As an agency that specialises in chat and voice-based research, a key question we come across is when to use chat and when to use voice.
In this post we will outline what we see as the key benefits of chat-based research as compared to voice, as well as compared to more traditional research methodologies like surveys and focus groups.
- Chat or SMS is a familiar mode of communication. It is how many of us ask and answer questions when chatting with friends, talking to businesses and engaging in social media. It has a sense of immediacy, and it can feel fun rather than tedious.
- A chat-based survey can be launched seamlessly within a platform the user is already using via hyperlink. From an email, an SMS, a message in Facebook, Teams or almost any app or social media platform you can think of.
- Chat is visual – perfect for including scales, showing stimulus, ads, concepts ideas. Our ad tester chat survey plays video within the chat without allowing the respondent to skip ahead. We have also built in the ability to replay the ad if they have problems with sound.
- Chats are mobile optimised – perfect for in-the-moment feedback – particularly when paired with SMS and timed to be sent to coincide with key events.
- Unlike static surveys, our chats are powered by Artificial Intelligence. This means that when we design the conversation, we can borrow from survey design methods used in traditional quantitative research and more free-flowing discussion guides that we use in focus groups. We can anticipate how people will respond to each question and program the chat accordingly. For respondents this means that that it is more natural and conversational than other modes of research.
- Prior to AI, when we asked questions in an open text format, either in a survey or a group, depth interview or an online forum, a human would have to read through and make sense of the responses. It was a time-consuming, expensive and subjective process. Our AI powered reporting now makes analysing hundreds, thousands and even tens of thousands of open-ended responses a snap.
- While watching video we seek permission to access the participants’ camera to use another face tracking AI tool to read their emotional response to the stimulus. This not only allows us to infer how their emotions are impacted by the stimulus, it also allows us to estimate their age and gender. You can see what these outputs look like in the sample below. From this example we see that at the 22 second mark in the ad that there is a peak in happiness – a moment in the ad when a young child has a cuddle with a grandparent.
So in general if you have a visual component to what you are wanting to research and if you are confident that literacy is not an issue chat, is often the way to go. If you are wanting to ensure that no one is excluded on the basis of literacy, or if asking respondents to engage using their hands and eyes could be limiting, voice may be a better option. Voice also has a certain novelty value that could signal relevance to some hard-to-reach audiences. So if you can’t decide – why not provide both options? You can learn a bit more about the benefits of voice in this post.
Whilst we remain advocates of traditional forms of research like surveys, focus groups and online qual, we are truly excited by these innovations that have enabled us to use chat-based surveys to deliver conversational research at scale.
