What is a harbinger of failure?
A working definition from MIT Sloan
harbinger of failure (noun)
A consumer with a knack for repeatedly purchasing flop products.
Did you get in early on Google Glass and Amazon’s Fire Phone? If so, you might be a “harbinger of failure.” Back in 2015, MIT Sloan marketing professors Duncan Simester and Catherine Tucker turned conventional wisdom on its head: Not all positive feedback is good feedback, and product sales don’t translate to success if the wrong people are buying.
The research — conducted using transaction data from a large U.S. convenience store chain — showed that such harbingers’ early adoption of a new product is a strong signal that a product will fail. These customers have unusual preferences and tend to buy things that appeal to only a narrow slice of the marketplace, according to the research. The more they buy, the less likely it is that the product will succeed.
Firms can identify these customers through past purchases of either new products that failed or existing products that few other customers have purchased.
“The next question is, where else does this happen? We’re not sure yet, but we’re contemplating ideas,” Simester said at the time. “One idea might be, there are harbingers of political failure: donors to political campaigns who systematically give to losing campaigns.”
Are you a harbinger of failure? What products did you buy early that didn’t make it?
Working Definitions: Research
MIT Sloan's Working Definitions explore the words and phrases behind emerging management ideas.
Strategy for Startups: From Idea to Impact
In person at MIT Sloan
Register Now
4 takeaways for finance teams as they implement AI
Creativity and clean data are at the core of successful artificial intelligence implementations, according to the CFOs of Shopify and Arm Holdings.
Large language models can help professionals identify customer needs
A study found that trained LLMs can identify what customers want as well as expert market reach analysts, who are freed up to apply their expertise to high-leverage tasks.
New MIT Sloan courses focus on deep learning, gen AI, and fintech
Additions to the MIT Sloan 2025 – 2026 course list include Intensive Hands-On Deep Learning, AI and Money, and The Arrhythmia of Finance.
5 actions to elevate customer experience in physical retail
Physical retailers should combine data-driven insights with human touch to create a seamless hybrid shopping experience, these B2B experts say.
Consumers prefer early entrants in new markets, but 2nd movers can still win
Consumers approve of firms that do the work to make an industry seem legitimate. Those that free-ride on that “legitimation work” are seen as less authentic.
Better predictive models could reduce clothing returns
Adding images to predictive models can help retailers estimate return rates as they decide what to feature on their websites.
Study gauges how people perceive AI-created content
Companies that intend to use generative artificial intelligence should first consider how people regard work created by AI, humans, or some combination of the two.
Xbox CFO on gaming content, business models, and generative AI
Xbox CFO Tim Stuart explains what other industries can learn from the booming gaming industry.
Blockchain for marketing? Maybe, but privacy issues abound
Blockchain’s permanent record is one of its strengths, but it can cause problems for marketing strategies and consumer privacy.
How to nurture a data-driven customer — and why
Customer data is key as companies seek to create new digital revenue streams. Here’s how to attract and retain a new class of customer.