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Sharing economy, cloud computing, AR in smartphones, AI in smart homes. But what is the next step to make market research "Smart"? Nowadays a consumer expects, rather than seeks, a direct dialogue with a brand through direct channels where they can share thoughts and experiences. We believe we must stop looking for respondents and stop looking for people driven by the reward intent. We must look for opinions and intentions in an authentic and transparent way. At the ESOMAR Congress 2019 we demonstrated that 70% of smart speaker owners in the US are willing to be interviewed by Alexa without a reward. But would they join a panel? We ran an experiment to find out. Join us and be inspired!
Join Zontziry 'Z' Johnson of Zappi for a presentation on the market research process and how it drives business decisions. Theoretically, market research is a core set of steps that works in conjunction with the rest of an organization's efforts to drive business decisions using data. Realistically, that's not always how it happens. Or is it? In this webinar, Zontziry will cover the following topics:- Reviewing the ideal market research process- Customer input as a source of data- Feeding business decisions - Theory vs. reality
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
This workshop challenges you to imagine and realise the 'Survey of the Future'. With the tools of research shifting, we want to help you re-evaluate how you conduct survey research, and put the learning to the test in real-time with real research.
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.
Machine learning is a concept that has long been applied to many industries that need to use predictive data, and has been used for some time in the online advertising industry. The survey research industry is ideally suited to benefit from machine learning for many reasons. The most pressing of which is to lessen respondent burden. Well share the success weve had by applying machine-based learning, and explore other ways we can gather data to improve insight generation including permission-based digital tracking, all with an eye on improving insight and removing the reliance on respondents.
How healthy is your survey? Are all the questions in your survey working efficiently? Is your survey performing above or below benchmark standards? In this session Steve Wigmore and Alex Wheatley will discuss 10 diagnostic techniques which everybody in research can undertake to check the health of their surveys and give some tips on better ways to ask questions, resolve common data problems and improve the performance of their surveys.