An Omni-Media Approach to a Digital Technique
Marketers have always sought to make their messages relevant to their customers. Faced with an increasing barrage of ads, consumers are filtering out all messages except those that are most relevant to them. Advertisers must fine-tune both their marketing messages and the media they deploy to overcome this resistance, ensuring that their relevance to the consumer is maximized – so that their risk of inefficiency – and commercial avoidance is minimized.
Digital marketers have successfully improved the efficiency of their messages by leveraging their large databases to quantify relevancy. This paper argues that marketers should seek to adapt this approach to all of their media. The goal would be to develop a brand-specific metric, R , that allows each vehicle to be ranked on the degree of relevancy of the brand’s message to the vehicle’s audience. Since non-digital media lack the big databases and interactivity of digital, this poses a considerable challenge – but one that may be surmounted by utilizing a variety of available or soon-to-be-available data sources.
In support of this argument, this paper:
1. Documents consumers’ increasing tendency to filter out all but the most relevant commercial messages.
2. Reviews the success of digital media to calculate formal metrics for Relevancy
3. Suggests the need for marketers to re-examine existing models of how advertising works repetition/frequency and the “sales funnel” – in favor of one which uses relevancy to penetrate the consumer’s filters
4. Defines successful communication as delivering the right message to the right person, in the right place (media) at the right time, and looks at each of these elements with respect to relevancy
5. Explores possible ways to create a brand-specific relevancy measure using currently-available data
6. Recommends a set of actionable steps for marketers to develop competence in Quantifying Relevancy