10 NPS Alternatives to Help You Better Understand Customer Behaviors

Net Promoter Score (NPS) is a simple metric to measure customer loyalty. It asks a customer to rate how likely they are to recommend your product or service to their family and friends, using a scale of zero to ten. Since its introduction in 2003, NPS has been adopted by leading companies across industries as a quantitative measure of customer sentiment. But here’s the thing: NPS doesn’t reflect actual customer behavior. That’s why marketers hoping to actually drive brand advocacy have sought NPS alternatives to help them better understand and influence their customers’ behavior.

When Harvard Business School conducted a qualitative survey of customers to supplement their understanding of NPS, they found that a significant share of respondents who answered an NPS survey would both actively promote and actively criticize a brand. For example, a consumer may be a regular customer at an outdoor retailer and answer favorably on NPS surveys, but actively discourage a more fashionable friend from purchasing clothing there.

Humans are complicated. Their feelings about brands are mutable and may depend on the person they are talking to or the product being discussed. Relying exclusively on NPS can give brands a skewed idea of what makes their customers happy.

Beyond the stated-intent problem described above, NPS has several well-documented limitations:

• It does not explain the “why.” A low score tells you a customer is a detractor, but not what drove that sentiment or what to fix.
• It is easy to game. Companies can inflate scores by surveying only satisfied customers or by coaching employees to solicit high ratings—making the metric unreliable as an internal KPI.
• It oversimplifies complex sentiment. Different customers rate the same experience differently based on personal expectations, recency bias, and cultural context.
• It does not predict churn well in isolation. Behavioral data—login frequency, product adoption, renewal history—often predicts churn more accurately than a recommendation score.

Brands seeking a more complete picture of customer loyalty should look beyond NPS to metrics that reflect what customers actually do—not just what they say they might do.

Here, we break down the most helpful alternatives for marketers and business owners who want to understand customer behavior and measure loyalty in ways that drive action.

1. Customer Effort Score (CES)

The Customer Effort Score (CES) tells you whether customers have a hard time performing certain actions with your brand, such as navigating online checkout or contacting a customer service representative.

While it may look similar to NPS in format, CES measures the amount of effort a customer actually has to exert to get something done with your company. It’s not a hypothetical metric — the feedback you receive is based on real customer experiences.

Usually, brands calculate CES by sending a customer a survey just after they perform an action with your brand. In that survey, ask “How easy was it to complete your purchase?” (or another desired action) and follow with a scale of answers ranging from “Very easy” to “Very difficult.” Some brands even use emojis instead of word-based responses.

To measure CES, collect survey feedback over a period of your choice (a month, a quarter, or any other time period). Then, total your highest responses (e.g., Easy and Very easy) and divide the number of positive responses by the total number of responses. Multiply by 100.

Number of positive responses / Total number of responses × 100 = CES

There is no universal industry standard to define a “good” CES. This is a metric you can define for your own company and track directionally over time.

Customer support interactions, onboarding flows, self-service UX, and ecommerce checkout. CES is particularly strong for identifying friction points that contribute to churn.

CES captures ease, not emotional attachment or overall satisfaction. It works best as part of a broader measurement stack rather than as a standalone loyalty signal.

2. Customer Satisfaction Score (CSAT)

Customer Satisfaction Score (CSAT) is a straightforward way to find out just how satisfied your customers are with your company.

CSAT is used at the very end of a customer’s interaction with a brand, closing the loop on their experience. Unlike NPS, which measures the likelihood of customer loyalty, CSAT is based on actual customer sentiment at a specific moment.

Send customers a short, one-question survey to measure your CSAT score. Ask, “How happy are you with [brand name]?” Collect survey feedback over a period of time (a week, a month, a quarter, or any time period of your choice).

Then, add up your highest responses (e.g., Happy and Very happy) and divide the number of positive responses by the total number of responses. Multiply that number by 100 to get your CSAT.

Number of positive responses / Total number of responses × 100 = CSAT

Post-purchase feedback, customer support interactions, onboarding completion, and product releases. CSAT is the most practical starting point for brands replacing or supplementing NPS because it is tied to specific interactions and gives teams clear signals about what to fix.

Limitation: CSAT measures short-term satisfaction at a touchpoint and does not capture long-term loyalty or predict whether a customer will return.

One way to make your customers happier is to reward brand advocates with targeted offers and incentives. Whether it’s a discount or a free shipping offer, rewards are a great way to make customers feel appreciated and nurture loyalty.

Learn more about building high-performing referral programs in Extole’s Referral Marketing Playbook.

3. Customer Retention Rate (CRR)

Customer Retention Rate (CRR) is a metric used to measure how many customers your company can keep over time.

This metric is a valuable alternative to NPS because it shows exactly how many customers you’re able to retain—a direct behavioral signal that stated recommendation intent cannot provide.

Customer acquisition costs have risen significantly across most industries, and retaining existing customers is meaningfully less expensive than acquiring new ones. Calculating your CRR helps shift the focus from acquisition-only thinking to a more balanced growth strategy.

CRR accounts for three factors: the number of customers you started with, the number you added over a period of time, and the number you ended with.

(Number of period-end customers – Number of period-added customers) / Number of period-start customers × 100 = CRR

Best for: Subscription businesses, SaaS, financial services, telecom, and any brand where recurring revenue depends on keeping customers engaged over time.

Limitation: CRR tells you how many customers stayed but not why. Pairing it with CSAT, CES, or churn surveys helps identify the drivers behind the number.

4. Customer Lifetime Value (LTV)

Customer Lifetime Value tells you the amount of revenue your company has gained from your customers. You can calculate it based on a single customer or a customer segment.

Unlike NPS, which only looks at the likelihood that a customer will refer your brand to a friend, LTV shows the real financial impact a customer has made on your company over time. It’s a tangible metric that’s a strong indicator of customer loyalty and satisfaction.

To calculate LTV, multiply customer value by the average customer lifespan.

Customer value × Average customer lifespan = LTV

To get your customer value, find your company’s average purchase value and multiply that number by the average number of purchases. Your average customer lifespan is the average number of years you retain customers.

LTV is useful for any B2B or B2C brand, but it’s particularly useful for companies with subscription-based products or services. This metric will point out trends across a multi-year relationship with a customer. It’ll also show you churn risks if you see sustained dips in revenue over time.

Best for: Growth strategy, customer acquisition investment decisions, and segmenting your most valuable customer cohorts for advocacy and referral programs.

Limitation: LTV requires good historical data to model accurately and is more complex to calculate than survey-based metrics. It is a financial outcome measure rather than a diagnostic tool.

5. Churn Survey

A churn survey collects insightful data about the factors that drive customers to stop using your products or services. It shines a light on how both internal and external factors impact customer behavior.

While some customers churn due to reasons you have no control over, many also leave as a result of issues you can remedy.

Causes of customer churn include:

• Frustrating user experience
• Poor onboarding process
• Unresponsive customer service
• Unmet goals or expectations

When designing a churn survey, keep in mind that customers might have little patience for lengthy questionnaires. The survey should be brief while collecting the most important information.

Deliver the survey using the channel customers are most likely to use. For example, you can send it by email or display it as a pop-up on your website.

Once you identify issues that erode the customer relationship, you can brainstorm a strategy to fix them.

Best for: Any brand that needs to understand why customers are leaving and which friction points are most responsible for attrition.

6. Post-purchase Survey

A post-purchase survey helps you understand:

• The reasons customers make a purchase
• The marketing channels that led them to your brand
• Any friction points that occurred during the shopping experience

It’s important to display this survey immediately after the customer completes the purchase because the experience is still fresh in their mind, and because they’re more likely to fill out the survey then.

Keep the survey brief, using a mix of open-ended and multiple-choice questions to gather as many insights as possible. Consider adding an incentive, such as a discount or free shipping, to get more responses and encourage customers to make a repeat purchase.

Best for: Ecommerce and retail brands looking to reduce checkout friction, understand attribution, and improve the post-purchase experience at scale.

7. Product Engagement Score (PES)

The Product Engagement Score (PES) measures user interaction with a software product. It allows businesses to measure their product performance and how customers engage with it.

To calculate PES, you need the following metrics:

• Adoption: The average number of features (core events) adopted by active accounts
• Stickiness: The percentage of monthly or weekly active users who use the product daily
• Growth: The number of new and recovered users or accounts divided by the number of users lost (churn)

Adoption rate + stickiness + growth rate / 3 = PES

By continually monitoring your PES, you can get valuable insights that will help you iterate and improve your product over time. It’s also helpful to calculate PES for different user segments, since customers in different demographics or life stages may interact with your product very differently.

Best for: SaaS companies and digital product teams that want a behavioral measure of how well the product is driving engagement, not just satisfaction.

Limitation: PES measures product usage but yields limited qualitative insight into why customers engage the way they do. Pairing it with open-ended feedback or user interviews provides the context that the score alone cannot.

8. Customer Health Score

A Customer Health Score is a composite metric that measures the overall well-being of a customer relationship by combining behavioral signals rather than relying on a single survey response.

Unlike NPS, which captures stated intent at one moment in time, a Customer Health Score continuously tracks what customers actually do. It aggregates signals such as:

• Product usage: login frequency, feature adoption, session depth
• Engagement: responsiveness to outreach, participation in onboarding or training
• Support history: volume of open tickets, severity of unresolved issues
• Business signals: renewal likelihood, upsell behavior, contract expansion

Each factor is weighted according to your business priorities and combined into a single score that indicates whether a customer is healthy, at-risk, or somewhere in between.

When a customer’s health score drops sharply, it flags an account for proactive intervention—before the customer raises a complaint or churns. When scores trend upward, they can identify customers ready for upsell or expansion conversations.

Best for: SaaS companies, B2B subscription businesses, and any brand using a customer success model. Health scores work especially well when behavioral data is already flowing through a CRM, CDP, or engagement platform.

Limitation: Health scores are internal and company-specific—there are no universal benchmarks, and building a meaningful one requires good data infrastructure. But that trade-off is usually worthwhile, because the insights are directly tied to your customer relationships rather than to an abstract recommendation score.

For brands already running referral and reward programs, health scores pair well with engagement data from referral share rates, advocate activity, and repeat reward redemption—giving teams a richer view of which customers are truly loyal versus simply satisfied.

9. Time to Value (TTV)

Time to Value (TTV) is another useful metric for analyzing customer experience. It refers to the amount of time it takes customers to get value from your product, or to put it another way, how quickly customers get a return on their investment.

TTV calculations may look different from one company to another. The first step is to define the following variables:

• Value: What is the primary value customers are looking to get from your product? Try to see it from a user perspective. As an example, a social media app might define this as the first time a user posts a video, or the first time a user interacts with a video.
• Start Point: From what moment do you begin measuring whether a customer has received value from your product? This could be once they purchase the product, open an account, finish onboarding, etc.
• End Point: What action or outcome indicates that a customer has reached your predetermined value?

End point (value realized) – start point = TTV

The best piece of advice regarding TTV is to aim for as small a number as possible. In a landscape where so many options are available for virtually every product and service, consumers usually expect to start seeing value soon after purchase—or they might begin to regret their decision.

Soliciting customer feedback that can supplement your TTV is a critical step in identifying ways to improve it. In doing so, you’ll not only shorten your TTV, you might also improve your CSAT and CRR.

Best for: SaaS and digital product companies focused on reducing onboarding friction and accelerating the moment customers realize why they chose your product.

10. Referral Rate

Referral Rate measures the percentage of your customers who actively refer new customers to your brand within a given time period. Unlike NPS, which asks customers whether they would recommend you, Referral Rate tracks whether they actually did.

This distinction matters. Research has consistently shown that stated recommendation intent is an unreliable proxy for actual advocacy behavior—customers regularly both promote and criticize the same brand depending on context and audience. Referral Rate cuts through that ambiguity by measuring real action.

How to calculate it:

Number of customers who made a referral / Total active customers × 100 = Referral Rate

You can track Referral Rate at the aggregate level or break it down by:

• Advocate segment: Which customers refer most frequently?
• Channel: Where do referrals originate—email, social, in-app?
• Incentive type: Which reward structures drive the highest referral conversion?

Best for: Ecommerce and consumer brands, subscription businesses, financial services, and any company that treats customer advocacy as a growth channel. Referral Rate works especially well alongside CSAT and repeat purchase rate as part of a behavioral loyalty measurement stack.

Why it belongs in your loyalty measurement toolkit: A rising Referral Rate signals that customers are not just satisfied—they are confident enough in your brand to put their own reputation behind a recommendation. That is a stronger loyalty signal than a score on a 0–10 scale. And unlike NPS, it connects directly to measurable customer acquisition outcomes.

Extole’s enterprise referral platform gives brands the tools to track Referral Rate at scale, understand which advocates drive the most high-quality referrals, and connect that data to the rest of their customer engagement programs.

Which of These NPS Alternatives Is Right for Your Business?

The right choice depends on what you are trying to measure and how your customers interact with your brand. Rather than replacing NPS with a single metric, most mature customer experience teams use a combination of metrics that work together to capture both sentiment and behavior.

Here is a practical starting point by business type:

The core principle: Survey metrics like CSAT and CES tell you what customers feel at a specific moment. Behavioral metrics like Referral Rate, Retention Rate, and Customer Health Score tell you what customers actually do over time. The most reliable picture of customer loyalty comes from combining both.

If you are just starting out, the simplest high-value stack is:

• CSAT for transactional feedback at key touchpoints
• CES for friction detection in support and onboarding
• Customer Retention Rate to validate that sentiment improvements are translating into real behavior

From there, you can add Customer Health Scoring, Referral Rate tracking, and Product Engagement Scores as your data infrastructure matures.

Get More Insights Into Customer Behavior With An Offer Program

When you deliver targeted customer incentives using Extole‘s offer management platform, you’ll get the opportunity to gather more data about your audience’s behavior.

Extole’s sophisticated reporting and analytics tools compile data on referral share rates, advocate relationships, audience segment performance, and more. Use this data to personalize marketing and build a stronger relationship with your customers.

NPS Alternatives FAQs

What Is the Best NPS Alternative?

There is no single best replacement for NPS—the right alternative depends on what you are trying to measure and how your customers interact with your brand. That said, here are the most practical recommendations by situation:

• If you want the most actionable single metric for most brands: Customer Satisfaction Score (CSAT). It is tied to specific interactions, easy to improve, and gives teams clear signals about what to fix.
• If you want the strongest predictor of loyalty after a support or service interaction: Customer Effort Score (CES). Research consistently shows that reducing customer effort is more strongly linked to retention than delighting customers.
• If you are a SaaS or B2B subscription business: Customer Health Score. It combines behavioral data—product usage, feature adoption, support history—into a predictive signal that surveys alone cannot match.
• If you want to measure actual advocacy, not stated intent: Referral Rate. Tracking how many customers actually refer others gives you a behavioral loyalty signal that is resistant to the biases that affect NPS surveys.

Most mature CX teams do not replace NPS with a single metric. They treat NPS as one signal among several, pairing it with CSAT, CES, behavioral data, and in some cases, referral and retention metrics that capture what customers do rather than what they say.

What Are Some Alternatives to NPS?

You can use the following metrics to measure customer sentiment and behavior:

• Customer Effort Score (CES)
• Customer Satisfaction Score (CSAT)
• Customer Retention Rate (CRR)
• Customer Lifetime Value (LTV)
• Customer Health Score
• Product Engagement Score (PES)
• Time to Value (TTV)
• Referral Rate
• Social Media Sentiment Analysis

Additionally, consider running targeted surveys such as churn surveys and post-purchase surveys to collect behavioral data at critical points in the customer journey.

Is CSAT or NPS Better?

CSAT and NPS have different goals. While CSAT measures customer happiness at a specific touchpoint, NPS attempts to quantify overall loyalty intent. Neither is universally better—CSAT tends to be more actionable for operational improvements, while NPS is more often used as a high-level benchmark. For most brands, using both together provides more signal than either does alone.

Is NPS Outdated?

Some marketers believe NPS is an outdated metric because it’s too general and doesn’t provide enough insights into the customer’s experience or journey. Janelle Dieken, the Senior Vice President of Marketing at Genesys, explains that NPS helps measure whether a business has met consumer expectations, as long as the results are positive. However, the metric is less effective when the results are negative because it gives little insight into what went wrong.

The more accurate framing may be that NPS is incomplete rather than obsolete. Most leading CX organizations still track it—but as one data point within a broader measurement stack rather than as a primary KPI.

What Is NPS 3.0?

The original creator of the Net Promoter Score, Fred Reichheld, developed NPS 3.0 to address the misuse and misunderstanding of the original NPS. The upgraded NPS 3.0 urges brands to consider a complementary metric, “earned growth rate.” This metric uses actual business results to highlight the quality and profitability of a brand’s growth when that growth is derived from an engaged customer base. It compares “earned customers” with their counterparts, “bought customers,” and highlights the growth that comes from the former rather than the latter.

Rather than relying on the potentially biased sample of customers who respond to NPS surveys, earned growth is based on the specific, measured revenues from all existing customers. NPS 3.0 is far more resistant to gaming, coaching, and response biases associated with non-anonymized NPS surveys.

NPS 3.0 is far more comprehensive than its older counterpart, but it is still stronger when supplemented by one or more of the behavioral metrics recommended in this article. The more data you have on customer behavior and sentiment, the more strategically you can improve your product and increase customer retention and value.