How to create synthetic respondents: our guide
FEB 2024
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Synthetic respondents are a valuable tool in research, particularly when real-world data is scarce or difficult to collect.
Creating synthetic respondents involves defining parameters that reflect the characteristics of your target audience. This could involve demographic variables, user personas, or modifying existing datasets. Once these parameters are set, you can use Large Language Models (LLMs) to generate a synthetic sample that mirrors your target audience.
The quality of your synthetic respondents largely depends on the quality of your instructions. Therefore, it's important to double-check your data for consistency.
Remember, synthetic respondents should closely resemble your real-world audience in order to provide valuable insights. For a detailed guide on how to create synthetic respondents, read our comprehensive guide here.
Try MindPort for better insights, faster ⬇︎
MindPort empowers researchers, data teams, and agencies to effortlessly generate synthetic data with unmatched efficiency. Whether you want us to run an end-to-end research project, or just generate the data for your in-house team, we use our proprietary data-driven platform to scope, synthesise, collect, analyze and share data with your team.
Using GPT can only get you so far. Inside MindPort, our data team can organize your projects, scope your requirements, generate a synthetic sample and track individual synthetic participants. We're able to generate validated data in a fully bespoke workflow. This means your teams get the data and insights they need, in one centralized location.
Take your insights and analytics a step further with MindPort's synthetic data and insights:
Even before generating synthetic data, we can tailor over 180 unique categories of variable, totalling over 700 individual parameters per participant, based on your data requirements.
We can scale up from one to one thousand participants, enabling us to generate entirely unique three-dimensional personas that reflect the complexities, nuances, and fidelity of your real-world data.
We take this further by using 3rd party verification and our review framework to benchmark generated data against input data, carefully checking for biases, errors, and miscategorisations.
We're then able to package your synthesized data and insights within a team workspace, incorporating quotes for a visually compelling presentation.
Notably transforms your data analysis process, making synthetic data synthesis a seamless and insightful journey from start to finish.
Interested? Contact us and we'll send you a synthetic sample for free.
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