Automated interviews in research:
Qualitative answers, quantitative numbers
Automated interviews provide researchers, designers, and product managers a powerful tool to achieve both depth and scale in their work. This unlocks significant opportunities for innovation and insights.
By Max de Jong · Last update: 23th of April 2025
Use automated interviews in different situations and for different goals
User feedback
Customer interviews
Instead of surveys
User tests
Insight sessions
User feedback
Customer interviews
Instead of surveys
User tests
Insight sessions
An automated way of conducting interviews in research? Which researcher or designer doesn’t want that? Well, I do! In this blog, we will explain what automated interviews are, how it works, what benefits it has and when it’s best to use it. We have written this article based on information from researchers and designers that are using it at the moment, our own experience building an automated interview platform and our own experience in automating interviews with AI. Parts of this article are (re-)written by ai to improve the quality of the article.
Read this if you would like to start using automated interviews in research set ups, or if you want to know more about automated interviews.
Introduction to automated interviews
Automation, something that everybody loves when done right. In research, automation was always an utopia when it came to analysing qualitative interviews. Interviews have always been a labor-intensive process, requiring researchers to personally engage with participants, often at significant cost and time. Up until now. We have found ways to automate interviews on scale by collecting, processing and analysing interviews with software based on artificial intelligence. With this innovative technology and the birth of automated interviews, the research landscape is rapidly changing, making qualitative interviews scalable to the world.
Create AI research assistants in three simple steps
Create an Automated interview
The automated interview will be conducted by an AI assistant for you
Share the Automated interview link
Share the Automated interview link with your users
What are automated interviews?
In the most simplistic way, we can define automated interviews as interviews that aren’t done by a human. In essence it can be defined a bit broader to ensure most people understand the background of it much better. It highly relates to AI interviews which we could define AI interviews as follows:
Automated interviews involve the use of artificial intelligence (AI) and machine learning algorithms to conduct interviews without human moderation.
Software that is developed for automated interviews, can interact with respondents, ask dynamic questions based on answers, and record responses in real time. Platforms that offer this technology, like f.e. Pitchwave, are capable of understanding natural language, which enables them to engage with participants in a conversational manner, while ensuring standardisation and consistency across all interviews. And even better; automated interviews can interact with respondents in every language at any time.
Applications of automated interviews in the research space
Automated interviews are being used in different research fields. Within social sciences, they are used to gather data on public opinion, social behavior and cultural trends. In UI/UX research they are used to find reasons why people love certain products and experiences, and what they would like to see improved. Market researchers also leverage these tools to understand consumer preferences and behavior at scale over the entire globe. With the birth of automated interviews, more insights can be gathered in a very short amount of time. Making it beneficial to lots of researchers at any time.
Benefits of automated interviews in research
While humans cannot be missed during the research process and fully automation is still far away, there are big benefits to use automated interviews during your research process. We have listed a few of them below:
Scalability
With human interviews, the interviews taken are in a limited amount of time and mostly due to those time constraints to a small number of your persona's or mindsets, most of the time between 10 and 20 (depends on the number of persona's). The time available to take interviews during a project and the time it takes to analyze all results is mostly limited. Since automated interviews are conducted with no human interference, it's possible to scale your interview to an unlimited number of users.
Accuracy
Automated interviews minimize human error and potential human bias in data analysis which is often the case with human interviews. Without that bias, it leads to more reliable results.
Accessibility
Automated interviews make time consuming research activities accessibile to a wider group of companies and businesses, including those without huge amounts of budgets.
Cost effectiveness
Traditional interviews require human interviewers, which means paying for their time and expertise. AI research assistants eliminate the need for human interaction or human labour, allowing organizations to save on salaries, training, and other associated costs. Once the automated interview software is set up, it can handle numerous interviews simultaneously without additional costs.
Advanced data analysis
Automated interviews provide capabilities for advanced data analysis, transforming the way organizations and researchers interpret and utilize interview data. AI is able to analyze responses in real-time during the interview, allowing for immediate feedback and adjustments of questions or aksing followup questions. This real-time processing enables the AI to dig deeper into relevant topics based on the interviewee’s answers, ensuring comprehensive data collection. Besided this, there are multiple capabilities that are enabled by a textual representation of an interview, like pattern recognition, sentiment analysis, natural language processing, predictive analytics, comprehensive reporting or data visualization.
Speed & efficiency
Automated interviews can process and analyze large datasets in a fraction of the time it would take a human. This allows researchers to focus on interpretation and application rather than data collection.
Anonymity and Comfort
Some participants may feel more comfortable sharing sensitive information with a machine than with a human interviewer. This anonymity can lead to more honest and accurate responses, particularly in studies involving stigmatized behaviors or topics.
The benefits & challenges of automated interviews in one overview
It's good to challenge the need of automated interviews. Automated interviews come with a price and therefor it is important to assess the need of it. Tools always contain a set of pros and cons. For many use-cases it is not suitable (yet) to use automated interviews. For some, it may already be a viable option, thanks to the advantages of speed and scalability. Below are the benefits and challenges associated with AI research assistants:
Benefits
Efficiency & Time Saving
Scalability
Cross-Cultural and Multi-Language
Consistency & Objectivity
Cost effectiveness
Advanced data analysis
Accessibility & convenience
Improved Data Quality
Challenges
Lack of human touch and emotion
Technical issues
Limited flexibility to change during a conversation
Bias in algorithms
Privacy concerns
Resistance in adoption by respondents
Cost of implementation
Less respondent engagement during the interview
Challenges and ethical considerations
Since people tend to look at benefits first and feel challenges after, we would like to highlight some ethical concerns we found while doing research to automated interviews. The first concern is the potential lack of empathy in AI-driven interviews, which might affect the depth of responses in sensitive or emotional contexts. While humans are extremely good at feeling what the other person means or read emotions from their behaviour, computers have that ability as well but only to a limited extend.This can potentially cause friction during the interview.
Additionally, ensuring the privacy and security of participants' data is crucial, particularly in light of growing concerns about data breaches and misuse. While the platforms we have used (f.e. Pitchwave) do take privacy and security very seriously and hold to global standards working with data, there might be others that are not taking this seriously and harm the respondent with unsecure systems. What also has to be taken into account, is to be cautious about the design of automated interview systems, as biases in algorithms can influence the data collected. It is essential to continuously monitor and refine these software platforms to ensure they are fair, transparent, and aligned with the research objectives. Each platform does do that in a different way, making results more use-ful than others.
The future of automated interviews in research
As AI technology continues to improve when the algorithms are fed with more data, the automated interviews will only improve in quality. Future developments may include some more sophicisticated NLP (natural language processing), better ways of analysis or global connection to respondents. With this in mind, the future is promising and the innovations will only further solidify the role of automated interviews as cornerstone of modern research methodologies.
To conclude; automated interviews are transforming the research space at this moment already, offering a scalable, cost effective and standardize method of collecting and analyzing data.This makes it beneficial to use by researchers across all disciplines. While challenges remain, the benefits make this still a promising area to step into and move your research activities to research platforms. As these tools continue to evolve, they will play an increasingly important role in the future of the research space.
One of the best Automated interview platforms: Pitchwave.io
We have created an automated interview platform that helps conducting qualitative interviews. Instead of you conducting the research and asking questions to your respondents, our software will ask the questions to your real respondents in a chat. This is convenient to you as a researcher but also for your respondent, since they are able to join the review whenever they want due to the 24/7 availability of the assistant.
The information collected during the interview will be shown in your personal dashboard and you are able to gain insights out of it in an easy and intrusive way.
Set up an automated interview yourself with Pitchwave
Curious to try it out yourself? Within a few minutes you would be able to integrate Automated interviews into your own research. Just follow the steps below to create an AI interview on our platform.
1. Request access on this page
Register for an account with Pitchwave. If you haven't requested access yet, do this first to ensure you will get credentials for your account.
2. Sign in here
After the registration, sign in with the credentials you received.
3. Create a project
After signing in, you are able to create a project which will help you to manage your automated interview research assistant in a structured manner.
4. Create an automated interview
After creating a project, you can create an automated interview by clicking "Create a new research". Once the important details are entered, you can brand your assistant to match your brand style.
5. Brand your automated interview
Branding ensures that users recognize your brand which builds trust. Upload your logo and select your brand colors to match your interview styling.
6. Share your interview link with real respondents
Once your automated interview is ready and branded, you will receive an interview link. Share this link with your respondents so they can start the interview immediately.
7. Receive responses and insights in a few minutes
After respondents complete the automated interview, their answers will appear in your dashboard. You can analyze individual responses or export all data for further analysis.
Frequently asked questions
The most requested answers
