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effectiveness

KaH: Elements of a Successful Brand Purpose Campaign

Defining what makes purpose-driven marketing campaigns successful has historically been more art than science. In an effort to shift the balance squarely back in favor of science, the ARF and Kantar have introduced Cracking Brand
Purpose, a study that identifies the elements that create leading purpose-driven campaigns and provides a best-in-class framework to shape, guide and evaluate future campaigns.  Read more.

CMO Brief: Elements of a Successful Brand Purpose Campaign

What do we really know about a purpose campaign? We know that eliciting an emotional response and sustainability are strategies that can deliver greater brand strength and appeal. Beyond that, there’s little else. So little, in fact that the industry hasn’t even agreed on how to properly define a purpose campaign.

The ARF and Kantar set out to uncover those defining characteristics. The result is Cracking Brand Purpose, a study completed in late 2019 that establishes a best-inclass framework that can be used to inspire, develop and evaluate purpose campaigns.  Read more.

CMO Brief: 2019 Organizational Benchmark Survey, The Advertiser Report

Advertising and market research have seen significant changes in the last couple of years. ARF members have been inquiring about different aspects of these changes. To answer their questions, the ARF Analytics Council developed the very first Organizational Benchmark Survey of the industry. The aim was to see how companies collect research data, what departments conduct research, how they organize around research and data, and, if small advertisers differ from large ones. Read more.

KaH: The 2019 Organizational Benchmark Survey, The Advertiser Report

Advertising and market research have seen tremendous changes in the last couple of years. As a result, ARF members have been inquiring about different aspects of these changes, from what to call their departments to what tools and techniques are considered best practices. For instance, should it be called a “research department,” “data science” or “customer experience” department? Is it better to have a centralized or decentralized structure? Do such departments provide positive ROI, according to stakeholders? And should they use R, Python, SPSS or SAS?  Read more.

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