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  • Writer's pictureThomas Mouquot

A Shift from Traditional Media Planning to Data-Focused Comms Planning

Introduction


In recent decades, the role of advertising agencies in developing comprehensive marketing plans has expanded, encompassing brand strategy and integration of data and psychology. However, with the rapid evolution of technology and consumer behavior, advertisers face new challenges and opportunities. This essay explores the understanding of data and programmatic technology, the changes in behavior and media landscape, and the evolution of communication planning to achieve effectiveness in today's dynamic advertising landscape.


Understanding Programmatic Methodology and Audience Segments


Programmatic media buying has gained significant attention in recent years, revolutionizing the way advertisers target audiences. By automating the buying process and leveraging supply-side and demand-side platforms, advertisers can make data-informed decisions and accurately target desired audiences. Programmatic buying has disrupted traditional linear planning processes, enabling improved data quality and availability for planning and mitigating risks associated with testing innovative ideas. Data management platforms (DMPs) have further transformed marketing strategies by collecting and matching first-party data from online and offline sources, allowing marketers to create targetable segments across channels. Loyalty programs have also evolved with the introduction of big data and segmentation, empowering advertisers to identify precise audiences and develop strategies based on more accurate data.


Changes in Behavior and Media Landscape


The evolving media ecosystem, shaped by user behavior and new touchpoints, demands constant adaptation from advertisers. Media meshing and media stacking have emerged as concepts driven by the growth of media channels, particularly on mobile devices, and the diverse consumption patterns across these channels. Effective campaign planning requires careful consideration of device and media platform usage, leveraging data to programmatically reach the right users at the right time. Initiatives like the ROPO (Research Online, Purchase Offline) project by Google enable businesses to calculate ROI more precisely by collecting pre-store data to identify in-market consumers and deliver targeted advertising. Planning campaigns in an omni-channel environment requires coherence and flexibility as new trends continue to emerge.


Evolution of Comms Planning Process


Comms planning has undergone transformation since its inception in 1994, evolving from the media department of full-service agencies. The process involves gaining a deep understanding of the audience, aligning client business objectives, and developing communication strategies in collaboration with partner agencies. The introduction of large datasets and econometrics has disrupted this process, enabling stronger business decisions based on media consumption and budget allocation. Behavioral economics, influenced by big data, has shifted the focus from assuming rational human behavior to understanding decision-making using data-driven insights. Advertisers can leverage audience segmentation within DMPs and programmatically utilize this data across multiple channels, improving effectiveness and campaign measurement.


Conclusion


The comms planning process continues to evolve in response to the data revolution and programmatic buying methods. Programmatic offers unprecedented opportunities to target custom audiences, but advertisers must also harness the generated data to drive audience insights and challenge conventional communication planning. By leveraging programmatic audience buying and utilizing data insights, advertisers can differentiate their marketing strategies and achieve greater effectiveness. As the advertising landscape continues to evolve, adapting to new technologies and consumer behaviors is crucial for advertisers to stay ahead and drive successful campaigns.

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