The world of market research is evolving rapidly. Synthetic respondents, also known as AI-generated or virtual participants, are being proposed as a potential alternative to human data collection. As brands seek faster, cost effective, and scalable insights, synthetic respondents offer an attractive alternative to traditional research methodologies; but how reliable are they? Could they replace real human participants entirely?
At FieldworkHub, we specialise in qualitative research, where real human insight is invaluable. However, we also understand the impact of new technologies on our industry. In this blog, we explore the rise of synthetic respondents, their benefits and limitations, and what they mean for the future of market research.
What are synthetic respondents?
Synthetic respondents are AI-generated entities that simulate human-like responses in market research studies. Using advanced machine learning and natural language processing, they analyse existing datasets to predict and generate responses to surveys, interviews and discussion prompts.
They are starting to be used in certain types of quantitative research, where large-scale data collection is required, allowing researchers to gather insights without the logistical complexities of recruiting real participants.
But are they a true replacement for human respondents?
The advantages of synthetic respondents
Synthetic respondents offer several advantages that can be useful for certain types of research, such as:
- Speed and scale. AI-powered respondents can complete surveys instantly, allowing brands to collect large volumes of data within minutes, rather than weeks.
- Cost-effectiveness. There are no recruitment costs, and no incentives to pay so AI respondents eliminate most of the variable costs associated with market research.
- Global reach and access to niche audiences. Synthetic respondents are not limited by geography, making it possible to run international studies without the need for translation work. They also offer an opportunity to research niche audiences that might be hard to recruit for conventional research.
- Maintain confidentiality and avoid data privacy concerns. Using synthetic respondents avoids any data privacy concerns and allows researchers to ask questions that might be difficult to ask real people.
These benefits make synthetic respondents particularly appealing for early-stage concept testing, pricing analysis, and large-scale behavioural trends.
Challenges in qualitative and quantitative research
While synthetic respondents offer clear advantages, they also present significant challenges. This is especially apparent when conducting qualitative research, where emotional depth, spontaneous reactions, and nuanced insights are key findings.
Challenges in qualitative research
In qualitative research, the richness of the human experience plays a crucial role in uncovering insights. Synthetic respondents struggle with:
- Lack of emotional intelligence. AI may be able to process words, but it does not think or feel like a human does. The ability to probe deeper, interpret emotions, and respond dynamically is something only real people can offer.
- Contextual limitations. Humans bring personal experiences, cultural nuances, and real-world perspectives to discussions – concepts that AI struggles to replicate. It’s also worth noting that the large language models which underpin most AI platforms typically have access to a lot more training material in English than other languages so synthetic responses may present an anglo-centric view of the research questions.
- Interaction and engagement. Focus groups and depth interviews thrive on live interactions, body language, and interpersonal cues, which AI simply cannot reproduce.
- Depth of responses. Synthetic respondents generate responses based on existing data, meaning they may lack originality and fresh perspectives on emerging trends.
For studies that rely on human storytelling, emotional engagement, and exploratory insights, synthetic respondents simply do not provide the same value as real participants.
Challenges in quantitative research
For quantitative research, synthetic respondents present different challenges, for instance:
- AI bias and data limitations. Synthetic respondents rely on historical data, meaning they might reinforce existing patterns rather than uncover new consumer behaviours.
- Validity of data. Since AI doesn’t make real-life purchasing decisions, its responses may not accurately reflect the complexities of human buying behaviour.
- Sampling accuracy. Without real demographic backgrounds, synthetic respondents cannot fully replace carefully screened, real-world participants.
- Reliability of results is hard to assess. There is a lack of transparency in how synthetic responses are generated and AI tools tend to hallucinate from time to time. This makes it difficult to judge whether quantitative results from synthetic responses are accurate.
While synthetic respondents can increase efficiency in large-scale quantitative research, their use must be carefully considered to ensure data validity, accuracy, and representation of true human behaviour.
Balancing AI and human respondents: Key considerations
While AI-powered respondents can be a valuable tool in market research, they work best when integrated strategically alongside traditional research methods. Here’s what to keep in mind:
- Synthetic respondents are best used for large-scale, trend-driven research. Their ability to process vast amounts of data quickly makes them ideal for early-stage research, predictive modelling, and data validation.
- Human respondents provide the nuance, emotion, and depth needed for qualitative insights. For research involving brand perception, concept testing, and human behaviour, real participants remain essential.
- A hybrid model can offer the best of both worlds. Some researchers are now using AI-generated respondents to pre-test surveys, refine question wording, and identify key themes before conducting full-scale market research studies.
Final thoughts
The future of market research is not about choosing between AI and humans – it’s about using the right approach for the right study, and also for the right stage of the research.
Synthetic respondents offer speed and scale, making them a valuable tool for refining certain research applications. However, when it comes to emotional intelligence, deep probing, and authentic storytelling, nothing replaces real human insight.
At FieldworkHub, we remain at the forefront of qualitative research, ensuring that businesses continue to access rich, meaningful insights from real people – while also embracing new innovations that enhance research effectiveness.
Want to talk about the future of market research? Get in touch – see how we can help you:
📩 hello@fieldworkhub.com
☎️ +44 (0)20 7458 4950
