Synthetic Survey Panelists

Reasons to Use Synthetic Survey Panelists

For the field of market research, synthetic survey panelists is an incredibly exciting new development. These artificial entities, powered by Natural Language Processing and huge troves of publicly available third party consumer data, not only hold the potential to revolutionize marketing techniques, but also drastically reduce costs and improve efficiency.

Synthetic survey panelists play a crucial role in simulating customer interactions for UX design, purchase behaviors, preferences, and sentiment. In capturing the essence of real humans, these panelists help marketers, researchers, product strategists, and UX designers test and iterate multiple concepts with ease. The opportunity to test and re-test design, messaging, and other elements in a consequence-free environment is another substantial benefit of using this technology.

In the realm of advertising, generative AI increasingly demonstrates its vast and transformative potential. Many still assume that AI marketing tools are limited to content generation. While this is very much a compelling and growing use case, it’s important to not overlook the incredible predictive power of machine learning-generated feedback. Integrating this concept with synthetic users provides an unprecedented level of customization and tailoring in ads distribution, which can dramatically boost marketing efficacy.

With the power of synthetic users, a new era of user-experience, design, and research is well and truly upon us, holding promise of significant evolution in approaching and boosting customer engagement.

Synthetic Data Generation

Synthetic data generation is a very new and not-well-understood concept. To summarize as plainly as possible, it requires Natural Language Processing to analyze troves of consumer data in order to properly emulate their preferences and emotions. 

The difference between real and synthetic data is sometimes in the level of contextual detail. In general, human responses tend to include a lot of “random” detail that doesn’t seem to matter directly to the prompt. This can provide researchers with valuable clues into the person’s mindset. AI-generated synthetic data, on the other hand, typically summarizes the average response, which omits such detail. Native AI has a feature that allows users to toggle between High Fidelity to source material (descriptive analytics output) and High Creativity (predictive output).

Synthetic data carries the same statistical properties as real data. However, it provides an opportunity to simulate various scenarios which may be challenging or impractical to conduct with real data. Synthetic data paves the way for organizations to probe into a myriad of situations and contingent scenarios without infringing upon customer privacy or relying heavily on actual data. This artificial data thus, may aid in better informing decisions, optimizing strategies and hoisting the curtain to new outlooks in market research.

To sum up, synthetic data generation is a potent and evolving methodological advancement. The utilization of synthetic data in market research could unlock many prospects and advantages. However, it is important to understand the risks and appropriate use cases. Some market researchers prefer to use synthetic data to simulate potential scenarios, and then validate using human responses.

Synthetic Data Examples

Synthetic data examples already exist in many industries, especially when real-world data may be extremely sensitive so researchers can simulate scenarios without revealing the confidential personal data.

A perfect illustration of synthetic data generation's importance can be seen in healthcare, where synthetic data is utilized to access sensitive patient records without violating privacy laws. By generating synthetic data in healthcare, researchers and practitioners can conduct tests, analytics, training, and medical prediction models efficiently.

For those keen on exploring this further, we recommend downloading a sample synthetic dataset for your particular industry. These off-the-shelf datasets help in understanding the structure and quality of synthetic data in various fields, from healthcare to e-commerce, banking to social media.

Synthetic data is rapidly becoming an integral part of the tech landscape, offering practical solutions to issues of data privacy and accessibility while enabling precise testing and analytics. This fascinating topic is yielding an ever-growing array of applications, methodologies, and discussions throughout the world. Native AI is proud to be part of this revolution for the consumer insights industry. To view more about how we can enhance your customer survey data, visit our Market Research solutions page.