Buyer guide
Which synthetic research tool do you need?
Some tools answer questions. Others work with data you already have. Here's how to choose.
Start with one question
Say you have three ideas for a new product. You want to know which one is worth testing with customers. That's a useful starting point for a demo. 'Show us your AI' isn't. Write down the question, who the customers are, and what you'll do with the answer.
Want to ask an AI audience questions?
Look at synthetic respondents. These are AI-generated participants that answer surveys or interviews. Qualtrics offers Synthetic Panels inside its survey platform. Synthetic Users lets you describe the audience you want to hear from. Ask the provider to show you how its answers compare with answers from real people like your customers. [1][2]
Already know your customer groups?
A digital twin can make that research easier to use. For example, your team could ask questions of a model based on an existing customer group. Ipsos PersonaBot is designed to help teams use their segmentation research this way. Segmentation simply means dividing customers into groups with shared needs or behaviour. [3]
Need more detail from an existing survey?
Look at sample augmentation, also called boosting. It adds generated responses to a dataset you've already collected. Toluna describes HarmonAIze Boost as a tool used after survey fieldwork. The key question is whether it improves the analysis you need, such as understanding a smaller customer group. Generated responses are not extra people you interviewed. [4]
Want to explore a change?
Audience simulation tools let you explore questions such as 'What might happen if we change the price?' Give each provider the same example and compare what comes back. Before you buy, agree on what a good result looks like, what data you'll need to supply, and the full cost of running the work.
Write down the output your decision needs
A transcript, a ranked concept list, a distribution of survey answers and an augmented dataset answer different questions. Suppose two concepts receive positive synthetic interviews. That may help identify objections to explore, but it does not provide a measured share of customers who will buy. Specify what you need to receive and how it will change the decision. This makes it easier to compare a respondent platform with a segmentation tool or an augmentation service.
Match the audience and question types
A general-population model is not automatically a model of your customers. Qualtrics, for example, documents a US general-population panel in English and notes limitations for questions about past behavior and personal experiences. A study in another language or among specialist purchasers needs relevant data and an evaluation in that setting. For a research-based twin, inspect the population, variables and collection dates in the research used to build it. [1][3]
Compare performance on one shared study
Do not compare a correlation from a concept ranking with a percentage agreement from another questionnaire. Give shortlisted providers the same brief and keep the human comparison out of their setup. Choose the metric around the decision: concept order, response distributions, subgroup differences or an observed behavioral outcome. Report weak results as well as the average. This small common test gives a more useful choice than a general accuracy figure from unrelated work.
