
From all my years in research and consulting, I
think I’ve learned a thing or two about marketing worth sharing. Enduring fundamentals, mostly—yet often overlooked. So, over the course of my biweekly column this year, I want to share
some snippets for your consideration. I hope they’re helpful.
This week’s thought: Marketing is not an exact science.
Marketing is not an exact
science. Never has been; never will be. Nor does it need to be.
Consider an example: Direct marketing lists.
In direct marketing, lists are used for targeting. But
every list is filled with errors, meaning people who shouldn’t be targeted. Thus, the whole enterprise of direct marketing is inherently inexact. Because no list is perfect. Some marketing
dollars will always be misspent.
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The idea in direct marketing is to buy a list of people who meet relevant targeting criteria. Let’s be generous and assume that a list used by
a brand includes only 10% who fall outside relevant criteria. That’s 90% accuracy. Which means that even before a marketing campaign is delivered, it is inexact to the tune of one-in-ten. Which
doesn’t include other kinds of targeting imprecision such as people out of cycle, people with no interest, people loyal to another preferred brand, or people turned off by the copy.
Yet, notwithstanding these built-in inaccuracies, marketers make a lot of money with direct marketing lists. Because lists include enough of the right people. Lists don’t have to be
exact to be worthwhile. They only need to be good enough. Indeed, lists could be, and often are, overwhelmingly inexact, but, still, they are valuable because they connect marketers with enough of the
right people.
Everything about marketing is like this. Segmentations are predictive, so statistically inexact by definition, especially at segment boundaries and dividing lines.
Loyalty is higher odds of buying not the certainty of someone buying.
The very idea of survey data is rooted in sampling error, which doesn’t include errors from poorly written
questions, poorly trained interviewers, poorly ordered questions, overly long questionnaires and overly complex batteries.
The infamous marketing funnel is a hierarchy of transitional
probabilities that ratchet down to a specific outcome, but one that remains approximate not certain.
Groups of consumers are often labeled on the basis of something that
characterizes 60% or 70%, or whatever, of the group. It’s never all. So, it’s inexact. But it’s good enough because such a grouping will connect marketers in the right way with those
60% or 70%.
Obviously, some aspects of marketing need high levels of precision. Estimates of audiences, delivery, costs and optimal allocations must be more rather than less precise.
Fractions of a percentage point matter because big dollars turn on small differences. This is media, which by my definition includes all channels, all promotions, all trade decisions about shelf and
in-store activity, and everything else tied up in connecting marketing with consumers.
For the most part, though, marketing can get by perfectly well with imprecision. Marketing
decisions tend to be go/no-go decisions. One thing versus another. This, not that. So, all that matters is knowing whether one choice is better than another. It doesn’t matter how much better or
how much worse. It’s yes or no, on or off, launch or shelve, the current or the new. A big enough chance of success or not. Above the threshold of action or below.
Marketers
value inexactness, at least implicitly. Creatives don’t like being second-guessed by pretesting. Not infrequently, researchers extrapolate early-stage trends using gut feel gained from
past experience. Many initiatives that seem right or ethical are often put in place well before marketers go in search of data proving ROI. A lot of decisions are made on the basis of qualitative
input.
To hold these decisions accountable to scientific rigor misses the point. The point is not to run every decision through high-tech evaluation. The point is to make money. If
that can be done unscientifically, then so be it. Exactitude may be a means to a better decision, but it is not the objective itself.
Mind you, I am not arguing for a repudiation of
rigor. One of my mentors, Kevin Clancy, liked to position Yankelovich as the research firm of choice with a thought exercise he called "the case of the escalating sevens." Imagine, he would say, seven
choices for each of 12 marketing decisions (target, positioning, creative, packaging, pricing, distribution, media spend, media mix, media schedule, promotional spend, promotional mix and promotional
schedule). Positing a mere seven choices for each is conservative, but even at that the total number of possible marketing plans is 13.8 billion. The odds of a marketer using gut feel to pick the one
plan that would be a “resounding success” — Kevin’s words — are infinitesimally small. More rigor is better than less.
But Kevin never advocated rigor
for its own sake. Kevin knew it was all about profitability, which was literally at the heart of every methodology and model that Kevin devised. Kevin pushed for marketers to be smarter, not to be
perfect. Better data. Better questions. Better frameworks. Better equations. Better forecasts. But always with the recognition that marketing decisions are go/no-go. Once you know that answer, more
precision is unhelpful.
Ultimately, this is what marketing ROI is all about — more correct decisions about go/no-go. When that decision is correct, marketing makes money for a
company either way—a correct go decision is more sales; a correct no-go decision is less costs. It shouldn’t matter if it’s marketing gut or marketing science. When marketing is
exactly right about whether to go or not to go, marketing need be no more an exact science than that.