Tag Archives: customer satisfaction

“Emotional Contagion” in the Workplace through Social Observation, Social Media

Emotions can be “contagious” between individuals, and can affect work group dynamics.

Douglas Pugh

Douglas Pugh

Emotional contagion is characterized by replicating emotions displayed by others, and differs from empathy, which enables understanding another’s emotional experience without actually experiencing it, according to Virginia Commonwealth University’s S. Douglas Pugh.

Adam D I Kramer

Adam D I Kramer

In addition to direct interpersonal contact, “viral emotions” can be transmitted through social media platforms without observing nonverbal cues, according to Facebook’s Adam D. I. Kramer, Jamie E. Guillory of University of California, San Francisco and Cornell University’s Jeffrey T. Hancock.
This finding suggests the significant impact of social media on workplace interpersonal relations and productivity.

Jeffrey Hancock

Jeffrey Hancock

Kramer’s team found that when positive emotional expressions in Facebook News Feeds were reduced, people produced fewer positive posts and more negative posts.
In contrast, when negative emotional expressions were reduced, the people reduced negative posts, indicating that people’s emotional expressions on a massive social media platform like Facebook influences others’ emotions and behaviors.

Sigal Barsade

Sigal Barsade

People in performance situations are influenced by observing others’ emotions.   
When participants observed positive emotions in a decision task, they were more likely to cooperate and perform better in groups, found Wharton’s  Sigal Barsade.

People who were more influenced by others’ emotions on R. William Doherty’s Emotional Contagion Scale also reported greater:

  • Reactivity,
  • Emotionality,
  • Sensitivity to others,
  • Social functioning,
  • Self-esteem,
  • Emotional empathy.

They also reported lower:

  • Alienation,
  • Self-assertiveness,
  • Emotional stability.
Stanley Schachter

Stanley Schachter

Individuals are more likely to be influenced by others emotions when they feel threated, which increases affiliation with others, according to Stanley Schachter‘s emotional similarity hypothesis.

Brooks B Gump

Brooks B Gump

Likewise, when people believe that others are threatened, they are more likely to mimic others’ emotions, found Syracuse University’s Brooks B. Gump and James A. Kulik of University of California, San Diego.

Elaine Hatfield

Elaine Hatfield

Women reported greater contagion of both positive and negative emotions on Doherty’s Emotional Contagion Scale.
Observers also rated these women as experiencing greater emotional contagion than men in research by Doherty with University of Hawaii colleagues Lisa Orimoto, Elaine Hatfield, Janine Hebb, and Theodore M. Singelis of California State University-Chico.

James Laird

James Laird

People who are more likely to “catch” emotions from other are also more likely to actually feel emotions associated with facial expressions they adopt, reported Clark University’s James D. Laird, Tammy Alibozak, Dava Davainis, Katherine Deignan, Katherine Fontanella, Jennifer Hong, Brett Levy, and Christine Pacheco.
This finding suggests that those with greater susceptibility to emotional contagion are convincing actors – to themselves and others.

Christopher K. Hsee

Christopher K. Hsee

Contrary to expectation, people with greater power notice and adopt emotions of people with less power, found University of Hawaii’s Christopher K. Hsee, Hatfield, and John G. Carlson with Claude Chemtob of the U.S. Department of Veterans Affairs.

Participants assumed the role of “teacher” or “learner” to simulate role-based power differentials, then viewed a videotape of a fictitious participant discussing an emotional experience.
Volunteers then described their emotions as they watched the confederate describe a “happiest” and “saddest” life event.
People in higher power roles were more attuned to followers’ emotions than previously anticipated.

The service industry capitalizes on emotional contagion by training staff members to model positive emotions, intended to increase customer satisfaction and loyalty.

James Kulik

James Kulik

However, customer satisfaction measures were more influenced by service quality than employees’ positive emotion, according to Bowling Green State’s Patricia B. Barger and Alicia A. Grandey of Pennsylvania State University.

Emotions can positively or negatively resonate through work organizations with measurable impact on measures of employee attitude, morale, engagement, customer service, safety, and innovation.

-*How do you intentionally model and convey emotions to individuals and group members?
-*What strategies do you use to manage susceptibility to “emotional contagion”?

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Does Customer Recommendation Predict Company Growth?

Fred Reichheld

Fred Reichheld

Net Promoter Scores gauge customer loyalty, expressed by willingness to recommend and advocate the company’s products and services to others.

Its creator, Fred Reichheld of Bain & Company, posited that NPS is a more meaningful measure of a company’s relationship with its customers than customer satisfaction metrics because, he argued, it is correlated with revenue growth.

Richard Owen

Richard Owen

Satmetrix Executives Richard Owen and Laura Brooks further articulated this linkage between customer loyalty and revenue growth.

NPS’s customer loyalty metric is based on 10-point ratings in response to just one question: How likely is it that you would recommend our company/product/service to a friend or colleague?

Laura Brooks

Laura Brooks

“Promoters” respond with a score of 9 or 10 whereas “Detractors” provide ratings of 0-6, and scores of 7 and 8 are ignored in this system, leading to the question of why they are included.
NPS is calculated by subtracting the percentage of customers who are Detractors from the percentage of customers who are Promoters.

Timothy L. Keiningham

Timothy L. Keiningham

Critics, including Ipsos Loyalty’s Timothy L. Keiningham, Bruce Cooil of Vanderbilt, BI Norwegian School of Management’s Tor Wallin Andreassen, and Lerzan Aksoy of Fordham, argue that American Customer Satisfaction Index (ACSI) is an equally accurate predictor of revenue growth.

They reinforced the frequently-replicated finding that actual behaviors, including positive and negative “word of mouth (WOM)are better predictors than attitudes about possible future behaviors, in their evaluation of longitudinal data from 21 firms and 15,500-plus interviews from the Norwegian Customer Satisfaction Barometer.

Claes Fornell

Claes Fornell

Likewise, University of Michigan’s Claes Fornell, Forrest V. Morgensen, and M.S. Krishan, with Sunil Mithas of University of Maryland, found that “it is possible to beat the market consistently by investing in firms that do well on the ACSI.”

Companies that invest in initiatives to increase customer satisfaction, reflected in higher scores than competitors on the American Customer Satisfaction Index (ACSI), also performed better in measures of market value.

More surprisingly, they found that these higher returns are associated with lower stock market risk, probably due to “stock market imperfections” that require time to adjust to news of strong ACSI performance.

Bob Hayes

Bob Hayes

Similarly, customer satisfaction and loyalty researcher Bob Hayes contended that “likelihood to recommend” measures the same construct and has the same predictive value of business growth as customer loyalty questions such as:

  • Overall satisfaction
  • Predicted likelihood to purchase again, evaluated through his Purchasing Loyalty Index (PLI)
  • Number of referrals through “word of mouth” and “word of mouse,” calculated in his Advocacy Loyalty Index (ALI)
  • Resistance to defection to competing offers, measured with his Retention Loyalty Index (RLI).

    Hayes Customer Loyalty Grid

    Hayes Customer Loyalty Grid

Hayes’ findings reinforced the caveat that actual behavior is a more accurate than attitudes about likely future behavior, also demonstrated by University of Connecticut’s V Kumar, J Andrew Petersen and Robert Leone in their analysis of telecoms and financial service customers willing to recommend their service provider.

V Kumar

V Kumar

Only about one-third of these potential Advocates actually recommended the provider, and only about 13% of those referrals actually led to new customers.
Kumar and team called this the “promise gap” and suggested that it can be mitigated by delivering beyond customer expectations, even when a customer complains.

Neal A Morgan

Neil Morgan

Indiana University’s Neil A. Morgan and Lopo Leotte Rego of University of Iowa added a wrinkle to critiques of Net Promoter Scores as the sole necessary indicator of customer satisfaction.

Like Keiningham’s team and Hayes, they found that recommendation intentions (“net promoters”) have “little to no predictive value.
Unlike Hayes, their results found little predictive strength for actual behavior in average number of recommendations.

Instead, Morgan and Rego argued for multiple measures of customer satisfaction as the best predictor of revenue group.
Additionally they found that Top 2 Box satisfaction scores – the sum of percentages for the top two point on surveys of purchase intent, satisfaction or awareness – provided “good” predictive value.

Daniel Schneider

Daniel Schneider

The Net Promoter Score also had the lowest predictive validity when compared to three other scales by Stanford’s Jon Krosnick and Daniel Schneider, with Intuit’s Matt Berent and Hays Interactive’s Randall Thomas.

To improve the NPS, the team recommended replacing the 11 point unipolar rating scale with a 7 point bipolar scale from positive to negative impressions.

Jon Krosnick

Jon Krosnick

Their work replicated Hayes’ finding that liking and satisfaction with a company are highly significantly predictors than the likelihood of recommending, so Krosnick’s team recommended including questions like:

  • Overall, how satisfied are you with the each of the following companies?
  • How much do you like or dislike each of the following companies?

They uncovered correlations among measures of customer experience, and showed that liking is the best predictor of the number of recommendations and satisfaction.

Leon Festinger

Leon Festinger

Customers typically form more positive evaluations after the decision to purchase, probably due to validating purchase choices and reduce cognitive dissonance of purchase dissatisfaction, described by Stanford’s Leon Festinger.

These findings suggest that Reichheld’s claim of NPS as “the only question you need to ask” may be unsubstantiated, and that multiple measures of customer experience are more accurate predictors of a company’s revenue performance.

-*How credible is “willingness to recommend” a company as a predictor of its revenue growth?

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