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Total: 6577

  1. article

    When is the best time to introduce a brand in a commercial?

    Four different theories on when to introduce a brand in a TV ad are explored, including examples of the best situations in which to use each approach and each one's strengths and weaknesses.

  2. article

    Predicting the sales effectiveness of advertising

    While advertisers pay amazing amounts of money on Super Bowl advertising, most advertisers have no idea if their commercials will be sales effective. This article discusses Advertising Research System, one firm's basic system for predicting the sales effectiveness of advertising.

  3. article

    Money isn't everything

    This article reports on the second phase of an ongoing research project about respondent motivation for participating in research, especially focus group sessions. The study used two focus groups, one paid and one unpaid, to explore this issue in more depth than in Phase 1 of the study. (Phase 1 was the subject of a May 1990 Quirk's article. A follow-up was published in the June 1992 issue.)

  4. article

    Best practices for shop-alongs

    Editor’s note: Michael Carlon is vice president in the New York office of Truth Consulting, a London research firm. Carlon will outline his views on rethinking the shopper insights function in the June issue of Quirk’s. One of the most ...

  5. article

    Insights in Action: Ethnography sharpens Gillette razor launch in India

    Just wanted to bring to your attention a great long-form piece by the AP’s Mae Anderson on Procter & Gamble’s adventures in ethnography as it determined how to sell its Gillette razors in India. The article offers, as one quoted ...

  6. article

    Trade Talk: Using stories to make sense of scanner data

    One study attempts to answer four questions: How are product managers using scanner data? How does the analysis of the data help them learn about changes in their marketing environment? How does this learning affect their decisions on pricing, promotion design and new product evaluation? How does the data affect their relationship with customers and fellow employees (salespeople)?

  7. article

    In 2012, will social media data analysis still give us fits?

    We’re getting ready to field our annual researcher salary survey and so I’ve been rereading some of the output from the 2011 study. One of the goals of this blog will be to give readers some tips and guidance on ...

  8. article

    Trade Talk: Study examines ad likability

    In conjunction with the advertising research issue, Quirk's Editor Joseph Rydholm contacted the folks at PhaseOne, a Beverly Hills research firm, for an update on their research into likability in advertising. Rather than edit the material and attach it to one of the ad research-related articles in this issue as a sidebar, it is published here in its entirety.

  9. article

    The importance of data quality in advertising decision-making

    In these harsh economic times, advertisers must put an emphasis on quality, both in terms of seeking to obtain high-quality data and also in making sure that the ad research they conduct adheres to high quality standards. The article outlines one research company’s multi-step guidelines for conducting quality-focused ad research.

  10. glossary

    Multicollinearity

    A problem that arises when at least one of the independent variables in a linear combination is in effect always a weighted sum of the values of the other independent variables. When this occurs, we are unable to separate its influence on the dependent variable from that of the others. In market research, multicollinearity occurs when two or more independent variables in a regression model are highly correlated, meaning they share similar information. This makes it challenging to determine the individual impact of each variable on the dependent variable, as their effects are intertwined. Who relies on multicollinearity in market research? Data analysts, statisticians, market researchers and econometricians rely on understanding and addressing multicollinearity when building predictive models. It is particularly important for researchers conducting regression analysis to ensure accurate interpretation of variable effects. What are key aspects of multicollinearity in market research? Key aspects include: High correlation between variables: Indicates that independent variables may provide overlapping information. Impact on regression coefficients: Makes it difficult to interpret the unique contribution of each variable. Variance inflation factor: A common measure used to detect multicollinearity. Model instability: Can lead to large variances in regression coefficients. Potential solutions: Techniques like removing variables, combining variables or using regularization methods can address multicollinearity. Why is multicollinearity important in market research? Multicollinearity is important because it can distort the results of regression analysis, leading to unreliable estimates and misleading interpretations. By identifying and addressing multicollinearity, researchers can ensure their models accurately reflect the influence of each variable, improving the reliability of insights for decision-making. How do market researchers use multicollinearity? Market researchers use techniques like the variance inflation factor to detect multicollinearity in their models. When multicollinearity is identified, researchers may remove or combine correlated variables or apply advanced statistical techniques to reduce its impact. This helps produce more accurate and interpretable models for forecasting, segmentation and decision-making.

  11. article

    Measuring retail signage saturation

    The body of retail research data has a gap regarding one key element of in-store signage: saturation. This article details signage saturation analysis, a research method that allows a retailer to systematically assess the current level of signage saturation and its effect on customers’ identification and interpretation of key messages.

  12. article

    Testing product names

    Name function tests aren’t really about names but the effect of the name on the consumer’s expectations of the product. This article—an excerpt from a chapter in the book Making Names—discusses using adjectival analysis to compare consumers’ expectations of a product with one name versus expectations of the same product with another name.