Why NPS doesn’t work any more, and what’s the alternative?


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“How likely are you to recommend our product and services to a friend or colleague”?

There are few questions in customer experience where the answers have been so deeply attributed to growth potential, profitability, and investor strategies. Net Promoter Score has for years been billed as “The one number you need to grow”. And much like B2C, NPS has been used as the gold standard in B2B to benchmark customer satisfaction and potential loyalty.

I would argue though that NPS is inherently flawed and a measurement of the past.

Customer experience has become too complex and nuanced for a narrow, largely inactionable metric. Customer service and support teams are already re-evaluating their options. Gartner predicts that 75% of organisations will abandon NPS as a measure of success for customer service and support within two years.

Before we explore some of the alternatives for your business, why doesn’t NPS work any more?

The psychology behind NPS revolves around gauging customer loyalty and satisfaction by measuring the likelihood of them recommending a product or service to others. However, NPS falls short in establishing a long-term efficient system for several reasons:

Limited insight – NPS primarily focuses on a single question about likelihood to recommend, providing a narrow perspective that may not capture the complexity of customer experiences.

We’re scoring intent not behaviour – saying you will do something doesn’t mean you will actually do it. The survey is static. It doesn’t tell you what customers do next. NPS is typically measured at a specific point in time, offering a snapshot of satisfaction. This static approach also doesn’t reflect the dynamic nature of customer opinions and perceptions over the long term.

Inadequate context -the score lacks detailed context as it doesn’t delve into specific aspects of the customer experience, making it challenging to identify and address specific issues. Even with the addition of an open ended question NPS tends to lack any meaningful context.

It’s a lagging indicator – large-scale NPS surveys can take time to complete, and then it takes time to analyse the results.

Overemphasis on promoters and detractors – NPS often concentrates on classifying customers as promoters, passives, or detractors, oversimplifying the diverse range of customer sentiments and nuances that impact long-term relationships.

Multiple buyers – in B2C, the buyer is usually an individual who has specific needs and expectations. In B2B there are around ”6-10 buyers” and stake holders, according to Gartner, in the average buying group. Senior executives, who sign-off contracts and renew subscriptions, have different expectations, needs, concerns and priorities than your regular contacts, who are probably filling out your survey. There’s a big risk that you are surveying the wrong people and missing the feedback of the people who influence the relationship.

Long journeys – a buying team or user’s willingness to recommend could change as they move through a buying journey. The member who has bought a new software solution could be a ‘9’ during the purchasing process. But a poor user experience could make them a 7 or below if they encounter usability issues.
Human nature – people are more inclined to report a poor experience than a good one. Your ‘promoters’ might not bother to fill in the survey is they were satisfied and wanted to leave it at that.

Should you just update your NPS strategy?

At a minimum, you could ask different questions on your NPS surveys to better understand customers. You could change your ratings or redefine ‘promoter’, ‘passive’ or ‘detractor’ ranges. You could add an open-ended question. But this makes NPS bespoke to you and difficult to benchmark against competitors. The same limitations apply to the score.

With all of this in mind, what are the alternatives to give you actionable insights on what customers think of doing business with you, what’s driving their loyalty and willingness to refer. B2B is built on referrals. What’s causing churn and what needs fixing? There is a better way.
What’s the alternative to NPS?

An alternative approach for a more efficient long-term feedback system could involve implementing a comprehensive customer feedback mechanism that includes a mix of qualitative and quantitative data. This could include AI-powered customer intelligence, detailed surveys and customer interviews to provide a more nuanced understanding of customer experiences, enabling businesses to make informed decisions and improvements over time.

AI-powered customer intelligence – there is no shortage of AI-powered customer intelligence platforms to give you analytics to drive your measurement strategy. Let me give you an example. NPS only tracks intent to refer. With an enterprise-grade customer intelligence platform / referral marketing platform you can track and measure actual referrals.

There is a significant opportunity here. As reported on Fast Company, 80% of organisations have yet to adopt AI or predictive routing for CX measurement. Customer intelligence platforms also surface real-time (and historic) qualitative insights. CX leaders are pulling ahead by capturing insights they need on their customers’ behaviour, preferences, emotional state and intent.

Customer lifetime value – this can be calculated on a single customer – or segment. An increase in customer LTV is a tangible business result. There’s a free customer service metrics calculator here to help you get the data you need to calculate LTV.

You can also measure churn rates, retention rates etc. The list is long depending on the business goal you want to achieve.

Product engagement score (PES) – have you thought about introducing a product engagement score? Unlike NPS and other surveys that give you limited insights on satisfaction, PES measures how customers interact with your product. This can help you strengthen the three elements: adoption, stickiness and growth.

Product market fit (PMF) – you could ask customers a simple survey question – how they would feel if your product was no longer available to them? Would they miss it? The test originates back to Sean Ellis, the first marketer at DropBox. Group respondents into 4 cohorts ranging from “very disappointed” to “somewhat disappointed” to “not disappointed” to “I no longer use this product”.

Adoption rate, customer effort etc. There are so many options depending on the business, metrics, and measurement models and approuch.

Tip: Ellis created the ‘40% rule’, which is a common metric for benchmarking survey results. If 40% of your customers would be “very disappointed”, or they view it as a “must have” then you’ve created a product that fits into your market.

Respondents who answer “very disappointed” if your product was no longer available to them are is your insights gold mine. Your customers in this group could also be your best salespeople.

Supplementary surveys – NPS has been elevated to “cherry” status on top of a layered cake of customer experience metrics like value enhancement score (VES) to predict loyalty outcomes (retention, positive word-of-mouth, wallet share). Customer satisfaction score (CSat) and customer effort score (CES). Arguably feedback via these surveys can give you a fuller picture of your CX – especially for service and support. There is scope to add qualitative questions to get to the why customers may feel a certain way, and why they do the things they do.

But these types of surveys also arguably have a limited shelf-life. Read our recent post What’s next in VoC as traditional customer surveys fade from our memories?

to find out why.

To conclude

While NPS provides a quick and easy metric, it is often criticised for being overly simplistic and providing only a surface-level understanding of customer satisfaction. It focuses on the likelihood of recommendations but may miss the intricacies of the customer experience. NPS is transactional in nature, concentrating on a single point in time and categorising customers into promoters, passives, or detractors. This categorisation oversimplifies the complexity of customer relationships and fails to capture the ongoing dynamics and evolving expectations of customers.

In essence, NPS is considered a part of a short-sighted view of customer transactions because it doesn’t provide the depth and richness of insights needed for building lasting, meaningful customer relationships over the long term. There are alternatives to give you a more granular, deeper understanding of customer relationships. Three-quarters of companies are already rethinking NPS when it comes to service and support. Are you rethinking your strategy? Change could require a different mindset at the top about how the business needs to shift from using metrics like to NPS to measuring tangible business outcomes.

What did I forget to mention in my original article?
Recognizing the oversight in our exploration of NPS alternatives, it’s crucial to address the often overlooked yet immensely impactful factor of cultural nuances in the context of Net Promoter Score (NPS). The cultural dimension significantly influences how customers express satisfaction and loyalty, and a one-size-fits-all approach, as exemplified by NPS, may inadvertently neglect these subtleties. Cultural diversity can manifest in varied expectations, communication styles, and preferences, ultimately affecting the accuracy and relevance of NPS metrics across different demographics and regions. Therefore, any discussion about evolving customer experience measurement must consider the necessity of culturally sensitive metrics that resonate with diverse populations. By acknowledging the role of culture in shaping customer perceptions, businesses can refine their strategies, ensuring a more inclusive and accurate representation of customer satisfaction in an increasingly globalized market.

This article was originally posted at: https://www.eglobalis.com/why-nps-doesnt-work-any-more-and-whats-the-alternative/

Your thoughts will be greatly appreciated.


NPS: A Misleading Metric For B2B In Unprecedented Times? https://www.forbes.com/sites/peggyannesalz/2020/12/03/nps-a-misleading-metric-for-b2b-in-unprecedented-times/

How to Calculate Customer Lifetime Value (CLV) & Why It Matters https://blog.hubspot.com/service/how-to-calculate-customer-lifetime-value#clv-formula

Definitive Guide to Net Promoter Score https://www.salesforce.com/eu/learning-centre/customer-service/calculate-net-promoter-score/

Is the Net Promoter Score dead? Why it may be time to look beyond this metric

How customer sentiment analysis improves the customer experience https://www.zendesk.co.uk/blog/customer-sentiment-analysis-improves-cx/

Beyond Net Promoter Score: Customer Experience Measurement Reimagined https://hbr.org/resources/pdfs/comm/Genesys/BeyondNetPromoterScore.pdf

Using Sean Ellis Test For Measuring Your Product/Market Fit https://productcoalition.com/using-sean-ellis-test-for-measuring-your-product-market-fit-c8ac98053c2c

Gartner Predicts More Than 75% of Organizations Will Abandon NPS As a Measure of Success for Customer Service and Support by 2025 https://www.gartner.com/en/newsroom/press-releases/2021-05-27-gartner-predicts-more-than-75–of-organizations-will-

Ricardo Saltz Gulko
Ricardo Saltz Gulko is the founder of Eglobalis and the European Customer Experience Organization. He is a global strategist specializing in B2B enterprises, with a focus on Customer Experience, Professional Services, Design and Innovation, as well as data-driven services. Ricardo empowers major global enterprises to generate new revenue and enhance market competitiveness through the delivery of exceptional global CX, and he employs design to drive adoption and growth. The end results of his work include high growth, increased retention, loyalty, innovation ignition, adoption and growth.


  1. I believe the only flaws are in the implementation. Cultural or team differences are accounted for, it is not just a point in time (that is transactional) there is also relationship. I do thing there are certain industries where other measures are better or a combination of measures. But by and large the biggest issue I see is that a statistically relevant tool needs people who understand metrics and research. We also need people to stop reading the headlines of – the one questions and seek to understand the rest based on maturity. I don’t think in-depth analysis has created the flaws it is the lack of capability around in-depth analysis and statistical relevance.

  2. While I respect Ms. McSweeney-Grant’s credentials, I have fundamental differences with her assertion that “the only flaws are in the implementation.” Many very accomplished research and marketing science practitioners, after rigorous analysis, have found multiple issues and concerns with the metric itself. In my 2012 book for ASQ, “The Customer Advocate And The Customer Saboteur”, I devoted an entire chapter – 25 pages worth (out of 363 pages) – to thoroughly evaluate the reality and unreality of recommendation/referral as a core CX KPI and metric. Here’s just a small sample of content from that chapter:

    “Recommendations are a key goal, but are they the main thing? Most customer management research practitioners argue that, while recommendation and referral are important (as is an unwillingness to recommend or refer), much more needs to be understood about customer decision and behavior dynamics.

    Recommendation is undeniably one of the principal outcomes of loyalty behavior, but certain pundits seem to be preaching from bully pulpits that recommendation is a prime indicator—in fact, the single or only predictor—of the construct, itself. There are numerous, serious limitations to this concept. It should be quickly recognized and understood that it’s possible, for example, to incentivize customers, and they will refer, once compensated and rewarded to do so. If companies, in effect, buy referral and recommendation—and it can easily be accomplished—what happens to the value of the metric? It’s very, very strongly compromised.

    There are many more problems with putting too much emphasis on recommendation and referral. One of these problems is that if other information is available about customer behavior, as it often is through targeted research, the over-focus on a single number suggests that these insights will receive less consideration and relevance. For example, if a company discovers that it has a high incidence of unresolved customer complaints, that serious loyalty-leveraging situation can get brushed aside as executives seek to create ever-higher positive recommendation levels.

    Also, companies using a single net recommendation “score” should understand that it can be obtained in multiple ways. In other words, a 40 percent recommendation score could be the result of 65 percent positive recommendation minus 25 percent negative recommendation or a 45 percent positive recommendation minus 5 percent negative recommendation. Yet, these two net scores represent entirely different customer referral scenarios. Though the first scenario might create some cause for concern because of the level of negative recommendation, the second scenario is far more serious because of the lower level of positive scores, suggesting that many customers are potential candidates for churn.

    Additionally, the use of alternative customer research methods to identify key drivers of loyalty—such as multi-question indices and models and probability allocation (assigning probabilities to events, including purchase activity or informal communication)—have been found by numerous customer loyalty research methodologists to correlate much more closely with actual customer behavior than willingness to refer or recommend. While I understand that these approaches lack the appeal of one-number simplicity, I believe they represent far greater accuracy and “actionability.”

    Finally, we’ve evolved to a time where most marketers live in a one-to-one customer communications, measurement, and management world. Linkage must be made between individual customer-detailed expressions of loyalty and customers’ estimated lifetime value. So, perhaps the biggest challenge with a net recommendation score is that it’s usually presented on a grouped, rather than specific customer, basis. Customer-level information systems can help leverage profile and loyalty research data, enabling marketers to understand behavior on an individual basis; but an aggregated score such as net recommendation offers no such flexibility. At the end of the day, this may be one of the measure’s more serious drawbacks.”

  3. Great points of view! I appreciate the diverse perspectives shared on the efficiency and POV of NPS, Ms. McSweeney and Mr. Lowenstein . It’s evident that every expert brings a unique viewpoint to the table. In my experience at Samsung many LOB, we’ve taken a different stance on NPS, recognizing its limitations as a somewhat transactional metric. It’s heartening to see that opinions and approaches to NPS vary widely among professionals. Living in democracies allows us the privilege of expressing our distinct views and sharing our diverse experiences with NPS. I believe this open dialogue is essential for fostering growth and understanding within our industry. Thank you both for contributing your thoughts to the conversation. Have a lovely season! Ricardo

  4. I agree, NPS only tells you whether you will buy again at that point (not much later) or recommend at that point. It gives no further information. You need to measure value.
    Many concepts are flawed or used wrongly like NPS, CRM and maybe even experience the wat it is being used now, as a catchall for everything

  5. Very well thought out piece Ricardo. NPS was an attempt at quantifying something that is, by definition, a qualitative experience. It thrives because the numbers give it an illusion of tangibleness.

    The tangible outcome of CX is (and has to be) profit or, in the case of non-profits, goodwill. CX achieves profit by increasing customer revenue and/or decreasing customer churn – the CLV equation. Unfortunately, most attempts to quantify the degree to which CX is actually contributing to this are convoluted at best.

    I do think the idea of finding a simple metric is important – because complex ones will never get traction throughout an organization. I just don’t think NPS is it.

  6. Hi Shaun, thank you for sharing your thoughts, and I completely agree with you regarding the relationship between CX, profit, and the Customer Lifetime Value (CLV) equation. and what you mention here ( Unfortunately, attempts to quantify CX’s impact often become convoluted.) I share your belief in the importance of finding a simple metric, as complex ones struggle to gain traction across an organization. Interestingly, I recently spoke with a Swiss company pursuing a different approach aligned with our mutual views. I believe we’re not yet at the point where a single metric suffices in B2B. I advocate for drawing conclusions based on a comprehensive 360-degree approach using a mix of diferent metrics and measurements depending the organization. Connecting revenue and CX is achievable by measuring the current situation and continuously assessing the progress of CX programs in this ever-evolving landscape but many struggle with it, maybe teh challenge is the accurancy of it to the cents. While we’ve seen positive results in some B2B companies, perfection remains elusive. Thanks for your insights, and I wish you and yours a wonderful holiday season. Ricardo

  7. Echoing Shaun’s point, and expanding on it a bit, a simple metric is important and sorely needed, if it is both real-world and actionable against business outcome goals. Since 2005, colleagues and I have been using, and continually refining, a b2b and b2c customer advocacy and commitment research tool which has proven reliable…..and universally actionable: https://www.linkedin.com/pulse/leveraging-word-of-mouth-advocacy-drive-customer-michael/

  8. Ricardo, NPS never worked. It was convenient and made firms look good: great for CEOs to boast about.
    But it did an indication of whether a company was preferred or not


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