Surprised when a good client fires you? You’re not alone. Many professional services firms are caught by surprise when a client with no previous red flags or warning signals informs them they’ll be terminating a relationship that seems to be running smoothly.
One of the underlying culprits? It’s often attributable to Net Promoter Scores (NPS) and Customer Satisfaction (CSAT) surveys that have given providers a false sense of security about the true state of their client relationships. As we’ll unpack in this article, there are a few issues with using NPS and CSAT as operational metrics:
- Stale and outdated vs. real-time
- Anecdotal and inconsistent vs. scientific
- Easily manipulated and subjective vs. objective
Historical Perspective on NPS and CSAT
Professional services companies have used metrics like NPS and CSAT for years as ways to gauge client satisfaction and proactively identify clients who are at risk of churning. These tools have increasingly become utilized as barometers to measure customer sentiment in the absence of more accurate, strategic methods or methodologies. We’re now in an environment where companies have more choice than ever before, however. And in this environment, where new AI technology can provide real-time, predictive intelligence, the role of NPS and CSAT scores can and should be called into serious question.
When Real-Time Data is Needed, NPS and CSAT Data is Stale
One of the primary issues with NPS and CSAT scores is their inherent staleness. These scores are typically gathered through periodic surveys, often conducted every three, six, or even nine months. This infrequency means that the data collected does not reflect the current state of customer sentiment. As David Dewolf, Knownwell’s CEO, points out, “The vast majority of the time, NPS and CSAT data is stale. You cannot ask your customers a question every single day and have real-time data on it.”
This lag in data collection means businesses are often making decisions based on outdated information. In a rapidly changing business environment, having actionable, real-time data is crucial. The delay between changes in a customer’s experience and sentiment and the survey response can lead to significant gaps in understanding and addressing customer needs.
Anecdotal and Inconsistent Nature
Another significant problem with NPS and CSAT is their anecdotal nature. These scores are based on subjective customer responses, which can vary widely depending on individual personalities, experiences, and even the phrasing of survey questions. “It’s anecdotal, it’s not actual data,” David says. “There’s no standard.”
The subjectivity of these metrics means they can be easily skewed. For instance, some customers may never give a perfect score, while others may give high scores indiscriminately. This variability makes it challenging to draw meaningful conclusions from the data. Moreover, external factors, such as a customer’s mood or recent unrelated experiences, can unduly influence their responses.
Misleading and Manipulative Practices
There are also instances where NPS and CSAT scores are manipulated, either intentionally or unintentionally, by those administering the surveys. Account managers and service representatives may time their surveys strategically to coincide with successful project completions or positive interactions, thus inflating the scores. Courtney Baker, Knownwell’s Chief Marketing Officer, says, “Account managers know when to send these surveys. They’re sharp people. They know when they just launched a project that went really well, and that’s when they’re going to send the survey.”
Additionally, the pressure to achieve high scores can lead to manipulative practices. David recounts an experience where a service provider explicitly asked for a perfect score, explaining that their compensation depended on it. This practice not only undermines the validity of the scores but also erodes trust between customers and service providers.
The Disconnect Between Scores and Reality
Despite good NPS and CSAT scores, businesses can still experience unexpected churn and client dissatisfaction. This paradox highlights the fundamental flaw in relying solely on these metrics to gauge customer satisfaction and loyalty. David shares an anecdote about a client who consistently gave high scores but terminated their contract unexpectedly. This incident underscores the disconnect between reported satisfaction and actual business outcomes.
The reliance on these scores can create a false sense of security. Businesses may believe that their relationships with clients are strong based on high NPS or CSAT scores, only to be blindsided by churn or dissatisfaction. This discrepancy suggests that these metrics do not capture the full complexity of customer relationships.
A Call for Real-Time, Data-Driven Insights
The limitations of NPS and CSAT underscore the need for more robust, real-time, and data-driven approaches to understanding customer satisfaction. Mohan Rao, Knownwell’s Chief Product Officer, suggests, “In a digital world, the best way to do this is to make these metrics come out as a byproduct of customers using your service.” By leveraging the vast amounts of data generated through digital interactions, businesses can gain more accurate and timely insights into customer satisfaction.
For example, software companies can track application usage data to understand how customers interact with their products. Metrics such as login frequency, session duration, and feature usage can provide a more comprehensive, real-time picture of customer engagement and satisfaction. Similarly, e-commerce platforms can analyze transaction data and customer behavior to gauge satisfaction without relying on periodic surveys. And services firms can tap into emerging AI platforms like Knownwell that sift through vast amounts of unstructured data to measure customer sentiment and provide proactive intelligence.
The Role of AI in Customer Insights
Artificial Intelligence (AI) offers significant potential to revolutionize how businesses measure and understand customer satisfaction. AI can process vast amounts of unstructured data from sources like emails, chat logs, call transcripts, and social media interactions to extract meaningful insights. By analyzing this data in real-time, AI can identify patterns and trends that traditional surveys might miss.
David notes that businesses already possess a wealth of untapped information: “The vast majority of organizations have tons more information than they’re even looking at already sitting as exhaust of their business.” By harnessing AI to analyze this data, businesses can gain deeper, more actionable insights into customer satisfaction and behavior.
Why It’s Time to Augment NPS and CSAT Scores with Something More
While NPS and CSAT have been valuable tools in the past, their limitations are becoming increasingly apparent in today’s fast-paced, data-driven world. These metrics are often stale, anecdotal, and susceptible to manipulation, making them unreliable indicators of true customer satisfaction and loyalty.
To stay competitive and responsive to customer needs, businesses must embrace real-time, data-driven approaches to understanding customer satisfaction. Leveraging AI and the vast amounts of data generated through digital interactions can provide more accurate, actionable insights, ultimately leading to better business outcomes and stronger customer relationships. As we move into the future, it’s clear that the old ways of measuring customer satisfaction need a significant overhaul—and AI can help.
Learn More
For more, read key takeaways from our AI Knowhow episode, Why NPS and CSAT Hurt More Than They Help. You can also watch the full episode via the embed below or directly on YouTube. And you can listen on Apple Podcasts, Spotify, or wherever you get your podcasts.
