8/3/2023 0 Comments Quant research![]() ![]() Unfortunately, in this survey, we don’t have an indication of exactly howrespondents were using analytics in their projects. 74% of respondents who reported using quantitative research at least once per project also reported using analytics “often” (86 out of 117).Īnalytics data can play a significant role in UX design. These results give some context to the surprisingly high frequency of quantitative studies in design projects. Predictably, the relatively lower-cost methodologies rank near the top (analytics, qualitative usability testing, interviews) while more expensive methodologies are towards the bottom (quantitative usability testing and eyetracking, which can be both prohibitively costly). The most frequently used methodologies, as reported by our respondents, were, in order: Analytics, qualitative usability testing, and interviews were tied for the most popular methodology, each with 67% of respondents reporting that they use it “Often” or “Sometimes.” These three were the only methods used by a majority of respondents, with everything else clocking in at 48% at the most. ![]() This stacked bar chart shows the proportion of respondents who reported using each methodology often or sometimes. For each methodology, respondents told us if they were using it “often,” “sometimes,” “rarely,” or “never.” We asked respondents to tell us how frequently their teams were using 11 popular UX research methodologies - 7 quantitative and 4 qualitative. We were somewhat surprised to hear that the majority of our respondents (71%) said they performed quantitative research either “sometimes” or “at least one study per project.” This result makes sense when we look at the methodologies that respondents report using. (Although, since you are reading this article, that likely means the results of this survey are probably fairly representative for the kinds of projects you work on, even though they may not be representative for all design projects in the world.) I’d bet that sample (and probably you, since you’re reading this) likely performs more quant research on average than the wider UX community as a whole. As a result, our sample consisted of NN/g-fan UX practitioners who potentially were interested or had heard of quantitative research methods. We also mentioned that the survey was about quant practices. We recruited our respondents from Twitter and LinkedIn outreach, and offered a chance at a free report or online seminar as an incentive. When interpreting these results, bear in mind that there may be some sample bias at play. The activities of the research team are in different fields including decision under risk and ambiguity, Financial markets and asset pricing, Real options/investment under uncertainty as well as the performance of machine learning models.The majority of respondents said their teams perform quant research at least occasionally: 44 % report doing it “sometimes” and 27% say they perform one or more quantitative studies per design project. Quantitative Finance covers all applications of quantitative methods to finance (mathematics, statistics, computational methods). The focus is on computational intelligence approaches and optimization methodologies tailored to specific practical applications such as finance, real economy, education, logistics/transportation, customer service, manpower planning or yield/revenue management. The research team performs basic and applied research for solving complex problems arising in Decision Systems. In particular, the research team aims at becoming a vehicle for corporate partnerships with the school, where collecting and using data become central dimensions in business strategy. But it is relevant to develop a forum where each of these specialties can meet and compare their approach to develop transversal methods and projects, and possibly a common vision. ![]() Each of the functions of a business, from finance to HR, can study these challenges from their own viewpoint. ![]() “Data” as a subject introduces major economic, cultural and social challenges, from new business models to the protection of personal data. ![]()
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