Derek Gleason

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Derek spent two-and-a-half years running the CXL blog.

He now does a mix of internal and client-facing content and SEO stuff for Workshop Digital. Before all of that, he edited encyclopedias.

Find him on Twitter.

Should how fallacy

Get a chicken. Cook it until it’s perfectly done. Reduce the jus to a nice pan sauce. Then finish it with some butter until it has the right balance of flavors. Enjoy.

This is a useless recipe, but it’s not wrong. It assumes, however, that accurate advice on what you should do is as valuable as advice on how to do it—the “Should-How Fallacy.”

But being right doesn’t create value; empowering others to succeed does.

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Product Bundling

It’s the early 1980s. You’re in charge of a fledgling ESPN, and you have two choices:

  • Add more college basketball—you’re highest-rated programming—to the schedule.
  • Stick with the skiing and billiards you’ve aired for years (because you couldn’t afford anything else).

Which creates the more profitable programming bundle?

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Economic Moats

When Warren Buffett coined the term “economic moat”, he stated that the products that have wide, sustainable moats around them, are the ones that deliver rewards to investors.

That’s why determining the competitive advantage of any company is key to investing, to which moats were initially tethered: a bigger moat makes a stock a better bet.

But the implications are broader, for companies large and small. An effective moat doesn’t require Amazon’s distribution network or Microsoft’s monopolistic software strategy.

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Good user research depends on asking questions that let respondents describe what they actually think, remember, or experienced.

A leading question pushes someone toward a particular answer through its wording or framing. But biased survey results can also come from response options, question order, interviewer behavior, social desirability, and the wider context of the questionnaire.

That distinction matters. Not every biased survey question is technically a leading question, but the result can be similar: data that reflects the survey design as much as the respondent’s actual opinion.

Decades of survey-methodology research show that wording, response format, question order, and context can all change the answers people give.

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Product lifecycle marketing

The classic graph for the product lifecycle is a sales curve that progresses through stages:

  • a sharp rise from the x-axis as a product transitions from the Introduction to the Growth phase;
  • a sustained, rounded peak in Maturity;
  • and a gradual Decline that portends its withdrawal from the market.

Each stage of the product lifecycle has implications for marketing. But an MBA-friendly curve rarely translates to reality. The goal of product lifecycle marketing is not to match the curve but to outline what may work best now and plan for the future.

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Neuromarketing uses neuroscience, physiological measurement, and behavioral methods to understand how people respond to marketing stimuli beyond what they can, or choose to, report directly.

Depending on the research question, that can include fMRI, EEG, eye tracking, heart rate, skin conductance, implicit-response testing, and other methods. These signals can reveal patterns that surveys and interviews alone may miss, but they are not a direct window into what every customer thinks or why they behave a certain way.

Scientific knowledge builds incrementally. A single study does not establish a universal marketing rule, and findings from one product, audience, or setting may not transfer directly to another.

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