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National Economic Indicator

U.S. Overall Customer Satisfaction

U.S. Customer Satisfaction at Record High

Q4 2023: The American Customer Satisfaction Index (ACSI)

In 2023, and especially in its final quarter, the U.S. economy showed remarkable vigor: GDP, labor markets, consumer spending, household income, productivity and the stock market – all improving at a healthy rate. The rate of inflation dwindled close to its long-term average and customer satisfaction surged to an all-time high.

This is a far cry from two years ago, when US customer satisfaction, following years of decline, reached its lowest point in 20 years due to COVID, supply chain obstacles, high inflation, product shortages, and poor customer service.

Over the past six consecutive quarters, there have been substantial improvements in customer satisfaction. In the final quarter of 2023 ACSI rose by 0.9% – to a record score of 77.8 (on a 100-point scale). In part, the increase is due to the impact of more contemporaneous data, made possible due to larger samples.  A total of 212,512 survey questionnaires were completed in 2023 (about 53,000 each quarter). The graph shows 2017 as the starting date for updated data. As a result of near real-time updating, ACSI is now more precise and more likely to detect rapid changes in customer assessments of quality, value, service and satisfaction, etc.

Many of the problems caused by COVID, supply chains, and uneven service quality have dissipated. There has also been a return to traditional competition among sellers, and fewer shortages of product and service personnel. Another change is a drop in consumer expectations. While small, it does lower the bar for creating satisfied customers.

Among the greatest beneficiaries of these improvements have been gas stations, hospitals, social media, and personal computers. They are among the businesses that have seen the greatest increase in customer satisfaction. As far as individual companies are concerned, there are several in other industries that stand out with both high levels of customer satisfaction as well as major improvements: Macy’s, Hyatt Hotels, Amazon Prime Video and Avis Car Rentals are among these.

There is one remaining economic anomaly, however. As evidence of a well-functioning economy, companies with superior customer satisfaction usually have superior stock returns. The positive relationship between strong customer satisfaction and positive abnormal stock returns has yet to recur. It is not that the stock returns on customer satisfaction have been weak, but they have not outperformed the market the way that did in the past.

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.

1st Quarter 2nd Quarter 3rd Quarter 4th Quarter
1994 74.8* 74.2
1995 74.1 73.7 73.7 73.7
1996 73.0 72.4 72.2 72.0
1997 70.7 71.1 71.1 70.8
1998 71.9 72.2 72.3 72.6
1999 72.1 72.0 72.1 72.8
2000 72.5 72.8 72.9 72.6
2001 72.2 72.1 72.0 72.6
2002 73.0 73.0 73.1 72.9
2003 73.8 73.8 73.8 74.0
2004 74.4 74.4 74.3 73.6
2005 73.0 73.1 73.2 73.5
2006 74.1 74.4 74.4 74.9
2007 75.2 75.3 75.2 74.9
2008 75.2 75.1 75.0 75.7
2009 76.0 76.1 76.0 75.9
2010 75.9 75.9 75.7 75.3
2011 75.6 75.7 75.7 75.8
2012 75.9 75.9 75.9 76.3
2013 76.6 76.5 76.7 76.8
2014 76.5 76.4 76.5 76.5
2015 76.2 76.1 76.1 76.1
2016 76.3 76.2 76.4 76.7
2017 76.6 76.9 76.9 76.9
2018 76.7 76.2 75.9 75.6
2019 75.6 75.7 75.7 75.2
2020 74.3 74.1 73.9 73.6
2021 73.9 73.8 73.5 73.1
2022 73.1 73.0 73.5 74.4
2023 75.4 76.7 77.1 77.8

*Baseline measurement taken in summer 1994
Download Excel file of National ACSI Scores


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