Driving the effort to close the widening industry “trust gap,” The ARF has launched its Research Quality Certification Program, created to raise the standards and increase the transparency of advertising and marketing studies. A key element of certification program includes making study data available for public review and reanalysis.
John Wanamaker’s quip “Half the money I spend on advertising is wasted; the trouble is don’t know which half” takes on new meaning with the measurement options available today. But which work best in quantifying the impact of marketing activities? The ARF’s Scott McDonald tackled the topic by providing tips on the best use of A/B tests vs. Market-Mix Models vs. Multi-Touch Attribution to measure marketing ROI.
When you hear claims on generational differences in media and market behavior, your first reaction should be: “Show me the data.” Two such claims—that younger cohorts do not care about privacy, and that they are averse to advertising—might be misinforming strategic marketing and advertising decisions, raising the distinction between longitudinal vs. attitudinal research.
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Popularity can come with a price. Although mobile survey research is increasingly popular, it often suffers from high drop-off rates. What can marketers and researchers do to reduce drop-off? This ARF-original Knowledge At Hand article identifies best practices to overcome the problem and improve mobile survey effectiveness.
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Flaws in data sampling accuracy and coverage can foil brands’ targeting efforts and ultimately their ROI, which bodes badly for advanced TV advertising. The culprits: crippling media fragmentation, and a dearth of research on missing and misidentifying consumers when using commercially available target segments for digital campaigns.
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Interested in AI best practices? Wish you had a succinct definition of what AI does? Curious about a simple visual that explains the ability of five different levels of AI to tackle tasks? Want to understand better how machine learning differs from deep AI-powered learning?
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Who doesn’t like less complex and less costly solutions, if similar results are achieved? This study claims to deliver on that goal by validating the single-item measurement approach (preferred by practitioners) vs. using multiple measures of attitudes (preferred by academics. It’s a welcome outcome in the current era of decreasing survey response rates and respondents’ attention spans.
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What four features does IBM Watson Ads believe must be satisfied for an effort to be considered AI? How is the company applying AI to produce conversational marketing? What steps can improve marketers’ use of AI?
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