How do you really know if your customers are satisfied? It’s a question businesses have wrestled with forever. But maybe the answer isn’t about finding the right method, but the right approach.
It’s like peeling back layers, uncovering the truth bit by bit. We’re ready to dive in and solve this puzzle—starting with this post.
4 Customer Satisfaction Metrics To Track
1. Overall perception(Attitudinal)
The overall perception of customer satisfaction is driven by the customer's end-to-end experience with a product or service.
Interestingly, the core of this attitude depends on the solution offered. Favorably, for a pressing problem that makes customer life easier at least temporarily.
The overall perception is shaped by:
- Value
- Quality
- Convenience
Not just these, there are other factors such as empathy, ease of access, and simplicity of process.
In a nutshell, the entire perception of customer satisfaction is the availability of a solution at the right time. More importantly, the one that meets the needs of the customer. They either say ‘This is the best there is’ or ‘Thank god, I found this’.
Here’s how you can measure this for two different products:
Ask a customer to rate their overall experience with the product (CSAT).
There’s another NPS question you might want to ask.
For Robinhood, a retail investment app, you can ask a CSAT question:
For NPS, you can ask.
Plus, these tips could help you get to the skin of feedback:
- Evaluating the severity of the problem solved—helps in assessing the drivers that led to using your product such as How would you rate the severity of the issue you are experiencing?
- Go beyond the surface and ask the root of the problem—How does this problem impact your daily operations or personal use?
2. Customer Loyalty Measurement (emotive, behavioral)
While traditionally customer loyalty is the willingness to make a recurring purchase, another aspect is preferred—a recommendation to others.
Here’s a question that can help you understand the sentiment of customer loyalty.
For a product like Canva, it could be:
Helps in determining the continuity of using the product.
For a retail investor app like Robinhood, it can be:
Determining future engagement for the fintech app.
For every detractor or passive response, here are two follow-up questions to give you better insights:
- What is the primary reason for your score?
- What could we do to improve your score?
Next, it’s critical to find out the repurchase intent to know if your product still is a crowd puller. Start by asking:
"How likely are you to purchase from us again in the next [X] months?"
Even if you get a high score on repurchase intent, a sizable number of customers may not be willing to recommend. It'd be due to reasons such as good product but lacking innovation or cost-effective but prone to complacency.
Other reasons could be due to customers finding initial value but might not recommend it to others fearing a tarnished reputation.
You might want to split these users into cohorts and survey them again for more granular insights.
3. A series of attribute satisfaction measurements(Affective, Cognitive)
While customer satisfaction is normally based on touchpoints or interactions, there’s another component called Attributes.
Attributes, from a psychological perspective, determine the liking or disliking of a product. If the product is good enough but does not empower users to solve key problems without external help, it is not worthy of a recommendation.
For instance, a user using an HR SaaS product may not feel empowered when they can’t create an onboarding flow for 50 new employees. It’s okay but not great.
One question to find out is: How much do you enjoy using our product daily?
The other attributes are reliability and durability. You might ask yourself these questions such as:
- Is the product experience great when onboarding employees from different teams?
- How often are users facing errors that stop them from smoothly using our product?
This opens up a necessity to create a reliable and efficient infrastructure for your products.
Cognitive factors influence a user’s perception vs expectations. This is followed by the validation of a product that should be delivered to solve a problem.
Even expect it to be a repurposed entity—a product or feature that is perceived to solve a problem outside its original purpose.
That’s best measured by How well does our product meets your needs or solves your problems?
Other questions include:
Assess satisfaction level.
Evaluate ease of use.
4. Intention to recurring purchase measurements(Behavioral measures)
When it comes to recurring purchases, users are more likely to rebuy based on customer equity. Now, customer equity is the sum of all the customer lifetime values of current and future customers.
When we further break it down, three factors drive repurchase:
- Value equity—If the perceived value of the product is higher than the actual value, then there is a value gap, that affects the repurchase rate
- Brand equity—the elements such as brand recall, customer service, high quality, and price involve brand equity that influences a brand’s relationship
- Relationship equity—Relationship equity includes the interactions and customer experiences that influence a positive or negative relationship
Here are some of the questions you might want to ask:
Renewal or repurchase.
Upgrade or downgrade intent.
Recurring purchase on a fintech app.
Assess upgrade intention.
Here are two additional questions you might ask:
- What do you associate with our brand? (e.g., quality, reliability, innovation)
- What improvements would enhance the value of our products/services for you?
What Is The Best KPI For Measuring Customer Satisfaction?
There’s no single best KPI for measuring customer satisfaction. Instead, these three KPIs can help you with a well-rounded answer.
1. Usage metrics
The amount of time users spend using a product is a major indicator of their affinity towards their product.
In case you need a better picture of how regularly your product is used, you’d want to find out usage frequency, feature adoption rate, and time of use.
Take a look at the instances of usage by taking a look at metrics like DAU and MAU. See the monthly and daily trends to assess progress. Another metric that is also worth monitoring is the average session length, comparing the length for each user since sign-up. Session interval indicates the break between two sessions, the shorter the session, the higher the usage.
If you want to calculate the daily users who use the product, divide the DAU by MAU to find your stickiness ratio. This shows the percentage of daily users against monthly users. A high stickiness ratio means more engagement while low rates could mean wrong audience targeting, poor onboarding, etc.
Here are a few examples to help you understand better. Netflix uses median hours per month, Headspace has mediation sessions per week, Swiggy measures orders per week, and Hubspot uses WAU.
2. NRR
Net Revenue Retention or NRR is a better reflection of customer satisfaction since it factors in both existing and new customers. It includes both churned and expansion(upselling, cross-selling, upgraded) customers.
This gives the fuller picture because it creates a distinction between new customers, current customers, and churned customers. This is something that ARR and MRR lack.
While a NRR of > 100% indicates higher customer satisfaction because of retention while < 100% indicates churned revenue such as cancellations, non-renewals, and downgrades.
You might want to look at the trends and patterns such as:
- Compare with CSAT and NPS survey data for questions like "How likely are you to purchase from us again in the next [X] months?"
- Assess the positive opinion of your brand with What do you associate with our brand? (e.g., quality, reliability, innovation)
- Check for any spikes or dips excluding seasonal fluctuations—analyze the reasons for other changes
- Measure the satisfaction by comparing it with cohorts such as regular users, high-value users, and churners
3. Cohort retention
Segmenting users as cohorts can help you track changes in usage and engagement levels. For instance, you could create 3 cohorts based on events completed, sign-up dates, time to the first value, etc to identify trends over weeks and months.
This can help you understand attributes like feature usage, stickiness ratio, potential churn signals, and drop-offs to benchmark against your high-performing and low-performing cohorts.
The only reason cohorts water down is when you have too many. We recommend having cohorts where there are at least 200 users so you can reach statistical significance.
To top it off, you can segment users who have a higher ARPU compared to the cost to acquire them. By analyzing the actions and behavior using heatmaps, you will be able to know what makes your users satisfied.
In the end…
Customer satisfaction shouldn’t be a numbers game. Beyond the surface, you must be able to take a peek at the attitudes, emotions, behaviors, and cognitive elements that bring out the “actual” data to light.
