We've reimagined how traditional research methods, such as surveys and user interviews, should work in the age of AI. To help you capture user insights faster and build better product experiences, we've created a new conversational AI-first user research method that gives you the breadth of a survey and the depth of a user interview.
Studies on Wondering combine traditional survey-style questions (such as multiple-choice, rating-scale and open text questions) with AI-generated follow-up questions that help you dig deeper into each response. The result is a flexible research method that can be used to can be used to gather quick but deep insights with users you recruit in your product, from Wondering's panel or via unique shareable study links.
How do I create an AI-first study on Wondering?
For an in-depth guide about how to create AI-first studies on Wondering, see this dedicated section of our help centre.
We recommend getting started by generating your study. To do this:
Pick the kind of study you're planning on running (AI-enhanced survey, Image test or Prototype test). If you're planning on doing a mixture then just pick the one that you think fits best.
Add in what you'd like to learn - to help you get started here we've added in 4 good examples for this per study kind.
Now you'll have a draft study made up of Wondering blocks. These are the building blocks of all studies. There are 6 block-types you can use to create your studies: Message, Explore, Rate, Choose, Image test and Prototype task (currently in early access).
You can now customise your study to achieve your goal by adding, removing or re-ordering the blocks. This will allow you to create studies ranging from the very simple (such as asking a single NPS question to track customer sentiment) to the more complex (such as in-depth AI-moderated semi structured user interviews).
Read this guide for more details on how each of the block types work.
What can I do with AI-first research studies?
Scale your user interviewing with AI-moderated semi-structured user interviews
Traditionally, gathering in-depth data from research participants has required researchers to schedule and conduct, a process which can often take multiple weeks to complete even for just a few participants.
AI-first studies on Wondering allow you to gather similar conversation-style transcripts from participants in just a few hours. Simply create the study you want by adding a block for each question you want to ask participants, and then use Wondering's AI generated follow-up questions to dig deeper into each response your participants give.
Using AI generated follow-up questions in your studies on Wondering make it possible to structure your studies similarly to how you would normally run a semi-structured user interview, but without you needing to moderate each conversation manually.
Want to learn more about how to use AI generated follow-up questions in your studies? Check out this guide.
How do I apply AI-first user interviewing in practice
AI-first research studies on Wondering can be used to gather similar conversational data that you collect through traditional user interviews, and can be sent to participants via a unique link, in-product or via our built-in panel.
This insights report from the Wondering research team showcases how you can use AI-first research studies to evaluate a new product concept (a new running app centred around social running) entirely using data gathered through data gathered from a study run on Wondering. In the study, 14 participants from a panel were AI-interviewed using Wondering, with each interview lasting between 30-45 minutes.
The team at Katkin, a quickly scaling UK-based subscription service for pet food, uses this method to scale their user interviewing with AI-first research studies. You can read more about how they do this here.