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Total: 6577

  1. article

    Big ideas, real-world solutions. Now in two locations!

    It has been a few months since the 2016 Quirk’s Event and we are excited to be planning not one but two events for 2017! We’ve been thinking about and planning for 2017 since we returned from Brooklyn in February. ...

  2. article

    Good enough for us? My family's flawed foray into research

    The first weekend in August, my family hosted the bi-annual reunion for my late maternal grandmother’s family. She was one of 14 siblings and many of them stayed close to the small Wisconsin town where they grew up. As I’m ...

  3. article

    Why DIY marketing research is good for our industry

    There is a lot of talk among marketing researchers that DIY research is bad for the industry. I, for one, am not convinced. I understand the fear among research suppliers that DIY will cut into their business. I also understand ...

  4. glossary

    Precision (lack of)

    If, in repeated sampling, the values obtained tend to be widely scattered or spread out (the results obtained from one sample usually cannot be duplicated with another sample) the sample has a lack of precision. Precise samples have low standard errors. Increasing the sample size often increases the precision. Lack of precision in marketing research refers to the degree to which results or measurements are inconsistent or imprecise. It suggests variability in data collection or analysis, which can reduce confidence in findings and limit their usefulness for decision-making. What are key aspects of precision (lack of) in marketing research? Results show high variability or inconsistency. May stem from poorly designed questions or samples. Impact reliability and replicability of findings. Often reflected in wide confidence intervals or standard errors. May be caused by respondent misunderstanding or bias. Can lead to misleading insights or poor strategic decisions. Why is precision (lack of) important in market research? Precision is critical for producing trustworthy and actionable insights. A lack of precision can result in misleading conclusions, weak correlations and flawed strategic recommendations – potentially costing businesses both money and credibility. Who relies on precision (lack of) in marketing research? Data analysts assessing model reliability. Survey designers aiming for clarity and consistency. Client-side researchers validating findings. Decision-makers relying on accurate forecasting. Academic and applied researchers ensuring rigor. QA teams checking methodological soundness. How do market researchers use precision (lack of)? Market researchers monitor and assess the precision of their data to ensure results are consistent and trustworthy. When a study lacks precision – due to ambiguous wording, poor sampling or uncontrolled variables – it becomes difficult to replicate or generalize findings. Researchers identify and correct these issues by improving question design, increasing sample size, refining data collection methods or applying statistical controls. Addressing a lack of precision is essential for boosting the reliability of insights and maintaining confidence among clients and stakeholders who rely on the data for strategic decisions.

  5. article

    Using photovoice to discover and tell stories with impact

    Photovoice is a methodology employed by qualitative research to gain insights about peoples’ thoughts, behaviors and emotions. Annie Levy explores one organization’s innovative use of photovoice and participatory communication to build a fundraising and engagement campaign.

  6. article

    10 tips to ensure engagement in online qualitative

    Editor’s note: Layla Shea is founder and chief insights officer at Upwords Marketing Solutions, a Victoria, British Columbia-based research firm. One of the objections some clients still have against asynchronous (not in real time) online qualitative research is that they ...

  7. article

    Designing a questionnaire that dives beneath the surface

    A well-designed questionnaire is critical to research success. This article discusses questionnaire design, including setting objectives, general considerations, wording questions, one question that should never be asked and why time and money should be spent designing an effective questionnaire.

  8. article

    Qualitative advertising communication checks: 10 rules to guarantee great creative choices

    In any marketing research career, you will be asked to participate in a qualitative advertising communication check, a process no one is particularly fond of. This article outlines 10 rules to guarantee great creative choices.

  9. glossary

    Probit Model

    A version of regression analysis, same as logit model except it uses a cumulative normal curve rather than a logistic one. A probit model is a type of regression used in marketing research to predict the probability of a binary outcome – such as purchase vs. no purchase – based on one or more independent variables. It assumes a normal cumulative distribution for the error term. What are key aspects of a probit model in marketing research? Used for modeling binary (yes/no) decisions. Based on the normal distribution curve. Estimates likelihood of an outcome based on predictors. Often compared to or used alongside logit models. Useful when decision data are not linearly related to predictors. Why are probit models important in market research? They allow researchers to understand and quantify the drivers behind binary consumer decisions – such as purchase intent, product adoption or brand choice – and to predict future behavior based on specific attributes or market stimuli. Who relies on probit models in marketing research? Data scientists and statisticians. Market modelers. Econometricians. Marketing analysts. Product teams testing concept or trial likelihood. How do market researchers use a probit model? Market researchers use probit models to analyze how variables such as price, advertising exposure, demographics or feature changes affect binary decisions like whether a consumer will try a product or not. For example, in a new product test, researchers might use a probit model to estimate the probability that a respondent will purchase the item based on their stated preferences, income level and exposure to marketing materials. The model helps quantify how sensitive consumers are to specific variables and provides a predictive framework for scenario planning and campaign optimization.

  10. sourcebook

    Fieldwork Webwork & Anywhere

    Fieldwork Webwork and Anywhere bring the experts and tools needed to leave behind the traditional facility setting, including hands-on technical support, one point of contact project management and Fieldwork-quality recruiting.

  11. article

    The Power of Packaging to Drive Sales Growth

    Abstract: Interested in moving forward (or not!) with added certainty about your pack performance? This month, Behaviorally introduced the PackPower Score™, one number that predicts the potential of packaging design to grow in-market sales.

  12. article

    Seven suggestions to help you hone your humility at work

    Larger-than-life egos are fast becoming liabilities. Indeed, in what may first appear to be a paradox, ego’s mortal enemy – humility – is one of the traits most likely to guarantee success in the 21st century workplace.