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Giles Keeble: in the age of ‘big data’ and ubiquitous ads – do we measure more but understand less?

I think that I shall never see a billboard lovely as a tree. Perhaps, unless the billboards fall, I’ll never see a tree at all – Ogden Nash

The last chapter of Michael Sandel’s interesting and clearly written book, ‘What Money Can’t Buy’, is entitled ‘Naming Rights’ and has a section in it headed ‘Your Ad Here.’ Sandel gives examples of the commercialisation of everything from sports grounds (named after the sponsor rather than the team) to ads on everything from people’s foreheads to signposts on nature trails.

He asks if there is anything wrong with commercialism. An analogy he makes is one of pollution: “emitting carbon dioxide is not wrong in itself: we do it every time we breathe. And yet an excess of carbon dioxide can be environmentally destructive. In a similar way, otherwise unobjectionable extensions of advertising into novel settings may, if widespread, bring about a society dominated by corporate sponsorships and consumerism, a society in which everything is brought to you by MasterCard or McDonalds.”

Ads of one sort or another are everywhere, in toilets, on taxis, and on tickets. This leads to another concern, raised by Matthew Crawford in his new book ‘The World Beyond Your Head’ about how our ability to concentrate is being eroded by constant messages, distractions that are ‘a kind of obesity of the mind.’

The way in which we respond to advertising and other messages has changed with technology. Where old farts like me had TV, press, posters and radio, the new farts have a range of other channels as well as different ways of using the ‘old’ ones. The nature of digital has enabled new, faster and broader ways of looking at data. Despite the fact that most advertising is not about direct response but about longer term brand building, access to big data seems to me to have made it, psychologically at least, closer to ‘direct marketing’ than it used to be. A shift in emphasis and attitude: anything goes, anywhere.

The danger remains that as we measure more we understand less.

But my real worry about proliferation is that, in time, it might be harmful to a business which is (or can be) not only economically effective, but fun and enjoyable – for those seeing the work as well as those creating it.

The fact that we screen out such a huge percentage of the commercial messages we are presented with is beside the point. If you can slap an ad on anything, effective or not, what does it say about our society?

And surely, everyone still involved in the advertising business wants to feel proud of what they do?

One Comment

  1. In the world of structured data information searches for users, based on their profiles of structured information. These profiles contain all preferences and emotions towards goods and allow very precise targeting.

    I discovered and patented how to structure any data: Language has its own Internal parsing, indexing and statistics. For instance, there are two sentences:

    a) ‘Fire!’
    b) ‘Dismay and anguish were depicted on every countenance; the males turned pale, and the females fainted; Mr. Snodgrass and Mr. Winkle grasped each other by the hand, and gazed at the spot where their leader had gone down, with frenzied eagerness; while Mr. Tupman, by way of rendering the promptest assistance, and at the same time conveying to any persons who might be within hearing, the clearest possible notion of the catastrophe, ran off across the country at his utmost speed, screaming ‘Fire!’ with all his might.’

    Evidently, that the phrase ‘Fire!’ has different importance into both sentences, in regard to extra information in both. This distinction is reflected as the phrase weights: the first has 1, the second – 0.02; the greater weight signifies stronger emotional ‘acuteness’.
    First you need to parse obtaining phrases from clauses, for sentences and paragraphs. Next, you calculate Internal statistics, weights; where the weight refers to the frequency that a phrase occurs in relation to other phrases.
    After that data is indexed by common dictionary, like Merriam, and annotated by subtexts.
    This is a small sample of the structured data:
    this – signify – : 333333
    both – are – once : 333333
    confusion – signify – : 333321
    speaking – done – once : 333112
    speaking – was – both : 333109
    place – is – in : 250000
    To see the validity of the technology – pick up any sentence and try yourself. After that try a paragraph?

    All information is texts or can be reduced to texts.

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