Why Localizing Marketing Doesn’t Always Work

Why Localizing Marketing Doesn’t Always Work

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Whether to localize global-brand marketing programs remains one of the most contentious debates in multinational organizations. On the one hand, local brand managers typically argue that consumer habits in their market are different, their consumers’ purchase behavior is different, preferences and tastes are different, the media and the retail trade are different, and, therefore, their customers require unique, tailored, and delicate handling. The head office, meanwhile, takes the position that achieving scale justifies losing some local customers in return for global efficiencies.

Faced with this trade-off, local brand managers, often to the consternation of their head offices, spend inordinate amounts of effort demonstrating that national boundaries are an excellent segmentation variable — that consumers are sufficiently different across markets to justify adapting products and marketing programs. To defend their position, they’ll whip out the latest in a series of market research reports conclusively showing (at p<.05) regional customer differences which justify altering the product packaging, scent, and advertising execution for their market.

But what if these brand managers are wrong? What if consumers are actually more similar across markets than the research shows? My colleagues and I have long studied so-called “marketing universals,” consumer behaviors within a segment and toward a particular product category that don’t vary across culture – things like how consumers gauge quality and how they respond to price promotions. Among our findings – and we’re not alone in demonstrating this – is that while it’s straightforward to show differences it’s really hard to show similarities with any statistical rigor. Cross-cultural research is replete with findings of difference, due in part to methodologies and publication preference for positive findings. Findings of similarity across cultures, or universals, are rare, not least because identifying universals poses a host of methodological obstacles.

Most market researchers know this, but they tend to keep quiet about it. Here’s the problem: If you wanted to test the hypothesis that consumers in Michigan are different from those in bordering Ontario – looking, say, at their attitude toward your product packaging — you could readily design a study that would give you the answer. In fact, if you had a large enough sample on both sides of the border, you’d know the answer in advance: it would almost always show you that the two populations are different; that is the way significance tests work. The test tells you that if you were to run the study again and again, if there are underlying differences, then nineteen times out of twenty your results would show significant differences. That is taken as pretty strong evidence of underlying differences. But suppose you wanted to examine if consumers in Michigan and Ontario are the same or similar. What statistical test would you use?

You’d be out of luck. The most common tests are only designed to show differences. Let’s examine this more closely. You might think that a lack of difference on a statistical significance test is evidence of similarity.  But, in fact, any statistician would point out that statistical tests are not designed to demonstrate the absence of difference. Thus, consumers may be far more similar across national and cultural boundaries than the research shows. Indeed, there’s good reason to think this is the case; when it comes to universal human needs – the desire for security, a sense of belonging, to provide for one’s family – ample social science research shows that we have the same fundamental aspirations. Offerings that address these needs, it follows, will be embraced even without excessive localization. Parents of infants the world over want a dry (and therefore comfortable) baby who sleeps through the night; diapers that help with that probably don’t need a lot of localizing beyond labeling in the local language.

And yet, think about how much time, effort, and money goes into localizing products, positioning, prices, and advertising, based on findings of significant difference in market research studies. If these decisions are based on research showing differences, we may be localizing too much.

Fortunately, several organizational correctives to this statistical bias towards difference exist.

First, statistical tests of difference should be (and often are) interpreted pragmatically rather than dogmatically. Any decisions based on findings of statistical difference should still be subject to the hard-nosed business hurdles: how much will local adaptation cost? What is the potential return on the costs of adaption (how much more will we sell)? and will adaptation delay implementation (for example, a product launch)?

Second, multinationals thrive on scale. And scale favors standardization across markets. Even if statistical tests are biased toward difference, multinational organizations are biased toward similarity. Head office preference is to only allow adaptation for the more obvious differences such as language and retail format. The head office is also usually the more powerful voice in the organization, with a veto over local managers. In general, this power balance probably serves the firm, and customers, best.

Finally, with markets and media becoming more global, similarities are now more visible if still hard to measure statistically. And statistical tests are beginning to emerge that can at least demonstrate that consumers’ tastes and preferences are converging.

Whether to standardize or localize marketing programs remains one of the most enduring debates in global firms. It will continue to be a point of friction because it is about trading off locally optimal programs versus globally optimal ones. This is an important debate, but it should not be adjudicated by significance tests.

iapers that help with that probably don’t need a lot of localizing beyond labeling in the local language.

And yet, think about how much time, effort, and money goes into localizing products, positioning, prices, and advertising, based on findings of significant difference in market research studies. If these decisions are based on research showing differences, we may be localizing too much.

Fortunately, several organizational correctives to this statistical bias towards difference exist.

First, statistical tests of difference should be (and often are) interpreted pragmatically rather than dogmatically. Any decisions based on findings of statistical difference should still be subject to the hard-nosed business hurdles: how much will local adaptation cost? What is the potential return on the costs of adaption (how much more will we sell)? and will adaptation delay implementation (for example, a product launch)?

Second, multinationals thrive on scale. And scale favors standardization across markets. Even if statistical tests are biased toward difference, multinational organizations are biased toward similarity. Head office preference is to only allow adaptation for the more obvious differences such as language and retail format. The head office is also usually the more powerful voice in the organization, with a veto over local managers. In general, this power balance probably serves the firm, and customers, best.

Finally, with markets and media becoming more global, similarities are now more visible if still hard to measure statistically. And statistical tests are beginning to emerge that can at least demonstrate that consumers’ tastes and preferences are converging.

Whether to standardize or localize marketing programs remains one of the most enduring debates in global firms. It will continue to be a point of friction because it is about trading off locally optimal programs versus globally optimal ones. This is an important debate, but it should not be adjudicated by significance tests.

[Harvard Business Review]

September 3, 2016 / by / in , , , , ,

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