According to a study released in April by the Interactive Advertising Bureau (IAB), $42.8 billion was spent on online advertising in 2013 – a 17% increase from 2012 – compared to a total of $40.1 billion spent on broadcast TV.
For marketers, the shift to digitization has significantly altered the media planning and buying process. Traditionally, marketers would plan and buy their TV/offline advertising up to a year in advance. But in today’s online world, media planning and buying happens at a much more frequent pace. Since nearly everything in digital is trackable down to the individual level, marketers have access to an ever-increasing volume of user data, actionable advertising and media insights, and the ability to optimize media buying much more regularly for a faster time to value.
But just because digital media is infinitely more measurable doesn’t mean marketers can simply abandon their traditional offline channels and move all their media dollars to the Web. Rather, they need to understand the consolidated influence of online and offline channels on their overall success. To do so, marketers must be able to track and analyze offline and online performance together, in an integrated fashion, so they can allocate their budgets accordingly.
Out With the Old, In With the New
Historically, marketers have used measurement and optimization techniques like marketing mix modeling (MMM) and marketing mix optimization (MMO) to understand the relationship between marketing spend and the resulting outcomes. These techniques typically provide a single, snapshot-in-time analysis of marketing performance using campaign information, sales revenue, econometrics, etc., but don’t deliver insights and optimization recommendations at a granular level. With the increasing number of online options available to connect with consumers, marketers need to understand how offline media influences online activity on a real-time basis, so they can optimize across all channels and leverage media to support their omnichannel customer engagement strategies.
Fortunately, advancements in measurement technology now enable marketers to track and analyze offline and online performance together, in an integrated fashion, and at a much quicker rate. Techniques like top-down modeling utilize “summary-level” data to analyze and predict performance for channels like broadcast TV and print media where user-level data isn’t available. Top-down modeling offers the same cross-channel analysis as traditional MMM, with the added benefit of incorporating an organization’s “tribal knowledge,” such as new product launches, good or bad PR, the marketing spend of competitors, etc. It can also be integrated with bottom-up modeling techniques, which leverage granular, timestamp-based cookie data to provide user-level insight into the performance of each channel and tactic.
By combining top-down and bottom-up techniques, marketers can identify the influences and synergies between online and offline channels and tactics, and how a change made to one or more of the tactics will impact the performance of the others.
More importantly, the insights and recommendations provided by combining top-down and bottom-up measurement techniques go beyond the channel level, drilling down to the most granular level of data, such as placement, creative, size, keywords, etc., to empower more specific, more impactful optimization decisions. When these insights and recommendations are refreshed and reevaluated on a persistent, on-going cycle, they provide marketers with a continual loop of planning, executing, measuring and optimizing.