Web Survey Bibliography

Title Conversational Survey Frontends: How Can Chatbots Improve Online Surveys?
Year 2017
Access date 13.04.2017
Abstract

Relevance & Research Question:

Even though online chats have been around for a long time, the tremendous success of WhatsApp and Facebook messenger have fundamentally changed how people interact and exchange information. With the appearance of “intelligent”, machine-learning based chatbots we assume that the areas of application will become even more versatile which leads to the question how we can utilize chatbots for market research purposes.

Chatbots consist of two components: (a) the frontend for the user as the point of interaction and (b) a backend, often based on Natural Language Processing algorithms that handles the user requests and sends appropriate responses back to the user.

Focusing on the frontend, we wondered how a chat interface impacts answer behavior. We were especially curious to understand the effect on response rates, data quality and survey fatigue by engaging in a conversational manner.

Methods & Data:

We developed a Chatbot interface which delivers survey questions to the user. Our aim was to create a non-obstructive, responsive frontend that feels familiar to users of messenger services. A sample of 600 participants from a commercial online panel was randomly assigned to either a traditional online questionnaire or a Chatbot interface. Both questionnaires included exactly the same questions covering topics concerning media consumption and mobility, as well as questions on the perception of the questionnaire itself. Different answer types were presented to the respondent, such as open questions, Likert scales and Multiple Choice questions.

(The study was pre-registered at http://aspredicted.org/blind.php/?x=cb5c

Results:

Results will be available in early January 2017.

Added Value:

Chatbots as survey frontends do not only offer a new but familiar interface for respondents. They allow the integration within different contexts using developer APIs for Facebook Messenger or other messaging services. This allows to recruit and survey participants very easily without the need to redirect them to a separate questionnaire.

Thus, it is important to evaluate benefits and potential pitfalls gained from using such frontends. Especially, when future applications of chatbots in online surveys include AI capabilities to analyze responses and adapt questions in real-time.

Year of publication2017
Bibliographic typeConferences, workshops, tutorials, presentations
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