An insights platform is seen by many industry leaders as an enabler to becoming insights-driven, step-by-step. In this webinar, we?ll explain everything you need to know about insights platforms ? how they help you to find insights, engage the business, drive intelligence and research new insights.Leading brands like Colgate-Palmolive, Mondelez and Prudential, who have successfully deployed platforms to become insights-driven, are reporting big gains on two fronts ? efficiency and effectiveness. When they equip their businesses to self-service answers to questions, they save stakeholders as much as one day a week searching for information, while experts use their time to advise the business with insights for winning decisions. For example, 80% of success factors in innovation are insight-related (Greenbook) while evidence-driven advertising delivers twice the growth (McKinsey).Join this webinar to learn why becoming insights-driven is a journey with an insights platform:- Start your journey by equipping business managers to find insights that answer their questions- Take the next step with a digital workspace where experts use their insights asset to advise the business, drive intelligence and engage stakeholders- Close the loop by researching new insights on the same platformIn the session, you will also learn from best practices and see how you can measure business impact. Register now to ensure your team is ahead of the curve in 2021.
From ethnography to rapid ethnography to insights sprints, it seems like there is a constant request for faster results. How can we tackle this without compromising the essence of user-centered design? Quick Qual Manifesto aims to explain how.
From ethnography to rapid ethnography to insights sprints, it seems like there is a constant request for faster results. How can we tackle this without compromising the essence of user-centered design? Quick Qual Manifesto aims to explain how.
Gary Ellis, COO and co-Founder of Remesh, in this piece outlines key advantages of AI in market research resulting from work with a number of organisations facing the challenge if transitioning from traditional market research to modern representative intelligence; intelligence capable of engaging, understanding and authentically representing massive groups of stakeholders (customer, employees, citizens, etc.). Readers will learn how new capabilities in market research, such AI-powered tools, enable researchers to combine quantitative methods with qualitative research. Furthermore, the piece will deliver a better understanding of how AI can deliver insights in a digestible format in real time, uncover hidden truths and increase efficiency within and among organisations.
Gary Ellis, COO and co-Founder of Remesh, will delve into the importance of AI in market research, and how it is a valuable tool for drawing qualitative insights on a massive scale to better understand the masses and bring market research into the 21st century.
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.
This paper demonstrates through a case one way to integrate traditional inferential research based on random sampling with the more recent online research based on (self-selected) panels, thereby making use of the strengths of both approaches. The focus of the case is segmentation research, but the principles should be applicable to other areas as well.
In business and marketing, qualitative research is needed but rarely accepted. Data from focus group discussions, case histories or interviews requires qualitative analysis if the researcher is to discover new meanings in accounts or interpret discussions of issues or topics. Qualitative methods are, however, widely seen as entailing inefficient and time consuming data management, analysis processes that lack rigor, and reports that are unpersuasive. Early qualitative computing programs failed to solve these problems of time, rigor and credibility. New computing tools, however, deliver speed, efficiency, integration of qualitative and quantitative data, rigorous and sensitive analysis, and rich presentation of results.
This paper focuses on efficiency, advertising investment efficiency, and of course, the most important theme, efficiency measuring. Measuring and efficiency, or efficiency measuring and efficiency - it is the same, because we will not know if we are efficient in our advertising investments until we measure. There are two messages: first, efficiency can be measured. This is not just a utopia in Spain and in other markets. The second message is that in order to make use of technology that supplies us with accurate measuring, we must change the relationship between advertisers, agencies and media centrals.
Let us just think about the specificity of services : how to manage, and how to implement a much more efficient marketing and strategy for a service company.