Goal 3: Persuasive Advertising
The romantic view of advertising is that advertising is powerful. It persuades people to change what they feel, think, or do.
In practice, there is no generalizable evidence on any lasting persuasive effects of advertising — at least not enough to justify a global spend of billions. There is not one advertising, marketing, or economic text that even suggests advertising is powerful, let alone flaunts proof. Although people see or hear hundreds or thousands of advertisements a day, by and large people do nothing in response. Sales and images seldom change. I’m not suggesting that competent brand advertising generally fails. But people’s exotic expectations of its outcome seldom are realized.
Advertising lacks consistently dynamic effects because of, once again, competition. Your competitors’ omnipresent retail availability, quality control, category management, CRM, promotion, and advertising all interfere. Left to itself, advertising your brand would, of course, work wonders.
Realistically, I maintain that advertising works as paid-for creative publicity. A competent ad automatically publicizes its brand and brand name. Ads can create and refresh memory traces and associations. True results can be rediscovered often. But often they aren’t. This kind of publicity can then affect whether consumers find the brand salient, familiar, and reputable — in short, a brand they may want to buy. Indeed, the more alike two brands are, the more effective creative publicity can be, as it is virtually the only thing that separates them, in both the short term and the long term.
The realistic task for advertising is not to change what people think about your brand, which is always hard to achieve, but to have them think about your brand at all. As Dr. Johnson said almost 300 years ago, “Men more frequently require to be reminded than informed.”
Goal 4: Profit Maximization
Maximizing shareholder value has become the plaything of the Western world. You can always seek more profit. But seeking to maximize it would let your competitors undercut your efforts.
Technically, the ubiquitous precept to maximize or optimize is a bad taskmaster. It leads to extreme decisions. Sophocles’ Antigone chose to reject the laws of Thebes (and her uncle) in favor of the laws of her gods. She paid with her life. Should executives, asks Charles Handy, aim to sacrifice career to family, or vice versa? All of one or all of the other? Economists would have us similarly believe that consumers choose the brand with the optimum utility. But in a customary near-steady-state market, each rationally optimizing consumer would then always choose the same “best” brand. The empirical and theoretical evidence on consumer behavior, however, shows otherwise. As we have seen, consumers run with repertoires of brands.
The realist method of optimizing is therefore to “satisfice,” as the late and great Nobel laureate Herbert Simon put it some 50 years ago — combining the words satisfy and suffice. Both managers and consumers choose what is “good enough,” not what is supposedly “best.” They strive to make a good profit, to reach suboptimal multiple goals, and to choose an adequate product (since nothing better can usually be found or made). It’s not survival of the fittest, but survival of the fit enough.
The idea of pursuing multiple goals is of course not new. But it requires us to religiously forgo the simple mathematics of maximizing or optimizing things, the mathematics romantically beloved by economists and management scientists through the ages.
Goal 5: Knowledge Management
Knowledge management is the latest marketing mantra. It is unrealistic when we are mostly drowning in catadupes of undigested data.
Blindly accepting our sophisticated colleagues’ analysis techniques would require a romantic act of faith. No statistically derived “best” cluster, market segment, price elasticity, or econometric sales–advertising regression like S=5.39A + 14.56 has ever passed into lasting marketing know-how or textbooks. Where is the “best-fitting” cluster or model from 10 years ago? With the current PC-induced spate of multivariate regressions, there should be, of course, not just one or two such success stories, but hundreds, even thousands, of them.