Several of the author's primary examples were actually companies she's continued to do business with, so they're clearly not applying this just to customers who

Several of the author's primary examples were actually companies she's continued to do business with, so they're clearly not applying this just to customers who weren't going to come back. I've certainly decided not to deal with a company again because right after the initial transaction I've gotten hit with a flood of this spam. I suspect there's one of the standard measurement issues where companies find it easier to quantify customers who've apparently come back due to this kind of marketing than to measure customers who've gotten sick of it and reduced or ceased their business with the company. It's possible to do a better job, but these companies never seem to and it might be that there's a perverse incentive for the marketers to mismeasure. Having worked directly under the SVP of Business Intelligence & Analytics at one of the larger US-based social networks I can say from experience that it's really, really hard to get people to consider the things that are hard to measure or hard to interpret. Even in a company that's heavily analytics-driven there's a lot of magical thinking, a lot of anecdata, and a strong bias towards short term effects. Think of it as the marketing equivalent of laying off 20% of your workforce, telling everyone else to work 25% harder, and convincing Wall Street this means profits will go up and stay up. It's easy to spot the bump in your balance sheet from lower costs and it's hard to quantify the long term costs of decreased morale, lower total productivity, most likely lower individual productivity, attrition, and inability to take advantage of opportunities.