On July 26, measurement practitioners discussed how to adapt to this new era of privacy with tools for measuring ad performance effectiveness. Panelists explored new considerations for existing methods, such as marketing mix modeling (MMMs) and multi-touch attribution (MTAs), and discussed the pros and cons of various privacy enhancing technologies (PETs), including multi-party computation, clean rooms, and more.
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Is there a better way to measure the digital behavior of consumers considering a complex or expensive purchase and improve outcomes going forward? Measurement company Arrivalist shared techniques they have used successfully, illustrated with six case studies. Their work has application for both considered and impulse purchase brands.
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To improve data quality, the marketing and advertising industry could establish a “Principles of Data Quality” disclosure; create a roster of items to ask of data suppliers; request transparency—data firm disclosures—including consumer authentication procedures, multiple data source descriptions, model target techniques and testing results, recency of data, integration techniques, data labeling, and top-line descriptions for all of the above; create best practice standards.
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Using data to microtarget messages to Chobani customers produced a positive sales impact, according to this case study. The authors show how loyalty card data, linked to household address and then to a digital address was used to identify key audience segments to whom messages were specifically directed – with implications for future efforts.
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