Streaming brands that are only just thinking about how to leverage AI to generate creative and deliver smarter content recommendations are already falling behind. The conversation has moved on to a host of other potential applications. This includes bolstering research efforts with synthetic respondents, which offers the possibility of replacing costly audience testing with virtual viewers.

These synthetic respondents don’t exist in the real world. They’re essentially artificial stand-ins for real audience members, created to model how actual viewers might engage with content or respond to questions. However, their modelled behaviours can be collected and analyzed far faster than human data. 

Synthetic respondents can represent broad demographic segments, be persona-based, or evolve over time to simulate changing tastes. They promise quick answers to “what might work” without waiting for weeks of real-world patterns to emerge. That speed is tempting, especially in an industry where getting the right content to the right audience at the right time is important. 

But faster data doesn’t automatically translate to better insights. Synthetic respondents only add value if they meaningfully advance our understanding of current subscribers and potential audiences.

HOW SYNTHETIC RESPONDENTS CAN SUPPORT STREAMING

There’s obvious appeal in synthetic respondents for streaming brands: the ability to pre-test shows, forecast potential reach, optimize marketing campaigns, and train recommendation algorithms without waiting for live viewing data. They can run dozens of “what if” scenarios in days rather than months, giving decision-makers a speed advantage in an industry where content turnover is relentless.

Here’s how streaming brands are leveraging synthetic audiences:

• Content Intelligence: Using AI to analyze massive volumes of video and extract granular metadata – tone, emotion, sub-genre – to better predict audience responses.
• Privacy-Safe Reach Mapping: Creating privacy-compliant “virtual IDs” to measure cross-platform reach without relying on identifiable personal data, which is critical in an era of stricter privacy laws.
• Natural Language Data Access: Deploying AI “agents” that let teams query complex datasets conversationally, with models validating each other’s outputs to improve accuracy.
• Faster Insight Discovery: Leveraging AI-powered “story finding” tools to surface actionable advertiser insights in a fraction of the time manual analysis would require.

As NielsenIQ notes, they can support early-stage scenario testing, forecasting potential outcomes before committing to costly human studies, especially when grounded in recent, diverse, in-market behavioural data. 

These applications show how synthetic respondents and related AI tools can slot into real streaming workflows, accelerating testing, filling gaps where direct measurement is difficult, and surfacing opportunities faster. 

LIMITATIONS OF SYNTHETIC RESPONDENTS

On the flipside, a Kantar study reveals a cautionary perspective. When Chat GPT-4 was tested against real survey respondents, its synthetic answers tended to be more positive than human feedback, especially on emotional questions. It also lacked the nuance that comes from lived human experience, often flattening subtle differences in opinion and producing less depth in open-ended responses.

When it came to qualitative responses, Kantar compared a typical human answer on attitudes towards technology with a GPT-4 answer from the perspective of a 65+ Caucasian married male in the US. While initial responses looked similar, repeating the test 50 times and coding on a 5-point scale showed GPT-4’s answers were more stereotypical, less varied, and consistently more positive than human responses.

NielsenIQ add another layer of caution. Synthetic respondents can produce convincing results quickly, but without fresh, diverse, and in-market human data to train and validate them, the insights risk being misleading. They also warn that unvalidated models can give decision-makers a false sense of certainty, potentially steering strategy in the wrong direction.

So for streaming brands, in theory, a synthetic respondent might overstate a platform’s UX based on early-stage subscriber data, while in reality, user experiences evolve – real subscribers may encounter nuanced issues with specific UI features that only surface through lived experience.

WHERE HUMAN INSIGHT STILL WINS

Emotion, creativity, and cultural resonance remain distinctly human strengths. Synthetic respondents can project behaviour based on the past, but they can’t anticipate the next cultural surprise that sweeps through viewers’ hearts. They don’t feel nostalgia, thrill at an unexpected plot twist, or participate in the social buzz.

And the data backs it up. System1 research demonstrates that emotionally engaging content generates up to 57% greater business impact, independent of targeting approach. This highlights that strategies grounded in emotional data deliver superior profitability and resonance. 

Additionally, price sensitivity is a highly subjective and nuanced topic. If streaming brands are collecting data to determine optimal pricing strategies for a specific region, simply inputting geographic and demographic information won’t provide sufficient insight. This approach overlooks crucial cultural factors, local economic conditions, competitive landscapes, and consumer behaviour patterns unique to each market, which isn’t something synthetic respondents can provide.

Real viewers can break patterns, defy trends, and reward risks. That’s why the most successful streaming campaigns still start with a creative spark rooted in genuine human understanding. 

FINAL THOUGHT

Synthetic respondents can be part of the toolbox but must always be grounded in recent, real human data. If platforms lean too far into synthetic projections, they risk building a content strategy that fills a spreadsheet but fails in the living room. The winning formula is using AI to broaden the perspective, while letting human creativity and emotional intelligence lead the way.