Devendra Chandani

The definitions of qual and quant are getting blurred with new AI capabilities as is clear with our new AI moderated video feature in Upsiide, by Dig Insights. But this confusion over definitions of quant and qual isn’t a new phenomenon. Social scientists and statisticians (my undergrad) use the terms quantitative vs. qualitative data to refer to continuous vs. discrete data in a model. For example, if you have a “qualitative” dependent variable, then you’d run a logistic vs. linear regression. In market research (my industry), qual typically means unstructured data (e.g., interviews/text) and quant means structured data, usually survey data. But other data heavy industries sometimes refer to surveys as qual because they're stated opinions and behaviors, not data on what actually happened. To some people, quant means behavioral data (e.g., purchases at store). And in the future, our data capabilities may increase by another step change. We could have real-time data ingestion using computer vision techniques to quantify almost anything, such as how many people are wearing a specific brand of shoes in a specific city. The AI is already capable, but it’s a complex issue in terms of data privacy and security. If that does come to fruition, then maybe the goal posts shift again and current behavioral quant data becomes “qual” and real-time data is the new gold standard “quant”?

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Join us for our next KEYS webinar as we share findings from our new Ipsos Generations Report and discuss how businesses can foster genuine connections with diverse generational groups and take the right steps to prepare for tomorrow’s population realities. https://lnkd.in/g-bFnr4g

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Toluna continues to innovate with AI, creating more robust insights faster, allowing more time to "action" for success! Reach out to learn more, and get ahead of the competition while better understanding consumers to drive their satisfaction and your growth! #AIInnovation #DeeperInsights #Action4Success"

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This article by Nikhil Goel from Ipsos MMA (Marketing Management Analytics) outlines six best practices for evaluating and selecting a world-class marketing mix modeling partner. It emphasizes the importance of high-quality data, benchmarks, expert domain knowledge, and techniques aligned with business objectives to drive adoption and value creation. https://lnkd.in/eVevHj8Q

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Losing survey respondent interest early on can have serious consequences, impacting the quality of responses. One of the worst things a market researcher can do is bore a survey taker, potentially leading to false conclusions. To keep them engaged, consider these tips: - Inform them of the number of questions upfront - Maintain a format that is straightforward but not overly simplistic (avoid true/false & yes/no) - Share the results with them; everyone appreciates seeing their POV! Remember, if you offer an incentive, clearly tell them! Keeping respondents engaged is key to obtaining valuable insights. #MarketResearch #SurveyTips

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AI generated synthetic data can help us avoid or reduce the impact of bad respondent / bots. So how big of an issue is bad data? It depends on your study type. Let's take a look at a few examples. 1. Low incidence studies have higher proportions of bad respondents. If you answer randomly, you are more likely to randomly select than you own a helicopter than a good faith respondent (also, sometimes they can detect the screening intentions of the survey writer). We recently implemented a new smart machine learning method of automatic bad respondent detection (very proud of this! Might have to make a whole post on it). In short, it detects self consistency patterns across responses to multiple questions and gives a quality score. We found that in a high incidence study, there actually were much fewer bad respondents than with other low incidence studies. 2. Virtual shopping studies (e.g., conjoint, shelf tests) are significantly impacted by bad respondents. If you answer randomly, by definition, you don't make selections based on price. To the underlying mathematical model, this doesn't randomly affect the betas, it specifically targets the pricing coefficient to suppress it. If ignored, this leads to simulators with very low price elasticity (of course, some categories are legitimately low price elasticity). 3. Segmentation studies are also impacted in a specific way. Bad respondents aren't internally consistent so they usually cluster together near the origin in multidimensional space (see pink group in the image below in 2d space). If bad data are not removed, this group sometimes appears to be very weird, over indexing on low incidence stuff and under indexing on high incidence stuff. If you also have a low incidence product, they'll appear very interested and you have a sinister combination! This isn't a doomsday scenario. Bad respondents aren't impossible to deal with if you know how they manifest. But we are still working on high quality AI generated synthetic data solutions to improve results further. 

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PersonaBots - fueled by robust research and insights - are an engaging way to bring a segment or target to life for your team and stakeholders. Let us know if you'd like to explore a PersonaBot on your next project!

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With Nielsen’s integration of big data into our audience measurement (already happening for national and launching local in January), this article really helps explain why our viewership methodology (panel + big data) is the most reliable in the marketplace. As media consumption has evolved, so have we! A great read - shout with any questions! #nielsensports #data #TV

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Sharing some thoughts on my book #nonlinear which discusses the potential of #genai to usher in #digital #renaissance and how Ipsos is rapidly adopting #genai

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🔥 What is the reach of #AI in the lives of #IndianConsumers and its implications for marketing? Our research suggests that 724 Million Indians are exposed to AI and its features. Kantar has an unprecedented access to consumer trends in the digital space using ICUBE and Target Group Index (TGI) studies across urban and rural India to help you fine tune your AI based #BrandBuilding efforts: -Know the reach of AI features -Understand the profile of AI feature users -Discover the categories and brand usership -Learn the consumer psychographics and lifestyles Explore more: https://lnkd.in/edzfupEf Stay tuned as we continue to share some of the most incredible AI-infused Kantar solutions to today's marketing challenges in the series, "Reimagining brand building in the AI era". Puneet Avasthi, Biswapriya Bhattacharjee, Deepender Rana

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𝗔 𝗻𝘂𝗮𝗻𝗰𝗲𝗱 𝗖𝗣𝗚 𝗰𝗮𝘁𝗲𝗴𝗼𝗿𝘆 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗳𝗼𝗿 𝟮𝟬𝟮𝟱 𝗶𝗻 𝘁𝗵𝗲 𝘁𝗼𝗽 𝟲 𝗘𝘂𝗿𝗲𝗼𝗽𝗲𝗮𝗻 𝗴𝗿𝗼𝗰𝗲𝗿𝘆 𝗺𝗮𝗿𝗸𝗲𝘁𝘀 based on 6 factors; in the final issue of the 2024 Demand Signals* Category Monitor: 💰 𝗜𝗻𝗳𝗹𝗮𝘁𝗶𝗼𝗻 𝘀𝗲𝘁 𝘁𝗼 𝗿𝗶𝘀𝗲 𝘁𝗼 𝟮.𝟳% 𝗯𝘆 𝗲𝗻𝗱 𝗼𝗳 𝗛𝟭 𝟮𝟬𝟮𝟱; COL crisis continues 🥈 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝘃𝗼𝗹𝘂𝗺𝗲 𝗴𝗿𝗼𝘄𝘁𝗵 𝗶𝘀 𝘁𝗵𝗲 𝗰𝗿𝘂𝗰𝗶𝗮𝗹 𝘁𝗵𝗲𝗺𝗲 as demand slows 🌟 𝗣𝗿𝗼𝗺𝗼𝘁𝗶𝗼𝗻𝘀 𝗮𝘁 𝗮 𝟱-𝘆𝗲𝗮𝗿 𝗵𝗶𝗴𝗵 𝘄𝗶𝗹𝗹 𝗻𝗼𝘁 𝗰𝗿𝗲𝗮𝘁𝗲 𝗼𝗿𝗴𝗮𝗻𝗶𝗰 𝗱𝗲𝗺𝗮𝗻𝗱 - so brand over-saturating shelves must look to the whole toolbox 🏪 𝗣𝗿𝗶𝘃𝗮𝘁𝗲 𝗟𝗮𝗯𝗲𝗹𝘀 𝘄𝗶𝗹𝗹 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗲 𝘁𝗼 𝗴𝗿𝗼𝘄 𝘆𝗲𝘁 𝗮𝘁 𝗮 𝘀𝗹𝗼𝘄𝗲𝗿 𝗿𝗮𝘁𝗲 despite retailer transformation strategies 🛒 𝗗𝗶𝘀𝗰𝗼𝘂𝗻𝘁𝗲𝗿𝘀 𝗴𝗿𝗼𝘄𝘁𝗵 𝘁𝗼 𝘀𝘁𝗮𝗹𝗹 as Supermarkets fight back comprehensively 💡 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 - 𝗯𝗲𝘆𝗼𝗻𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 - 𝗵𝗮𝘀 𝘂𝗻𝘁𝗮𝗽𝗽𝗲𝗱 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 - to include Media & Promotion Effectiveness & Execution We may have got 6/6 predictions right for 2024. But we are not bringing out the champagne just yet! Happy Holidays to you from Circana

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Start 2025 a step ahead by curating existing data into insights to guide your projects. Let us know if we can help! Robyn Clayton

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Quality Data: 3 Steps to Data Excellence in Market Research 🚀 👉 AI is only as effective as the data it's built on. To unlock the true potential of AI for market research, prioritizing data quality is paramount. 📈 Here are 3 key takeaways for achieving data excellence: 🔎 Embrace a Centralized System: Fragmented data residing in silos hinders effective analysis. Integrating an Insight Management System (IMS) can unify your data, eliminate inconsistencies, and provide a single source of truth. 🔎Improve Data Quality and Processing: Poor data quality is a major roadblock to scaling analytics and AI initiatives. Help improve data quality by providing tools for cleaning, validating, and standardizing data. This leads to more reliable insights and better decision-making. 🔎Democratize Access to High-Quality Data: Empowering users across departments with easy access to reliable data fosters a data-driven culture. Focus on data democratization by providing intuitive dashboards and reporting tools, enabling users to extract valuable insights without relying solely on data specialists. You don't have to navigate this journey alone. 🦸 Implementing tools as IMS is a natural step towards achieving these goals, providing a robust framework for data management, analysis, and informed decision-making. #AI #dataquality #marketresearch #dataexcellence #insightmanagement #datadriven #techinnovation #businessintelligence

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Ipsos in India CEO Amit Adarkar in conversation with ET Edge Insights.   Join Ipsos India CEO, Amit Adarkar, as he delves into the future of insights and the transformative power of #generative AI.    Discover how #Ipsos is using this cutting-edge technology is being used to enhance efficiency, connect the dots between diverse data sources, and elevate the quality of #insights.    Amit also emphasizes the importance of human expertise alongside #AI, ensuring the insights #industry retains its vital human touch. Geeta Ravindranath Lobo, Parijat Chakraborty, Jyoti Susarla Malladi, Ashwini Sirsikar, Vivek Gupta, Rinku Patnaik, Krishnendu Dutta, Sakina Pittalwala, Geetika Singh, Balaji Pandiaraj, Gauri Pathak, Madhurima Bhatia, Pallavi Mathur Lal, Neetu Bansal, Reema Notani

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On CX day, let's acknowledge the impact of prioritizing customer experience on creating positive customer interactions, fueling business growth, and cultivating a vibrant work atmosphere. Share your strategies for enhancing CX within your organization and explore the Ipsos Global Trends to uncover the macro forces shaping our world today. https://lnkd.in/geHG_ERz #CXDay #CustomerExperience #Ipsos #Globaltrends

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Ever wonder why some brands can charge a premium while others get commoditized? Our new Blueprint for Brand Growth report sheds light on just that. Our analysis of 6.5 billion attitudinal and shopper data points found that brands that reach “meaningfully different” status, addressing a spectrum of practical and emotional needs in unique ways that competitors don't, have much greater pricing power, higher brand equity and much faster growth. Learn more about how brands can extend their identity and become more differentiated in this @MediaPost article: https://lnkd.in/gHRSmHgw

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Feeling uncertain about AI's role in marketing? Merkle's blog addresses common misconceptions and reveals how AI can enhance your strategies, helping you connect more effectively with your audience: https://bit.ly/48yaA9s

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Revisit our webinar for inspirational stories of clients leveraging our best-in-class generative AI research solutions. Hear how L'Oréal, Orange and Nestlé Purina used Ipsos' Gen AI solutions to unlock data and nuanced insights that are highly actionable. https://lnkd.in/eav5-6n5

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