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Leveraging AI to reducing survey fatigue and survey send outs while maintaining stable customer satisfaction scores and enhanced response rates.3 takeaways:- How AI can be used to multiply stability of CX scores for a certain area or segment;- Why CX score can be reported for some area or segments EVEN without measuring them- How AI can select those customers most responsive to surveying and scale down email outreach
The plummeting of response rates figures is a very well-known issue in the Market Research industry. While the possible ways to deal with this issue are plentiful, an unavoidable candidate is engagement, in particular among Millennials. We test the use of two innovative technologies in the field of Artificial Intelligence in order to improve survey engagement: Google Vision API for classifying images and a speech recognition tool to convert voice input to text. The results of both studies are positive and draw a promising landscape for further research.
In today's fast-paced digital world time is precious, speed is of the essence and attention spans are short - yet expectations of market research have never been greater. This is why we have to adjust, challenge existing norms and come up with entirely new ways of doing research. To uncover how today's consumers truly think and behave we need to connect with them in the same way they connect with the world around them. This means that new research methods will have to place mobile technology at their core, replace overly rational questions with fast-paced intuitive exercises and entertain rather than bore people. This paper shows how combining implicit research techniques with an engaging mobile interface can do exactly that. More specifically, by using intuitive swiping and tapping exercises that trigger more instinctive responses and incorporating reaction time as an implicit measure, response biases prominent in Asian cultures can be reduced and true preferences uncovered.
In today's fast-paced digital world time is precious, speed is of the essence and attention spans are short - yet expectations of market research have never been greater. This is why we have to adjust, challenge existing norms and come up with entirely new ways of doing research. To uncover how today's consumers truly think and behave we need to connect with them in the same way they connect with the world around them. This means that new research methods will have to place mobile technology at their core, replace overly rational questions with fast-paced intuitive exercises and entertain rather than bore people. This paper shows how combining implicit research techniques with an engaging mobile interface can do exactly that. More specifically, by using intuitive swiping and tapping exercises that trigger more instinctive responses and incorporating reaction time as an implicit measure, response biases prominent in Asian cultures can be reduced and true preferences uncovered.
Strategies on how to best balance expanding survey length with the need for concise, relevant and engaging surveys is explored in this paper. Innovative ways to shorten survey length without compromising the amount of business decisions that can be unearthed and accurately researched from online surveys are reviewed. The overall goal is to explore how adapting survey research improves rather than complicates the lives of both researchers and research participants. If we are not able to shorten our surveys, then survey modularisation is certainly a proven approach that can be adopted to deliver a complete, representative data set. It will also achieve accuracy and data consistency both confidently and efficiently at scale.
Ascription is a data science method which we have adopted to cut long questionnaires for mobile surveys, shorten the length and decrease the cost of large tracking desktop surveys. Using proprietary mathematical and statistical algorithms, responses are accurately ascribed to some respondents based on the overall data of the studied population, and without the need for the respondents to go through the entire survey. A secondary benefit comes in the form of cutting costs by shortening the surveys for some respondent segments, survey length and data collection are greatly optimised.
Ascription is a data science method which we have adopted to cut long questionnaires for mobile surveys, shorten the length and decrease the cost of large tracking desktop surveys. Using proprietary mathematical and statistical algorithms, responses are accurately ascribed to some respondents based on the overall data of the studied population, and without the need for the respondents to go through the entire survey. A secondary benefit comes in the form of cutting costs by shortening the surveys for some respondent segments, survey length and data collection are greatly optimised.