The Marketing Analytics Accelerator – the only event focused exclusively on attribution, marketing mix models and the science of marketing performance measurement – returned for its ninth year on November 13. The industry’s boldest and brightest minds joined us in NYC to share their latest innovations and case studies that will improve your business outcomes.
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On November 7, the ARF Creative Council held an immersive event exploring the powerful role of sound in branding. At this event, the Council unveiled its thoroughly-researched white paper on sonic branding. Members of the Council provided a preview of the white paper. They covered what sonic branding is, how it has evolved, how it works at a neurological level, how leading brands have successfully used sound to build and reinforce brand memories, and how brands can get started on their sonic branding. Practitioners of sonic branding revealed how they go about creating sonic signatures and even played a possible sonic signature of the ARF. The event began with a quiz in which 10 audio clips were played and the audience was asked to identify the brand associated with each sound.
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This study explores the impact of using "containing language" in advertisements on perceived offer fairness and consumer behavior. Identifying useful phrases like "That's it!" and "Period!" can reduce perceived price complexity and enhance perceived offer fairness, leading to higher purchase intentions, the researchers conclude. These findings suggest that marketers can use such language to communicate prices more effectively and responsibly.
The study involved multiple experiments and a large-scale field study, demonstrating that containing language can positively influence consumer perceptions and responses. The research provides valuable insights for marketing practitioners on how to design advertisements that improve consumer trust and engagement.
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This study explores the identification of nonlinear and time-varying effects in marketing mix models (MMM). It highlights the challenges of conflation in model selection and proposes a framework for simulating and estimating these effects using Gaussian processes. The study emphasizes the importance of accurately identifying the underlying response to optimize marketing spending.
The research provides insights into the complexities of marketing effectiveness and offers practical solutions for improving model accuracy. By addressing the issue of conflation, the study aims to enhance the decision-making process in marketing strategies.
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