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Research & Data Quality

Are Marketers Using the Right Metrics?

  • MSI

Which is more efficient when it comes to advantageous decision outcomes, marketing-mix metrics or financial metrics? Researchers in this award-winning MSI working paper investigated this question, basing their research on a behavioral framework and statistical model. On average, according to their sample, marketing-mix metrics are more effective than financial. Even so, managers seem more eager to use financial metrics, possibly, because they are easier to understand across the organization.

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The ARF Supports ANA’s Raising 2020 Census Concerns

Troubling. Bias. Distortion. Why would the ANA use these words in a letter to the U.S. Government expressing concern about the impact of the 2020 Census on marketing quality? Learn about what led them to act, why the ARF supports them, and possibly join them in sharing your views before the feedback period ends on August 7, 2018.

Why Re-Testing “Truths” Is Good Practice

  • Marla B. Royne, Great Oaks Foundation professor of marketing and chair at the U. of Memphis Fogelman College of Business & Economics Dept of Market & Supply Chain Mgt.
  • JOURNAL OF ADVERTISING RESEARCH

Should the marketing community support repeating a study, when so much value is placed on new research? The answer may be a resounding “Yes.” Learn why repeating a study matters, especially when marketers seek transparency and data-based support for recommendations — and how advertising research might need to change.

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In the Age of the ‘Modeled’ Sample: Can We Still Trust Polling?

  • Mark Blumenthal – Head of Election Polling, SurveyMonkey

The 2016 U.S. presidential election served a big blow to the polling community, as pre-election predictions proved to be dramatically wrong. But is there really a crisis in pre-election polling? Mark Blumenthal, Head of Election Polling at SurveyMonkey, summarizes the AAPOR’s post-election investigation that demonstrated the accuracy of national polls, but weaknesses in state-level polls. Part of the challenge going forward – correcting for sample bias in an age of lower survey response rates.

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Deriving Social Insights by Mining Meta Data

  • Preriit Souda, Consultant, Data Science & Strategic Insights, Independent

How sad to get only a fraction of the available insights from social media! You can change that by using a new approach to link a range of data related to social posts, thereby generating more information about your followers’ attitudes, behaviors, and experiences.

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Validating Programmatic Audiences

  • Laura Lewellyn – Senior Director, Market Innovation, Lotame; Jim Warner – CTO, Survata

With so much 3rd party data available, how do you know how well that data represents your intended consumer target? Lotame and Survata partnered to link 1st and 3rd party data and boosted accuracy rates for identifying auto intenders on a publisher’s website by nearly 1/3rd.

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Making Mobile Listening More Insightful

  • Dave Vannette
  • Qualtrics

As more consumers respond to surveys on smartphones, fewer are completing them. That trend puts the representativeness of your sample at risk. Qualtrics has developed six best practices to optimize mobile survey design and thereby minimizing the respondent burden and maximizing your data quality.

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