers.
Popular examples include:

Net Promoter Score (NPS)
Brand Perception
Customer Onboarding
Feature Request
Product-Market Fit
Employee Engagement

Figure 5: Researchers filtering survey-based research templates in Terapage to find suitable options for customer research.

User and Product Research Templates These templates focus on how people actually use products and services. Examples include usability testing, A/B testing, first-click testing, card sorting, user persona research and diary studies.

They help you spot usability problems, compare design choices, understand real behaviour and see how people experience a product over time.

Figure 6: Researchers shortlisting an A/B testing survey from the user research templates available in Terapage.

Market and Customer Research Templates These templates help you understand what customers need, how they buy and which alternatives they weigh. Examples include competitive evaluation, customer journey research, value proposition testing and pricing page interviews. Use them to see how customers compare their options and where your offer can improve.

Figure 7: Researchers browsing market and customer research templates in Terapage, such as customer satisfaction and validation interview templates.

Mixed-Method Templates Some questions need both stories and numbers. Qualitative research explains experiences and motivations, while quantitative research measures patterns and outcomes.

A mixed-method template lets you do both. Measure a pattern first, then investigate the reasons behind it, or start with interviews and use a survey to check how widely the findings hold.

Figure 8: Researchers exploring mixed-method research templates in Terapage to identify suitable options for their study.

Figure 9: Market research template types at a glance, with what each type is best for and example templates.
How to Use Market Research Templates to Design a Study
Designing a study with a template takes eight steps, from setting a clear goal to reviewing AI-powered analysis.

Step 1: Set Your Goal
Before you browse, write one sentence about what you need to learn. For example: “Why do new customers drop off in the first week?” A clear goal makes every later choice easier, from the method to the questions you keep.

Step 2: Choose Your Method
The second most important step in choosing a research template is the method. If your team is looking for answers, reasons, motivations, choices, behaviours or patterns, it needs to choose qualitative research methods. On the contrary, if it wants numbers, figures, percentages or ratios, it must opt for quantitative methods. If the study requires both, your team can select mixed methods. Sometimes research teams themselves are unsure about the method, so a good rule of thumb is to start with a handful of interviews to learn what matters, then validate it with a survey. See our comparison of qualitative vs. quantitative research for more.

Terapage offers multiple research methods and allows research teams to select more than one method for a study. The available categories include:

Qualitative
Quantitative
Mixed
User & Product
Market & Customer
Academic & Scientific
Secondary & Data
For instance, a customer survey can also incorporate mixed methods and secondary data to provide richer insights and help decision-makers make more informed decisions.

Figure 10: Research teams can filter Terapage’s research templates by multiple categories, including qualitative, quantitative, mixed methods, and market and customer research, to find templates that align with their study objectives.
Step 3: Find and Preview a Template
Once the research method has been decided, research teams can more easily filter templates according to their requirements. However, template titles alone should not determine the selection, as each template may include different activities and tasks. Therefore, research teams should carefully review the details of each template and select the one that best meets their research objectives.

Moreover, research teams are not limited to using a single template. They can combine multiple templates within one study, depending on its nature and objectives. For instance, a survey can be followed by live interviews with a selected group of respondents to explore their answers in greater depth.

Figure 11: Previewing a research template’s activities in Terapage before using it in a study.
Step 4: Customise the Research Template
Research templates are not rigid formats that must be followed exactly. If researchers repeatedly use the same template without adapting it, they undermine the purpose of research, as each study should address its own specific objectives rather than produce the same content repeatedly. Templates are simply starting points that can be edited and customised according to the requirements of each study.

At Terapage, once researchers shortlist one or more templates for a study, they can customise the activities, questions, tasks, and study settings to align with their specific research objectives and requirements.

Figure 12: After selecting a template, researchers can customise its activities, questions, and settings to align with their study objectives.

Figure 13: Researchers customising a Terapage research template by adding the study title, objectives, and other essential study settings.
Modern market research platforms like Terapage allow researchers to edit, reorder, rename, or delete activities before launching the study.

Figure 14: A researcher edits a questionnaire in a Terapage research template to align the questions with the study objectives.
As an advanced, AI-powered market research platform, Terapage also suggests relevant research activities based on the study details provided during customisation. These recommendations help research teams explore additional areas, ask deeper questions, and avoid missing valuable opportunities to gather meaningful insights.

Figure 15: Terapage suggesting a diary study as an additional research activity to help teams capture participants’ experiences, behaviours, and insights over time.
Step 5: Plan Your Audience, Timeline and Privacy
Designing a research study involves more than simply selecting a template and sharing it with participants to collect responses. Research teams must also define their target audience and customise the following details:

Basic Settings
Platform Tasks
Scheduling, including the start date, end date, country and relevant time zone
Research Activity Visibility
Privacy is another important consideration. Research teams need to clearly explain to participants how their responses will be used, how their data will be handled, and whether their participation and responses will remain anonymous. These details help participants understand what to expect before taking part in the study. Read more on protecting participants in online research.

Terapage prioritises data privacy and security, with compliance measures designed to support applicable data protection and privacy requirements, including the GDPR and HIPAA, where applicable. This helps research teams consider data protection as part of their study planning process.

Figure 16: Researchers configuring the study schedule during research template customisation in Terapage.
Step 6: Invite Participants and Collaborators
Once the basic settings and research activities are configured, research teams can move on to inviting participants. In Terapage, researchers can prepare their study for participation by adding the intended audience and ensuring the study details are ready. Depending on the study requirements, they can choose an appropriate participant invitation method and provide participants with access to the research activities.

Figure 17: Researchers adding participants to a template-based study in Terapage workspaces.

Figure 18: Researchers adding team members, collaborators, and observers to their template-based study in Terapage workspaces.
Step 7: Review and Launch Your Research Template
Before launching the research template to collect responses, it is important to review the study settings, timeline, and participant instructions to ensure everything is in place. Once the Terapage research template is ready, researchers can review the details and launch it to start collecting responses. This final step brings the planning process together, allowing teams to move from designing their research study to gathering insights from their target audience.

Figure 19: Researchers previewing the selected research template in Terapage to ensure all essential sections are completed before launching the study.

Figure 20: Terapage confirming the successful creation of a study using the selected research template.
Step 8: Review Your AI-Powered Analysis
Once responses start coming in, AI-powered research tools help researchers make sense of the data more efficiently. Instead of reviewing every response manually, researchers can use AI-generated summaries, sentiment analysis, charts, and thematic categorisation to identify recurring patterns and understand participants’ perspectives. They can then explore individual responses, transcripts, and supporting media to understand the reasoning behind those patterns. With Terapage, researchers can bring these findings together, share insights with their teams, and decide on the next steps based on what they have learned.

Figure 21: Terapage displaying the study completion rate and the total number of responses submitted by participants in the research template-based study.

Figure 22: Sentiment distribution and tone intensity of responses collected through customised research templates in Terapage.

Figure 23: Detailed sentiment analysis of responses collected through customised research templates in Terapage.

Figure 24: Theme categorisation and tagged response excerpts from studies conducted using customised research templates in Terapage.

Figure 25: How to use market research templates to design a study, from first idea to AI-powered insights in eight steps.
What Mistakes Should You Avoid When Using Research Templates?
Templates can make research planning easier, but they are most effective when researchers use them thoughtfully.

Choosing a Template Before Defining the Objective
A template may look attractive and relevant, but that does not ensure it will address the actual question the business needs to answer. Therefore, defining your objective is the foundation stone of your research study.
Using Every Question Without Reviewing It
Not every question will be appropriate for your audience or research context. Therefore, questions should be shortlisted or edited as per the needs of your research study.
Choosing Methods That Do Not Fit the Research Question
If your team likes a survey, it does not mean the research question supports that template. As interviews, surveys, and product tests serve different purposes, market researchers must select the method based on the information they need.
Overlooking Study Settings
Even a well-structured set of activities needs appropriate scheduling, participant arrangements, visibility, and other relevant settings. If these are not set properly, the study becomes a waste of time and resources.
Collecting Data Without a Plan for Using the Findings
Decide how the results will inform a business or product decision before the study begins. This helps keep the research focused on outcomes that matter.

Figure 26: Common mistakes to avoid when using research templates, and what to do instead.
Start Your Next Study From a Research Template
Every great decision starts with a good question, and ready-built research templates help you ask it well. But the real magic happens when you stay in the driver’s seat by setting a clear goal, picking the right type, trimming the questions that don’t belong and double-checking your settings before you hit launch.

Your next study doesn’t have to start from zero. So pick a template, make it yours and let Terapage turn your questions into insights.

Figure 27: Terapage, an AI-powered all-in-one market research platform.
Ready to launch your next study from a template?
Start your 7-day free trial
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No credit card required. Need help adapting a template? Our Co-pilot Research Services team can help.

AI-Moderated Interviews: 5 Formats Modern Market Researchers Should Know

LAIBA CHAUHDRY — Wed, 14 Oct 2026 11:07:31 +0000

Key takeaways

An AI-moderated interview is a research interview led by an AI moderator that asks questions, follows up on vague or interesting answers and records everything for analysis.
There are five AI-moderated interview formats on Terapage: text, WhatsApp, voice, video and telephone (AI-powered CATI).
Text, WhatsApp, voice and video interviews share one four-step set-up; telephone interviews add campaign, participant import, test-call and compliance steps.
The right format depends on who your participants are and what you need to learn, from considered written answers to emotion, reactions and reach without internet.
Every format feeds the same AI analysis: searchable transcripts, speech maps, sentiment and intensity, AI excerpts and quote analysis.
AI has moved from experiment to everyday business practice. According to Amazon’s 2026 Unlocking Europe’s AI Potential research, 54% of European businesses now use AI, up from just 33% two years earlier. Market research is changing just as fast. Teams are expected to deliver deeper insight from more conversations, in more markets, in less time.

AI-moderated interviews meet that demand. One AI moderator can run hundreds of interviews at once, and each conversation keeps the depth of a one-to-one interview. But the format matters as much as the moderator: a busy shopper may prefer to reply on WhatsApp, while a rural respondent may only answer the phone.

This guide covers the five formats of AI-moderated interviews on Terapage: text, WhatsApp, voice, video and telephone. For each one, it explains when the format works best, how a study is set up and how the data is analysed.

What Is an AI-Moderated Interview?
An AI-moderated interview is a research interview led by an AI moderator. It is built on conversational AI, which IBM describes as technologies “such as chatbots or virtual agents, that users can talk to.” The AI moderator asks your questions, listens to each answer, follows up when an answer is vague or interesting, and records everything for analysis.

Instead of a fixed script, the AI moderator follows a discussion guide and responds to what each participant says, much like an experienced interviewer. New to the method? Start with this guide to conducting your first AI-moderated interview.
**
How Does an AI-Moderated Interview Work?**
Researchers set up the study once, and the AI moderator then runs every interview, asks follow-up questions and records each answer for analysis. Text, WhatsApp, voice and video interviews share the same four-step set-up, while telephone interviews have their own.

1. Choose the AI-Moderated Interview Format
Researchers start by choosing how participants will interact with the AI moderator: an interactive video call, an interactive voice call or a guided text and chat interview. Chat interviews can also run on WhatsApp.

Figure 1: Choosing the interview mode for an AI-moderated interview on Terapage.

Figure 2: Selecting WhatsApp Chat as the chat channel for a guided text and chat interview.

2. Add the Study Objective, Questions and AI Probes
Next, researchers describe the study objective and research theme, and AI can generate the interview questions from it. Each question can then carry follow-up probes, which researchers write themselves or let AI suggest, so the moderator asks for more detail whenever an answer is short or unclear.

Figure 3: Adding the activity details and study objective so AI can generate interview questions.

Figure 4: AI-generated interview questions, each with its own follow-up probes.

Figure 5: Adding an interview question with follow-up probes for the AI moderator.

3. Set Up the AI Moderator
Researchers choose the moderator’s name, tone of voice, speech voice and avatar once. Every participant then hears questions asked in the same way, which keeps interviews consistent and free from interviewer bias.

Figure 6: Setting the AI moderator’s name, tone of voice, speech voice and avatar.

4. Review and Launch the Interview
Finally, researchers check the activity overview, questions, AI moderator, schedule and participant incentives on one screen. Participants can come from the existing study, an insight community or participant recruitment, and the interview is published in one click.

Figure 7: Reviewing an AI-moderated interview before publishing, with the schedule and participant rewards.

What Are the 5 Formats of AI-Moderated Interviews?
Every format uses the same AI moderator, adaptive probing and analysis. What changes is how participants take part. On Terapage, they can join on any device, through the channel that suits them best.

1. Text-Based AI-Moderated Interviews
In a text-based interview, participants type their answers at their own pace, usually on their phone. The AI moderator reads each reply and follows up on it, for example by asking participants to walk through a real example instead of giving a general opinion. When the interview ends, responses are saved instantly for analysis.

Best for:

Sensitive topics where participants prefer privacy
Participants who like to think before they answer
Studies that need clean written responses with no transcription

Figure 8: A text-based AI-moderated interview on mobile, from a follow-up probe to the completed screen.

Participants who prefer not to type can record their answer instead, and it is transcribed straight into the chat. Read more about what works in AI-moderated chat interviews.

Figure 9: A participant records an answer in a text-based AI-moderated interview, which is transcribed into the chat.

2. WhatsApp-Based AI-Moderated Interviews
In a WhatsApp-based AI-moderated interview, participants take part on a messaging app they already use every day. Researchers simply select WhatsApp as the chat channel during set-up. Participants can reply with text or voice notes, and the AI moderator follows up on each answer.

Best for:

Consumer and mobile-first audiences
Shopper and usage studies for consumer goods and services
Markets where WhatsApp is the main way people communicate

Figure 10: An AI-moderated WhatsApp interview on mobile, with a participant replying by voice note.

Participants can also share photos and screenshots during the conversation, such as an error message from a failed checkout, and the AI moderator probes for more detail.

Figure 11: A participant shares a screenshot in an AI-moderated WhatsApp interview and the AI moderator probes further.

3. Voice-Based AI-Moderated Interviews
In a voice-based AI-moderated interview, participants speak naturally with the AI moderator, just as they would on a call. Every answer is transcribed live, so tone, hesitation and detail are captured without anyone taking notes. Learn how AI-led automated interviews are transforming conversational research.

Best for:

Participants who find speaking easier than typing
Emotional or experience-led topics
Longer stories that lose detail in text

Figure 12: A voice-based AI-moderated interview on mobile, with a live transcript.

4. Video-Based AI-Moderated Interviews
In a video-based AI-moderated interview, the AI moderator appears as an avatar with real-time facial expressions. It listens to each answer and keeps a live transcript, much like a face-to-face interview. Researchers can preview the interview before launch. Our step-by-step guide to AI-moderated video interviews walks through the full set-up.

Best for:

User experience research
Concept, ad and product testing, such as online qualitative concept testing
Studies where seeing reactions adds meaning

Figure 13: Previewing a video-based AI-moderated interview, with the AI moderator listening and a live transcript.

Participants can join from a laptop or a mobile phone, so they can take part from wherever they are.

Figure 14: A participant taking part in a video-based AI-moderated interview on mobile.

5. AI-Moderated Telephone Interviews (AI-Powered CATI)

In AI-moderated telephone interviews, the AI moderator calls participants at scheduled times and conducts the interview naturally, asking questions and following up just as it does in the other formats. This brings AI to traditional phone-based research without the need for a call centre.

*Best for:
*

Participants who prefer phone calls
Audiences with limited internet access
Large-scale fieldwork with wide geographic reach
Public health and healthcare research across regions

How to Set Up an AI-Moderated Telephone Interview

Create the campaign: Researchers choose the campaign purpose, such as market research or recruitment, and add the research activity name and description.

Figure 15: Setting the campaign purpose and research activity details for an AI-moderated telephone interview.

Add questions and probes: AI drafts the questions and follow-up probes from the study description, and researchers review, edit or add to them before any calls are made.

Figure 16: AI-generated questions and follow-up probes for an AI-moderated telephone interview.

Add participants: Participants can come from the current study, a CSV file or connected tools such as Salesforce, with phone numbers checked automatically for missing or duplicate entries.

Figure 17: Adding participants to an AI-moderated telephone interview campaign.

Figure 18: Importing participants from Salesforce for an AI-moderated telephone interview.

Preview the call: Before launch, researchers choose the AI interviewer’s voice and tone, then place a short test call to their own phone to hear the interview exactly as participants will.

Figure 19: Previewing an AI-moderated telephone interview with a test call to the researcher’s phone.

5. Compliance Built Into Every Call
Compliance is managed inside the campaign. Researchers can keep a Do-Not-Call list, track opt-outs and check country rules before calls go out, so every participant is contacted responsibly.

Figure 20: Managing the Do-Not-Call list, opt-outs and country rules for AI-moderated telephone interviews.

6. Tracking and Analysing AI Telephone Interview Results
Once calls begin, one dashboard tracks participants, total calls, completions, answer rate, average duration and opt-outs. Researchers can read every transcript, review key takeaways, transcript insights and a word cloud, and use Talk to your data to ask questions in plain language. Read more about how AI telephone interviews work, or how recruitment teams use them to screen candidates faster.

Figure 21: A results and AI analysis dashboard for AI-moderated telephone interviews.

How to Choose the Right AI-Moderated Interview Format
The right format depends on who your participants are and what you need to learn. Use this quick guide to match each format to your study.

Figure 22: When to use each of the five AI-moderated interview formats, and what participants need.

Some conversations still need a person, such as very sensitive interviews or stakeholder sessions. For those, many teams combine AI-moderated interviews with live interviews through hybrid research.
**
How Is Data From AI-Moderated Interviews Analysed?**
Analysis does not wait for fieldwork to end. AI-powered insights start working during the conversation and cover every format, so researchers can unlock insights with AI without coding answers by hand.

Transcripts and Speech Maps
Every interview has a searchable transcript, with an AI summary, AI analysis, word cloud and uploaded media in one place. Each participant answer is tagged, so researchers can quickly spot the most useful moments.

Figure 23: A searchable interview transcript with tagged participant answers and AI analysis tabs.

For group and spoken interviews, a speech map shows when each participant spoke and for how long, which helps researchers see who led the conversation.

Figure 24: A speech map timeline showing when each participant spoke and for how long.

AI Sentiment Analysis and Intensity
Responses are grouped into mood categories, such as positive learning or cautious optimism, and the granular sentiments behind them. Each mood shows its responses, share, average weight and strength. Learn more in our beginner’s guide to AI sentiment analysis.

Figure 25: Sentiment analysis of AI-moderated interviews, with mood categories and intensity.

The same results appear in a sentiment table that researchers can filter by emotion and strength, sort and export.

Figure 26: A sentiment table linking each emotion to a key participant statement.

AI Excerpts and Quote Analysis
The AI groups what participants said into topics and ranks them by the number of responses. Hovering over any topic reveals the verbatim quotes behind it.

Figure 27: AI excerpts ranking interview topics, with the verbatim quotes behind each one.

Quote analysis then ranks themes by how often they were mentioned, with every source quote one click away. Findings can move straight into reports and dashboards or branded insight reports.

Figure 28: Quote analysis ranking themes by how often participants mentioned them.

Consent, Security and AI Transparency in AI-Moderated Interviews
Consent is part of every study set-up. Before an interview begins, participants review and accept the study terms, such as a confidentiality agreement, through a mandatory e-consent. All responses are stored on a secure, GDPR-compliant platform, in line with Terapage’s AI transparency principles.

Figure 29: A mandatory e-consent that participants accept before an AI-moderated interview.
**
Choose the AI-Moderated Interview Format That Fits Your Participants**
The best AI-moderated interview is the one participants are comfortable taking part in. Text suits considered answers, WhatsApp suits everyday engagement, voice and video capture emotion and reaction, and telephone reaches people that online methods miss. On Terapage, all five formats share one set-up, one AI moderator and one analysis workspace, alongside every other platform feature for in-house teams and research agencies.

Figure 30: Terapage’s five research products and shared platform features on one unified platform.
To try AI-moderated interviews on your next study, start a free trial or request a demo.

AI-Moderated WhatsApp Interviews: How Conversational AI Is Changing Participant Engagement

LAIBA CHAUHDRY — Wed, 14 Oct 2026 10:44:30 +0000

Key takeaways

An AI-moderated WhatsApp interview is a one-on-one qualitative research interview run automatically on WhatsApp by an AI moderator instead of a human moderator.
Participants reply in their own words, by text, voice note, image or video note, on an app they already use every day.
A six-step process covers the research objective, an AI-generated questionnaire, AI moderator set-up, scheduling and invites, the conversation itself and real-time AI analysis.
Conversational AI uses adaptive probing to ask follow-up questions, which studies link to more informative, specific and detailed answers than standard web surveys.
WhatsApp interviews suit exploratory "why" and "how" questions, but not audiences who are not on WhatsApp, studies that need to see reactions, or projects that cannot protect participant data.

You share a survey link.

Participants open it, answer hardly six to eight questions, and quietly close the tab.

Sound familiar?

The problem may not be your participants. It may be the format.

Traditional online surveys require participants to visit certain links in a compatible web browser such as Google Chrome or Opera.

For many people, this creates friction before they even begin. Others lose interest when questions feel repetitive, impersonal, or disconnected from their experiences. This leads to incomplete surveys, making research teams vulnerable to inadequate data.

Now, think of a format where people spend most of their day, such as texting, calling or replying to their friends, family, and co-workers. They are constantly sharing content without any barrier.

WhatsApp, with 3 billion users worldwide, is one familiar place where people can easily start a conversation.

Now add AI to that conversation, and participant engagement starts to look very different. Researchers can invite participants to answer open-ended questions, explore their experiences, and respond at a time that suits them. Conversational AI can also ask follow-up questions based on participants' responses, helping researchers explore topics beyond the initial question.

Understanding how AI-moderated WhatsApp interviews work can help researchers decide when this method is appropriate and how to use it responsibly.

What Is an AI-Moderated WhatsApp Interview?
An AI-Moderated WhatsApp Interview is a one-on-one qualitative research method for market research and candidate screening conducted automatically through WhatsApp by an AI Moderator/Agent rather than a human moderator.

Participants answer in their own words, using the app already on their phone. WhatsApp supports both typed messages and voice notes, which gives people flexibility in how they respond (Mavhandu-Mudzusi et al., 2022).

Figure 1: AI-Moderated WhatsApp Interview at Terapage using adaptive probing and conversational AI for high participant engagement.

How Does an AI-Moderated WhatsApp Interview Work?
Running an AI-moderated WhatsApp interview takes six steps, from defining the research objective to analysing responses in real time.

Step 1: Define Your Research Objective
Every research team has one key question to answer:

What does this study aim to explore?

To answer this, researchers establish clear goals and objectives based on what they want to understand, whether it is customer satisfaction and dissatisfaction, reactions to a new product concept, factors influencing purchase decisions, or participants' experiences with a particular service.

Clear and concise research objectives help the AI moderator identify relevant information, ask meaningful follow-up questions, and distinguish insights that contribute to the research question from responses that fall outside the study's scope.

Figure 2: Setting the research objective for an AI-moderated WhatsApp interview on online cart abandonment, including adaptive probing around checkout barriers, pricing, trust, delivery, and return policies.

Step 2: Prepare the Interview Questionnaire
A questionnaire is the backbone of any research study. If it is not carefully designed, even a well-planned study may fail to produce meaningful and reliable results. Therefore, designing an effective questionnaire is one of the most important tasks for any research team.

Modern research platforms like Terapage allow research teams to design questionnaires with the help of AI. Researchers can simply define their study objectives and goals, and AI can generate a complete questionnaire with adaptive probing, making the research experience more natural, engaging, and conversational.

However, this does not replace the role of research teams. Instead, it empowers them to review, edit, refine, and approve the questions and probes generated by AI. Researchers can ensure that each question is relevant, easy to understand, and phrased in a natural, conversational way while remaining aligned with the study's objectives.

Figure 3: Researcher can review, add and edit the AI-generated Questions for WhatsApp AI-Moderated Interview during activity design at Terapage.

Figure 4: Researcher Approving AI-Generated Questionnaire for WhatsApp AI-Moderated Interviews.

Step 3: Configure the AI Agent for WhatsApp Interviews
AI-moderated WhatsApp interviews are more than simple polls or tick-box surveys. They use conversational AI to conduct qualitative research through real-time, open-ended conversations with participants. An AI interview moderator asks relevant questions, follows up on participants' responses, and uses adaptive probing to explore their experiences, opinions, and motivations in greater depth.

The AI moderator plays a critical role in the quality of these interviews. Research teams can configure the AI agent's tone, personality, language, and accent according to their research objectives and target audience. This customisation creates more natural, engaging, participant-friendly conversations while keeping interviews aligned with the study's goals.

Terapage enables research teams to customize their AI moderators with a variety of tones and personalities and supports more than 30 languages for AI-moderated WhatsApp interviews. These capabilities help researchers conduct multilingual qualitative market research, engage diverse participant groups, and gather richer insights through conversational AI and adaptive probing.

WhatsApp chat is one of several AI-moderated channels on the same platform, alongside AI-moderated voice interviews, AI-moderated video interviews and AI telephone interviews, so teams can pick the format that best suits each audience

Figure 5: Researcher Selecting WhatsApp Chat for AI-Moderated Interview during Activity design in Terapage Workspace.

Figure 6: Research teams can configure their AI-Moderator/Agent for WhatsApp Interviews at Terapage.

Step 4: Schedule WhatsApp Interviews and Invite Participants
Once the AI moderator is configured, the next step in conducting AI-moderated WhatsApp interviews is to invite participants and schedule the interview campaign. Research teams can define the campaign launch date, end date, interview schedule, time zone, and target country to ensure interviews run according to the study's requirements.

Clear campaign dates and times help researchers coordinate participant engagement across regions and time zones. By aligning the interview schedule with participants' locations and availability, research teams can organise WhatsApp interview campaigns more efficiently and create a smoother research experience.

With Terapage, researchers can configure their AI-moderated WhatsApp interview campaigns around their research timelines and participant recruitment plans, helping them manage interview scheduling and coordinate data collection more effectively.

Figure 7: Researchers can configure interview schedule launch and end dates, time zones, country and conversation expiry for their AI-moderated WhatsApp interview.

Figure 8: Selecting Terapage's WhatsApp Contact Number to Communicate with Participants During AI-Moderated Interviews.

Figure 9: Researcher sending WhatsApp Invites to Participants for AI-Moderated Interviews.

Step 5: Conduct the Conversation and Enhance Participant Engagement with Conversational AI
The real advantage of AI-moderated WhatsApp interviews is their convenience. Participants can join a conversation directly through WhatsApp without downloading another app or logging into a new platform, which keeps the experience mobile-friendly from the very first message.

Using conversational AI, the moderator starts with a warm, friendly greeting to help participants feel comfortable sharing their thoughts. When an answer is unclear or incomplete, it asks relevant follow-up questions through adaptive probing to explore the response in greater depth.

For instance:

Initial question: What did you think of your recent online shopping experience?

Participant: It was okay, but delivery took too long.

Possible follow-up: How long did you expect delivery to take, and how did the delay affect your experience?

Figure 10: An AI moderator using adaptive probing on WhatsApp to explore why a participant's online payment failed, after the participant shares a screenshot of the checkout error.

This natural, conversational approach can improve participant engagement and help research teams gather richer qualitative insights through AI-moderated WhatsApp interviews.

Figure 11: Participants engaging in meaningful conversation on WhatsApp during AI-Moderated Interview.

Step 6: Get Real-Time Insights and AI-Powered Analysis
AI-moderated WhatsApp interviews do not end when the conversation is over. Research teams can receive participant responses and access AI-powered analysis in real time, helping them identify emerging themes and patterns without waiting for all interviews to finish. By combining conversational AI with real-time data analysis, Terapage helps researchers speed up data collection and turn participant feedback into actionable insights more efficiently. It helps research teams to generate:

AI-Powered Summaries
Sentiment Analysis
Tones/Emotions Detection
Themes/Coding
Taxonomies
Excerpts
Highlighted Reels

All of these outputs sit in one reports and analysis workspace, ready to turn into shareable insight reports.

Figure 12: AI-powered Sentiment Analysis of responses in real time for WhatsApp AI-Moderated Interviews.

Figure 13: AI-powered Excerpts generated from the participants' responses in real time for WhatsApp AI-Moderated Interviews.

Figure 14: AI-powered Sentiment Distribution and Emotion detection of responses in real time for WhatsApp AI-Moderated Interviews.

Why Does WhatsApp Offer a Different Research Experience?
If conversational AI is changing how participants engage, WhatsApp is where much of that change is happening. Here's why it works so well.
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Familiarity and Convenience** Participants who already use WhatsApp may find a messaging-based interview more familiar than an unfamiliar research application or a scheduled video call. They can interact through a channel they know, potentially reducing some practical barriers to participation. Participants simply open a chat on the app they check every day, so fewer people drop off before the first question (Manji et al., 2021).

2. Flexible Participation
Traditional interviews require participants and moderators to be available at the same time. Asynchronous messaging reduces this requirement, allowing participants to respond around work, family responsibilities, and other commitments. This flexibility is particularly useful for studies involving participants with different schedules. It does not guarantee higher completion rates, since lengthy conversations or poorly timed messages can still lead to disengagement.

3. Participants Can Type or Talk
Messaging allows participants to express themselves in their own words rather than choosing only from predefined response options. Similarly, not everyone enjoys typing long answers. WhatsApp supports both written messages and voice notes, so participants can reply the way that feels easiest to them (Mavhandu-Mudzusi et al., 2022). Additionally, they can also record a short video note, provide images or other supporting documents. This allows rich responses with ease without any extra effort, saving time and money.

Figure 16: Participant recording voice notes during WhatsApp AI-Moderated Interviews.

4. WhatsApp Interviews Reach Anywhere, Anytime
Chat interviews don't need a shared time slot. Participants can reply on a commute, during a break, or after dinner. There's no scheduling and no time-zone juggling, which opens the door to people who would never book a live call.

Figure 17: At Terapage, AI-Moderated Research is Multilingual and globally accessible.
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How Is Conversational AI Improving Participant Engagement in WhatsApp AI-Moderated Interviews?**
Participant engagement does not mean they are filling out forms and submitting responses. Qualitative Research involves deeper conversations, encouraging participants to explain their experiences, defend their choices, clarify their decisions and share evidence to support their point.

Therefore, conversational AI is improving participant engagement in AI-moderated WhatsApp interviews.

1. It Listens Before Responding
One key difference between an AI-moderated interview and a fixed questionnaire is the ability to ask follow-up questions based on what a participant says. For instance, if a participant says:

"The signup was too complicated."

Instead of moving on to the next question, the AI Agent would probe deeper and ask a follow-up question:

"As you mentioned the signup was too complicated, could you please elaborate on it or highlight the part that you found complex?"

Therefore, well-structured probes help researchers uncover motivations, reasons, expectations and concerns.

A 2025 study also supports this, as it tested four theory-based interview probes in a chatbot built to improve the quality of qualitative data (Jacobsen et al., 2025).

2. A More Flexible Pace
Asynchronous interviews allow participants to respond without necessarily remaining in a live session for the entire conversation. They may have time to reflect on a question before answering.

This can be helpful when exploring experiences that participants need time to recall. On the other hand, a long interview spread across multiple sessions may interrupt the flow of the conversation or cause participants to lose interest.

3. Delivers Better Answers to the Same Questions
People are more inclined towards sharing their responses when it is a chat involving day-to-day conversations. To validate this proposition, a study was conducted in 2020 by a group of researchers involving 600 respondents where half took a standard online survey, whereas the other half had a conversation with an AI-powered chatbot. The results were striking: the chatbot conversations produced answers that were significantly more informative, relevant, specific and clear (Xiao et al., 2020).

In short, the questions didn't change. The conversation did.

4. Opportunities for Reflection
A chatbot messaging conversation allows participants to have a free and unbiased conversation without fear of any judgement. A recent study published in PLOS Digital Health in 2026 examined a conversational AI agent deployed through WhatsApp in a community-based weight-management programme. The results found that AI's quasi-human interactional qualities fostered a sense of support while reducing social judgement, enabling more candid disclosure during conversations (Downes et al., 2026).
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Brings Depth to Scale** A human moderator can only talk to one person at a time. An AI moderator can hold many one-to-one chats at once, giving each participant the same patient, consistent experience from the first message to the last. Most of the time, surveys reach many people but lose depth for multiple reasons. AI-Moderated Interviews add depth along with scalability. Researchers at NORC at the University of Chicago have identified that AI-assisted conversational interviewing via textbot can elicit more specific, detailed, and informative open-ended responses as compared to web surveys (Barari et al., 2025).

When Can Researchers Use AI-Moderated WhatsApp Interviews?
AI-moderated WhatsApp interviews can be useful when researchers need to understand participants' experiences, opinions, and motivations through open-ended conversations.

Potential applications include:

Customer experience research
Product and concept testing
Consumer behaviour research
Service improvement
Longitudinal research
Geographically dispersed studies
The method is particularly useful when the research question is exploratory: researchers want to understand why something happens, how people experience it, or what they think about a particular issue.

When Should You Think Twice Before Choosing WhatsApp for Interviews?
AI-moderated chat isn't always the best choice. Consider another method when:

Your audience isn't on WhatsApp. Chat only reaches people who use it.
You need to see reactions. Chat can't capture facial expressions or body language, so an AI-moderated video interview may suit better.
The topic is highly complex or emotionally heavy. Chatbots can still struggle to interpret the huge variety of free-text replies people write (Xiao et al., 2020), and a human moderator may handle nuance better.
You can't protect participants' data. A scoping review found little attention to research ethics across WhatsApp studies, which is concerning given debates about the app's data protection (Manji et al., 2021). Build in e-Consent and secure data handling before you launch.

Figure 18: A quick checklist of eight checks to run before launching AI-moderated WhatsApp interviews, from research goals and probes to privacy, ethics and analysis.

The Future of Market Research Is Conversational and AI-Moderated
The future of market research is not just about collecting more data; it is about making conversations more natural, accessible, and meaningful for participants. AI-Moderated WhatsApp Interviews bring research into a familiar messaging environment, allowing participants to share their experiences in their own words while helping researchers gather insights more efficiently.

With conversational AI, real-time analysis, and flexible participant engagement, research teams can move beyond traditional surveys to explore the reasons behind consumer choices, preferences, and behaviours. Platforms like Terapage make this approach more practical by combining WhatsApp-based conversations with AI-powered interviewing and analysis.

As conversational AI continues to evolve, the real opportunity lies in using it responsibly to improve participant engagement, preserve the depth of qualitative insights, and support better-informed research decisions.

Figure 19: Terapage: An AI-powered all-in-one Market Research Platform.