In the 19th century, John Wanamaker lamented, “Half the money I spend on advertising is wasted; the trouble is I don't know which half”. Since his time, and especially during the latter half of the 20th century, many theories and models emerged that have enhanced our understanding of advertising and its impact. Yet uncertainty still clouds advertising as the complexity of evaluating it has increased with media fragmentation and the proliferation of online and conventional platforms.
Advertisers are essentially interested in knowing who their audience is and how the audience engages with their ad campaigns. As depicted in Exhibit 13.1, there are three facets — audience measurement, engagement measurement and market response modelling (aka marketing mix modelling) — that collectively yield the knowledge and information that the advertisers are seeking.
In the broader context, marketing mix models (refer Chapter Marketing mix Modelling) that estimate the ROI of advertising tend to be far from perfect. This is because the impact of advertising on sales is primarily long lasting, and despite the use of stock variables and dynamic effects, these models are not particularly good at capturing long term effects. So, while the models are able to capture the impact of the persuasiveness of an advertisement, I believe they are less proficient in assessing how advertising helps to sustain and grow brand loyalty over the years. In this regard, engagement measurement provides for a better assessment. (Market response modelling is covered in Chapter Marketing mix Modelling).
This chapter dwells on audience measurement and engagement measurement. Audience measurement is a fast-changing field. In the past, it remained confined to silos — primarily TV, press and radio. With the onset of online advertising another silo was added — digital. And as eyeballs shifted across screens, multiplatform metrics and measurement methods that measure total audience are increasingly being demanded by media owners and advertisers.
We know that advertising works in many different ways. Moreover, marketers’ objectives on the engagement they desire from their audiences, vary substantially depending on the nature of the product, its lifecycle, brand history, corporate priorities, competitive environment and a host of other factors. Their objectives must be keenly considered while evaluating advertising, as was highlighted by a consortium of 21 leading U.S. advertising agencies.
This consortium which assembled in 1982, released a public document that laid out the Positioning Advertising Copy Testing (PACT) principles on what constitutes good copy testing. PACT stressed the need for multiple measurements — “because single measurements are generally inadequate to assess the performance of an advertisement”. It emphasised that a good copy testing system should provide measurements which are relevant to the objectives of the advertising, and that there was need for clarity and agreement about how the results will be used in advance of each specific test.
The key themes that shed light on advertising were reviewed in the previous chapter How Advertising Works. According to those themes, the success of advertising hinges on its ability to:
In the context of pre-testing (copy testing) and post-testing (tracking) advertising, this chapter reviews the imperatives in advertising analytics, and how key facets, such as those listed above, are tested and measured. Emphasis is given to the practices of the major global firms such as Millward Brown and Ipsos ASI that specialize in advertising analytics and research. It also covers Millward Brown’s awareness index model which provides a framework for measuring the effectiveness of advertising in generating awareness.
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