snippets from the guide   (Introduction ⇩)

(Introduction ⇧)

In the age of analytics, The Marketing Analytics Practitioner’s Guide serves as a comprehensive guide to marketing management, covering the underlying concepts and their application.

As advances in technology transform the very nature of marketing, there has never been greater need for marketers to learn marketing.

Essentially a practitioner’s guide to marketing management in the 21st century, the guide blends the art and the science of marketing to reflect how the discipline has matured in the age of analytics.

Application oriented, it imparts an understanding of how to interpret and apply research data and big data with the aid of the analytical tools that practitioners use.


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Advertising Analytics

“Advertising people who ignore research are as dangerous as generals who ignore decodes of enemy signals.” — David Ogilvy

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 to a great extent. Yet uncertainty still clouds advertising to a great extent, and the complexity of evaluating advertising 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 the Exhibit, there are three facets that collectively yield the knowledge and information that the advertisers are seeking:

  • audience measurement

    ,
  • engagement measurement

    and
  • market response modelling (aka market mix modelling)

Exhibit   Advertising effectiveness.

Market response modelling is covered in Chapter Market Mix Modelling. It is pertinent, however, to point out that in the context of advertising ROI, market mix models 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.

This chapter dwells on audience measurement and engagement measurement. Audience measurement is a fast changing field. In the past it was confined to silos — primarily TV, press and radio. With the onset of online advertising another silo was added — digital. And as content is increasing viewed across screens, multiplatform measurement tools that measures total audience are increasingly being demanded by media owners and advertisers.

We know that advertising works in many different ways. And 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 Chapter How Advertising Works. According to those themes, the success of advertising hinges on its ability to generate salience, persuade consumers, differentiate from competitors, generate affinity for the brand, associate the brand with values, symbols and images, build relationships with consumers, and increase their involvement with the brand, generate feelings and emotions, and convey relevant messages — its proposition, its mantra.

Advertising research and analytics is categorized either as:

  • Copy testing

    : pre-testing of advertising before it is aired, or
  • Advertising tracking

    : testing after campaign has been launched.

In the context of both copy testing and tracking, 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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