The American Customer Satisfaction Index (ACSI) was established in 1994 at the Ross School of Business, the University of Michigan, under the leadership of Claes Fornell, the Distinguished Donald C. Cook Professor Emeritus of Business Administration. Expressed as a system of latent variable equations and populated with data from about 200,000 customers/consumers annually, ACSI tracks the quality of economic output (products and services) in the US – as gauged by the consumers of that output. ACSI is complementary to GDP, which measures the (value of) quantity of economic output. Over the years, more than 16,000 peer-reviewed scientific articles confirm that company-level ACSI scores have an impact on earnings, cash flow, stock returns, earnings surprises, ROI, and a number of other important business performance metrics.
The American Customer Satisfaction Index (ACSI)
Third Quarter 2024: Strong Economy, Satisfied Customers
The economy has pulled off something that seemed virtually impossible not long ago: strong economic growth and satisfied customers. While historically remarkable in itself, it is an even more impressive record compared to other countries. Over the past five years, U.S. economic growth has outpaced the other G7 countries by about 300%. In terms of customer satisfaction, the national ACSI score is steady at 77.9 (out of 100) as of the third quarter of 2024, nearly the highest it has ever been.
Consumer spending is, by far, the largest contributor to economic growth, and the degree to which buyers are satisfied/dissatisfied affects how much they spend. The advance estimate released by the U.S. Bureau of Economic Analysis shows 2.8% GDP growth in the third quarter and a 3.7% growth in consumer spending. Looking back over the past five years, recession, which caused economic havoc in many other countries, was largely averted in the United States. However, worldwide supply chain problems caused product shortages in the U.S. and a strong labor market led to shortages in the service sector. That, in turn, made consumer markets less efficient, causing inflation and diminished consumer power. During this period, customer satisfaction mattered less and the national ACSI score had its steepest decline ever. The stock market became exceptionally concentrated, with fewer than 1% of the listed companies accounting for more than one-third of its capitalization. It no longer rewarded companies that provided strong customer satisfaction with excess returns. Even though a recession was avoided, the markets did not function well.
Now, however, things have changed. While U.S. overall satisfaction holds stable since last quarter at a near record high, it is just 1.4 points higher than it was a decade ago. Companies still struggle with how to best allocate resources for improving the satisfaction of their customers.
While national customer satisfaction has not changed much, there are individual companies that show substantial ACSI movement. During the past decade, Bank of America, United Airlines, Cigna, HP, and Allegiant have seen double-digit percentage improvements in satisfaction. Dillard’s, Entergy, and Chrysler are among those that have lost significant ground over the last several years.
Most industries continue to have high customer satisfaction elasticity. The higher it is, the more customer satisfaction impacts demand. Banks, internet service providers, financial advisors, and wireless phone service are among the highest elasticity industries. They stand to lose or gain the most from how they treat their customers. Financial punishment and reward are generally lower for general merchandise retailers, gas stations, and supermarkets because demand is more responsive to price and location in these industries. Overall, however, there is no industry or company in the Index that is financially immune to changes in the satisfaction of their customers. The higher the elasticity, the greater the competition.
| 1st Quarter | 2nd Quarter | 3rd Quarter | 4th Quarter | |
|---|---|---|---|---|
| 2024 | 78.0 | 77.9 | 77.9 | |
| 2023 | 75.4 | 76.7 | 77.1 | 77.8 |
| 2022 | 73.1 | 73.0 | 73.5 | 74.4 |
| 2021 | 73.9 | 73.8 | 73.5 | 73.1 |
| 2020 | 74.3 | 74.1 | 73.9 | 73.6 |
| 2019 | 75.6 | 75.7 | 75.7 | 75.2 |
| 2018 | 76.7 | 76.2 | 75.9 | 75.6 |
| 2017 | 76.6 | 76.9 | 76.9 | 76.9 |
| 2016 | 76.3 | 76.2 | 76.4 | 76.7 |
| 2015 | 76.2 | 76.1 | 76.1 | 76.1 |
| 2014 | 76.5 | 76.4 | 76.5 | 76.5 |
| 2013 | 76.6 | 76.5 | 76.7 | 76.8 |
| 2012 | 75.9 | 75.9 | 75.9 | 76.3 |
| 2011 | 75.6 | 75.7 | 75.7 | 75.8 |
| 2010 | 75.9 | 75.9 | 75.7 | 75.3 |
| 2009 | 76.0 | 76.1 | 76.0 | 75.9 |
| 2008 | 75.2 | 75.1 | 75.0 | 75.7 |
| 2007 | 75.2 | 75.3 | 75.2 | 74.9 |
| 2006 | 74.1 | 74.4 | 74.4 | 74.9 |
| 2005 | 73.0 | 73.1 | 73.2 | 73.5 |
| 2004 | 74.4 | 74.4 | 74.3 | 73.6 |
| 2003 | 73.8 | 73.8 | 73.8 | 74.0 |
| 2002 | 73.0 | 73.0 | 73.1 | 72.9 |
| 2001 | 72.2 | 72.1 | 72.0 | 72.6 |
| 2000 | 72.5 | 72.8 | 72.9 | 72.6 |
| 1999 | 72.1 | 72.0 | 72.1 | 72.8 |
| 1998 | 71.9 | 72.2 | 72.3 | 72.6 |
| 1997 | 70.7 | 71.1 | 71.1 | 70.8 |
| 1996 | 73.0 | 72.4 | 72.2 | 72.0 |
| 1995 | 74.1 | 73.7 | 73.7 | 73.7 |
| 1994 | – | – | 74.8* | 74.2 |
*Baseline measurement taken in summer 1994
While companies today have more data about their customers, the analytics employed to turn data into information are for the most part not good enough. Customer satisfaction data have certain characteristics that make it difficult to obtain accurate estimates, to pinpoint what aspects of the customer experience need attention, and to gauge the financial impact of actions contemplated. Traditional statistical methods assume normal frequency distributions among the residuals, moderate multicollinearity, and low levels of data noise. Customer satisfaction data don’t meet these assumptions.
ACSI Analytics is designed to overcome these problems and thereby turning raw data into financially relevant information by:
- Separating signals from noise
- Moving from correlations and artificial intelligence (AI) patterns to cause-and-effect interpretations
- Calibrating measurement instruments toward profitability
Data is not the same as information—especially not data from consumer surveys. Management decisions require information; raw data must be filtered in order to be useful for decision-making. ACSI technology filters out data noise.
Management decisions require cause-and-effect information—something that current CX tools, whether based on AI or descriptive statistics, don’t provide. ACSI Analytics, on the other hand, is based on a causal model.
There is a wide disparity in the amount of consumer data collected by companies today. Some data suppliers use surveys with more than 200 questions per respondent, while others focus on responses to a single question. Neither is appropriate. Excessively long surveys may lead to straight-line responses. Good measurement techniques—whether in the social or physical sciences—typically require several measures (survey questions in this case) per product feature or service dimension.
Accuracy and relevance are what matters. To contribute to the business objectives at hand, the measurement instruments need calibration in ways similar to the physical sciences. This is why companies with high scores in the American Customer Satisfaction Index, which is calibrated to maximize customer loyalty, are financially successful, most notably in terms of stock returns and profitability.
No advertising or other promotional use can be made of ACSI data and information without the express prior written consent of ACSI LLC.