Knowledgeistics

Quantitative metrics are key to understanding one’s market. Now, more than ever, marketers have access to a wealth of data to help make decisions. However, I’m going to argue that this new resource is often emphasized at the expense of qualitative knowledge, which is instrumental to creating effective strategy.

Today in the New York Times, they covered the efforts of big firms like M.R.I. to better quantify the impact of advertisements in magazines. A small detail stuck out as I read. Ad revenues at magazines are not falling as fast as they are at newspapers. One obvious explanation for this is that magazines come with built-in psychographic and demographic targeting. Want to reach snowboarders? Why not try Transworld Snowboarding?

The underlying message of the article was also pretty clear. Quantitative metrics are indispensable for marketers and advertisers. Online advertising and marketing offer quantitative analysis undreamed-of before the advent of the Internet. Print advertising offers metrics that have resisted improvement for decades- ergo, print advertising loses.

At Compete, Stephen DiMarco underscores this point by drawing a line between marketing undertaken on the basis of intuition, “Powerball Marketing” and marketing informed by substantial statistical analysis, “Moneyball Marketing”. His key points, roughly paraphrased, are that:

1) Desired outcomes of marketing campaigns should be specifically quantified

2) Advanced quantitative measures should primarily guide marketing initiatives

On point 1, I agree with Stephen wholeheartedly. All projects need clear-cut objectives, and woe to the firm that allocates hard money to soft, unquantified “improvements” or “increases”.

On point 2, I have to disagree, in part. Success in marketing-by-numbers can’t explain the persistence of magazine ad revenues over newspapers’, given that both media lack robust quantitative measures. Online marketing and market research provides a veritable fire hose of consumer data to the savvy marketer. This leads to a tendency to ignore or discount qualitative knowledge, despite its necessity, as demonstrated by those plucky glossies.

Quantitative data can accurately describe consumer behavior, and be used to predict it to some extent. Qualitative data is valuable when the quantitative data you have doesn’t provide the ability to rationally explain a behavior, or make rational strategic decisions. When the beliefs, attitudes and motivations of one’s customer or consumer are well-understood, it’s possible to make good decisions when quant data can’t do it for you.

For example, if your analytics show that conversion rates have fallen off sharply after introducing a new tagline, the most the numbers can do is identify that the tagline is the problem. With a robust qualitative dataset, and a good understanding of the beliefs, motivations, and other relevant pyschographic factors expressed in that dataset, you’ll be able to identify the unintentional use of a new slang word used to describe terrible body odor in the tagline. The quantitative data would allow you to replace the tagline and fix the problem. The qualitative data would allow you to replace the tagline, as well as spin the faux-pas, make a knowing joke with your consumer, and salvage brand image.

Part of a marketer’s job is to understand their customer or consumer. Clickstream data, correlates of conversion rates, or even surveys won’t really illuminate human beliefs, attitudes, or motivations. SMMR provides a unique opportunity to collect, oftentimes, both quantitative and qualitative knowledge simultaneously. It’s important for marketers to remember that both types of information are essential. Remember: Pizza and beer separately are great, but together they make a balanced meal.

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