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This episode of Now that's Significant features host Michael Howard, Head of Marketing at Infotools and Jo Secher, a freelance researcher.
Amidst the rise of misinformation (in this case that which is more unintentional than intentional), Jo joined the show to discuss the challenges of interpreting quantitative data and the role of researchers in distinguishing fact from fiction.
1. Misinterpretation of Quantitative Data: Jo highlights how quantitative data is often misinterpreted by staff in non-research roles, which can lead to significant errors in decision-making.
2. The Rise of Misinformation: The conversation explores the increasing difficulty in distinguishing fact from fiction and the responsibility researchers have in acting as credible fact-checkers.
3. Professional Ethics in Research: Jo emphasizes the importance of maintaining ethical standards in research to preserve trust in the market research profession.
4. Understanding Probabilistic Data: The discussion covers the need for researchers to communicate the inherent uncertainties in data to avoid misinterpretation by stakeholders.
5. Examples of Misinterpreted Data: Jo shares real-world examples where data misinterpretation led to strategic errors, underlining the importance of presenting data in an accessible manner.
Question of the episode that you can consider… How can your organization improve its processes to ensure that data insights are accurately interpreted and effectively communicated to decision-makers?
Thank you for tuning into this episode of 'Now that's Significant.' If you found this discussion valuable, please share it with others, subscribe to the podcast, and leave a review. Listen to our other episodes for more insights into market research.
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Infotools Harmoni is a fit-for-purpose market research analysis, visualization, and reporting platform that gives the world’s leading brands the tools they need to better understand their consumers, customers, organization, and market.
www.infotools.com
Established in 1990, we work with some of the world’s top brands around the world, including Coca-Cola, Orange, Samsung, and Mondelēz.
Our powerful cloud-based platform, Harmoni, is purpose-built for market research. From data processing to investigation, dashboards to collaboration, Harmoni is a true "data-to-decision-making" solution for in-house corporate insights teams and agencies.
While we don't facilitate market research surveys, provide sample, or collect data, we make it easy for market researchers to find and share compelling insights that go over-and-above what stakeholders want, inspiring them to act decisively.
One of the most powerful features of Harmoni is Discover, a time-tested, time-saving, and investigative approach to data analysis. Using automated analyses to reveal patterns and trends, Discover minimizes potential research bias by removing the need for requesting and manually analyzing scores of cumbersome crosstabs – often seeing what you can’t.
Discover helps you easily find what differentiates groups that matter to you, uncover what makes them unique, and deliver data points that are interesting, relevant, and statistically significant, plus see things others can’t. Add to all this an impending GenAI feature, and you have an extremely powerful, future-proofed tool.
This episode of Now that's Significant features host Michael Howard, Head of Marketing at Infotools and Jo Secher, a freelance researcher.
Amidst the rise of misinformation (in this case that which is more unintentional than intentional), Jo joined the show to discuss the challenges of interpreting quantitative data and the role of researchers in distinguishing fact from fiction.
1. Misinterpretation of Quantitative Data: Jo highlights how quantitative data is often misinterpreted by staff in non-research roles, which can lead to significant errors in decision-making.
2. The Rise of Misinformation: The conversation explores the increasing difficulty in distinguishing fact from fiction and the responsibility researchers have in acting as credible fact-checkers.
3. Professional Ethics in Research: Jo emphasizes the importance of maintaining ethical standards in research to preserve trust in the market research profession.
4. Understanding Probabilistic Data: The discussion covers the need for researchers to communicate the inherent uncertainties in data to avoid misinterpretation by stakeholders.
5. Examples of Misinterpreted Data: Jo shares real-world examples where data misinterpretation led to strategic errors, underlining the importance of presenting data in an accessible manner.
Question of the episode that you can consider… How can your organization improve its processes to ensure that data insights are accurately interpreted and effectively communicated to decision-makers?
Thank you for tuning into this episode of 'Now that's Significant.' If you found this discussion valuable, please share it with others, subscribe to the podcast, and leave a review. Listen to our other episodes for more insights into market research.
***
Infotools Harmoni is a fit-for-purpose market research analysis, visualization, and reporting platform that gives the world’s leading brands the tools they need to better understand their consumers, customers, organization, and market.
www.infotools.com
Established in 1990, we work with some of the world’s top brands around the world, including Coca-Cola, Orange, Samsung, and Mondelēz.
Our powerful cloud-based platform, Harmoni, is purpose-built for market research. From data processing to investigation, dashboards to collaboration, Harmoni is a true "data-to-decision-making" solution for in-house corporate insights teams and agencies.
While we don't facilitate market research surveys, provide sample, or collect data, we make it easy for market researchers to find and share compelling insights that go over-and-above what stakeholders want, inspiring them to act decisively.
One of the most powerful features of Harmoni is Discover, a time-tested, time-saving, and investigative approach to data analysis. Using automated analyses to reveal patterns and trends, Discover minimizes potential research bias by removing the need for requesting and manually analyzing scores of cumbersome crosstabs – often seeing what you can’t.
Discover helps you easily find what differentiates groups that matter to you, uncover what makes them unique, and deliver data points that are interesting, relevant, and statistically significant, plus see things others can’t. Add to all this an impending GenAI feature, and you have an extremely powerful, future-proofed tool.