Bad is Stronger than Good: Lessons for Customer Loyalty & Experience

It seems that your mother’s admonishment that “if you have nothing good to say, don’t say anything at all,” may have been counterintuitive and running against the grain of human nature and neuroscience. “Bad is stronger than good” (the phrase is borrowed from an article by the same name by Baumeister et al., 2001) is a core concept in behavioral economics and has significant implications for anyone managing and measuring loyalty and the customer experience, not just child rearing.

People, it seems, have a “negativity bias.” In a nutshell, this means we receive negative or bad information more quickly, process that information more thoroughly, and remember and respond to that information more swiftly and consistently than is the case for positive or good information. (Experiments confirm that this negativity bias appears in other species as well, leading to the hypotheses that it is part of the “survival of the fittest” selection criteria driving evolution, i.e. the need to process and respond to information about risks and threats is more essential to survival than good information.)

The Impact of Bad Experiences

Drawing on this premise from behavioral economics, there are a number of logical corollaries that are important to managing loyalty and the customer experience. First, customer behavior is far more likely to be affected by (and to be affected more dramatically by) bad experiences than by good experiences. In other words, bad experiences and problems will more likely and more quickly trigger customer defection and churn than positive experiences will deepen loyalty.

We all have heard some variation on the following rule of thumb: people who have had bad experiences or a problem are X times more likely to tell someone else than people who have had good experiences. It seems that all of us are hard wired to share negative information more than positive information. This leads to another set of corollaries: customer will spread negative word of mouth (WOM) more quickly, frequently and extensively than they share positive WOM.

Yet a third corollary can affect new customer acquisition: since we are more receptive to bad information than good information, negative WOM is far more likely to be heard, processed, remembered and acted on by prospects than positive WOM.

In other words, the adverse impact on a company from bad customer experiences, performance failures, problems and complaints are very likely to “outweigh” the gains from customer success stories in terms of

1. Customer defection vs. retention
2. Negative WOM vs. positive WOM
3. Lost opportunities with prospects vs. new customer acquisition

Managing and Measuring the “Bad” and the “Good” (To Avoid the “Ugly”)

Bad and good are not simply mirror images of the same things in greater/lesser quantity that can be captured with linear measurements. This means that it is critical for marketers and researchers to differentiate between positive drivers of loyalty or satisfaction with an experience and negative drivers of dissatisfaction.

Because bad is stronger than good, behavioral economics tells us, even yells at us, to address the downside, negative drivers or dissatisfiers as the first priority before turning to those upside drivers of loyalty. If the ship has holes and is taking on water, in other words, rearranging the deck chairs and sprucing up the buffet isn’t going to help.

The dissatisfiers often are basic performance expectations that customers take for granted. Every company and industry has such “table stakes” types of issues: accurate financial statements; clean hotel rooms; 100% system uptime for electricity, cable, Internet and similar services; timely ordering and both accurate and timely serving of food; products that “work” as expected; and so on. Poor performance on these basic expectations is a deadly dissatisfier. While customers will defect and spread negative WOM for such failures to meet expectations on these types of issues, exceeding expectations or trying to delight customers on the basic table stakes doesn’t earn the company any points: customers aren’t impressed or WOWed when statements are correct, the sheets are clean or the lights go on when they throw the switch.

The enhancers or positive drivers, by contrast, are those performance attributes that set a company apart, the potential differentiators that go beyond the basic expectations and which can be used to reinforce loyalty or deliver great customer experiences. These positive drivers are the attributes on which WOWing the customer yields a real and positive payoff. Some attributes might be both negative and positive drivers on which less/more of the exact same items can motivate both dissatisfaction and delight, as often is the case with price, for example.

And About that Measurement . . .

Measuring the downside risk separate from the upside potential is critical not just because the drivers may be different, but because the magnitudes or impacts differ. Negativity bias extends to the relative impact or importance of bad and good drivers. People are “loss averse.” An extension of negativity bias, loss aversion indicates that people attach more importance to avoiding losses, negative experiences or pain than they do to winning, positive experiences or getting pleasure. (One rule of thumb is that people attach at least twice as much value to avoiding a negative as gaining a positive.) Even when an attribute is both a negative and positive driver, a single linear regression line (or any single measurement, for that matter) can’t capture the differences between the potential bad/downside and good/upside impact.

Another problem with regression-based approaches (and for those of you both less and more stats savvy than I am, I apologize for this digression) is that they are “additive” and “compensatory”. In other words, they treat positive and negative coefficients like numerical weights on a balance scale, and the side with more “weight” tips the scale in its direction. But behavioral economics and negativity bias tell us this is a mathematical myth: the negative weights carry more impact than the positive. To go back to some of our earlier analogies: if the statement is wrong; the room is dirty; the lights don’t go on; or the ship is sinking, no amount of positive drivers can “compensate” or counter balance the failure on the fundamentals. (For this and other reasons, we recommend using Shapley Values for key drivers, a game-theory non-linear, non-compensatory approach that also reduces problems of multicollinearity, but here I am wading even further afield into stats.)

Bringing it all Together

What does this mean for companies trying to understand, measure and manage customer loyalty and experiences?

1. Positive and negative drivers should be measured separately because
2. The upside enhancers and downside dissatisfiers differ (but may overlap) and
3. Have widely differing impact on customer behavior; therefore,
4. Negative drivers that can undermine the customer relationship and lead to disappointing experiences should be given priority over and managed separate from the drivers of loyalty and satisfaction with touchpoint experiences.

Marketers shouldn’t stop looking for opportunities to strengthen customer relationships, deepen loyalty and deliver high-impact customer experiences. But they must be ever cognizant of the need to make “plugging the holes,” improving performance on attributes that undermine loyalty and lead to disappointing experiences, their top priority.

I wonder if I can blame my cynicism on negativity bias and a heightened sense of survival instinct?