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8000+ teams use Hiver to delight their customers!
Ever heard a company CEO say measuring customer satisfaction is not crucial to the success of their company?
We’re sure not.
According to Forbes.com, bad customer service costs $338.5 billion globally each year. In the US alone, that’s about $83 billion, or an average of $289 per lost relationship.
Most companies today ackowlegede the fact that good customer service has a profound effect on reducing customer churn, and eventually improving the bottom line. Measuring customer satisfaction has, therefore, become a key function in most Fortune 500 companies.
Apart from the growing competition, one compelling reason behind companies’ increasing focus on customer centricity is to meet the expectations of today’s ever-demanding customers. Customers are now more vocal than ever. They voice their opinions to the company; they share their experiences on social media; they share stories with friends and colleagues. Basically, they no longer sit down and take it if they’ve had an unpleasant experience with a product or a service.
Word-of-mouth and personal recommendations have become active drivers for business growth. Satisfied customers are very likely to put your company’s name forward.
Businesses, whether they want to or not, have no choice when it comes to satisfying customers. In fact, measuring customer satisfaction and implementing customer feedback is what differentiates a thriving company and from one that’s just surviving.
Companies might be growing in revenue, but that doesn’t always translate to customer satisfaction. There are several other factors that can have a profound effect on your bottom line – increase in marketing spend, product integrations, and more.
Now that we cannot rely solely on revenues to know if the customers are happy, it makes sense to employ other metrics for measuring customer satisfaction.
The role of customer departments in companies has evolved from solving problems to building lasting relations with customers. They now take a longer-term view of the relationship and strive to provide as much value from the product as possible.
There are four major methods which can help us understand how satisfied customers are with the product:
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- Ask for direct feedback for measuring customer satisfaction
- Analyze customer data without talking to them
- Analyze customer support data for measuring customer satisfaction
- Monitoring social media for measuring customer satisfaction
Ask for direct feedback for measuring customer satisfaction
There is nothing more accurate than the customer actually telling you what they feel about your product or how would they rate your product on a given aspect.
A great way to do this is by asking short questions and collating the results into key customer experience metrics. You can use a customer feedback software of your choice to answer these questions. Let’s jump in.
Net Promoter Score (NPS)
If we put it in the simplest of words, Net Promoter Score is the result you achieve when you survey your customers with the ‘would you recommend’ question. It has become the most ubiquitous metric for measuring customer satisfaction in SaaS. It is also the most reliable as it instantly captures the customers’ sentiment about your product.
The one reason this survey is the most popular is its simplicity. It asks one very simple question to every customer:
“Would you recommend the product to your friends or colleagues?”
People who rate you 0 through 6 are known as “Detractors”, those who rate you 7 or 8 are known as “Passives”, and those who give you a 9 or 10 are known as “Promoters”, as illustrated here:
Let’s take an example. Say there are 100 respondents.
10 responses were in the range 0 to 6 (Detractors)
40 responses were in the range 7 to 8 (Passives)
50 responses were in the range 9 to 10 (Promoters)
NPS: [(50/100)*100] minus [(10/100)*100] = 40
The worst score you can get is -100 and the best score you can get is +100.
Apple uses NPS surveys to find detractors and improve their retail store experience. Whether a customer made a purchase or scheduled an appointment to try on an Apple Watch, they e-mail a survey to rate the in-store experience.
Remember: Any score above zero is good, anything above +50 is excellent, and over +70 is considered world-class.
The greatest advantage of NPS surveys is its simplicity and ease of use. It can be set up in minutes and is easily understood by everyone in the organization. It also makes it very easy to compare yourself with the industry standards.
Additionally, NPS is very closely associated with a company’s propensity to grow. This post says companies with highest NPS in their industry tend to grow 2X faster than their competitors.
Delighted is a great tool to measure NPS.
Customer satisfaction score (CSAT)
A question intended for measuring customer satisfaction is usually asked at the end of a customer satisfaction survey. A typical question would look something like this:
“How would you rate your overall experience with the product?”
Respondents would be asked to rate their satisfaction on a scale of 1 to 5 as follows:
1 Very unsatisfied
2 Unsatisfied
3 Neutral
4 Satisfied
5 Very satisfied
You obtain the result by averaging all the scores received, it is called the composite Customer Satisfaction Score.
CSAT scores are expressed on a scale of 0 to 100 percent. A score of 100 means all your customers are completely satisfied with your product.
% of satisfied customers = # of satisfied customers / # of satisfaction survey responses
It is important to note that only the scores 4 and 5 are considered satisfied, which are then plugged into the formula. If you consider 3 as satisfied, you are failing at giving an opportunity for your business to go beyond mediocre!
A great resource: The American Customer Satisfaction Index benchmarks customer satisfaction for various industries, sectors, and brands. It can be used to compare your organization’s score with the best in the business.
Along with measuring customer satisfaction, CSAT scores are a good way to handle customer complaints too. Experts say that a score of 3 or less is a strong indication that you should follow up with the customer and keep in touch with them regularly to see if things improve.
The key is following up. Hiver’s Email Reminders ensure you send follow-ups at the right time. Know more.
Customer effort score (CES)
The customer effect score takes a slightly different approach to measuring customer satisfaction. The general question asked to customers here is
“how much effort did you have to put forth to handle your request?”
Let’s uncover the logic behind it. This metric gained worldwide popularity after HBR published a very popular article that discourages companies from trying to delight users, and suggests them to focus on solving customer problems quickly. It goes on to say that exceeding customer expectations has a negligible impact on customer loyalty. The only way to make your customer happy (and loyal eventually) is to reduce the efforts they have to make.
The customer effort scale for measuring customer satisfaction goes from 1 (I had to put very little effort to get the problem solved) to 5 or 7 (I had to go through hell trying to get my problem solved).
Nicereply implements it neatly:
To measure the CES, you just have to calculate the average of all the scores. Be sure not to make these scores anonymous. In order to track every effort transactionally, match up every score with the transaction it is referring to.
At the end of the reporting period, you will be able to identify the high-effort events. Look at each transaction that received a low score and put them into different buckets (based on the reason for the score). Create a graph that looks something like this:
In this graph, the most common high-effort issue is ‘too many replies’ which essentially means – a lot of information exchanges before the final resolution. I’d want to narrow down to the agents who were receiving these scores and work on their training.
Ensure that your support agents have quick access to all the answers they need. Make it easy for them to communicate with others in the team. Check out Hiver’s Email Notes.
Once the customer selects their response, a good practice is to follow up with an open-ended question such as ‘How can we improve in the future’? Be sure to leave this question completely open as it would allow your customers to express without restrictions. It makes them feel that the company wants to genuinely understand their problem.
Analyze customer data without talking to them
You don’t always have to rely on survey responses and reviews from customers to be able to gauge how satisfied they are with your product. Following are ways you can analyze customer support data implicitly:
Churn rate
Your churn rate is the percentage of customers who stopped using your product in a given period of time. It is one of the most important considerations while measuring customer satisfaction.
Even the largest companies suffer from customer churn – it is a strong indicator of how satisfied your customers are with your product.
Understanding what causes formerly loyal customers to abandon ship is crucial to the sustainability of your business.
Before a business can figure out what their churn rate is, they must be able to define the events that would essentially constitute churn. For example, for a SaaS business, the following would amount to churn:
- Cancellation of an ongoing subscription
- Closure of a user account
- Non-renewal of a paid plan
The above list is not exhaustive; the actions vary across businesses. Once you have this in place, you can get down to doing the numbers.
Churn rate = # of subscribers lost during a period / # of subscribers at the beginning of the period
Let’s take an example: Say 1 out of every 40 customers have discontinued their subscription every month, your churn rate would be 2.5%.
The natural question here is – What is an acceptable churn rate for a SaaS business?
Now, the best answer obviously is ‘as low as possible’, but, we do not live in a perfect world. A typical decent churn rate for SaaS companies that target small businesses is 3-5% monthly. For an enterprise level product, the churn rate should be <1% monthly. The acceptable rate is again defined differently by every company.
Average revenue per customer
It’s a pretty simple metric – the average revenue you have already received from your customers.
Once you have your churn rate under control and have a good addition to your customer base every month, the natural progression is to have your existing customers pay more. That happens when you are able to up-sell and cross-sell – which again is an indicator that your customers are satisfied.
An up-sell will move your customers to a more expensive plan. A cross-sell will enable you to sell additional services along with your primary offering.
A great way to increase your revenue per customer is to have them buy your annual plan – it puts them into a longer billing cycle.
The crux is building sustainable systems that will help you increase the total revenue from the same set of customers. A steady increase in revenue per customer is a clear indication that your customers are satisfied with your product.
Lifetime value (LTV)
This is the one metric which can help you determine the overall health of your business, including how satisfied your customers are. The lifetime value of a customer is the total revenue you will earn from them during the entire duration of which they use your product.
Before we jump in, it is important to understand the difference between the average revenue per person and the lifetime value of a customer. The average revenue is something you have already received from your customer, while, the lifetime value is a prediction of the total revenue you will receive over the entire duration of their usage. Now, this is a solid indication of how satisfied your customers are.
An upward trend in the LTV is a strong signal that your customers are satisfied with your product, and the service you provide.
As for the calculation bit, while there are a number of formulas out there. The formulas include your cost per acquisition and the cost of customer service – it basically gets pretty intense.
Given that you just want to see the LTV trend over a period of time, it would make sense to keep things simple. You can consider two crucial metrics: your average subscription length and the average revenue per customer. The metrics, when multiplied, will give you a number which is very close to your LTV.
A detailed explanation for calculating the LTV of a customer can be found here.
Analyze customer support data for measuring customer satisfaction
Following are some essential customer support KPIs that can give you accurate and measurable insights into customer satisfaction:
Support tickets volume (trend)
No matter how good your product or service is, it is inevitable to receive a few customer complaints every now and then.
It is usually not considered to be a huge problem for companies that have just started out, they will be happy to see the customers being more participative. But, as your products become older, you’d want them to be easy enough for customers to not have any problems.
Basically, when customers have to reach out to your support for anything, it is an indication that they are not completely satisfied with your product.
The number of support tickets raised is a clear measure of how many people are not happy with your product. Rather than looking at the absolute number, it would make more sense to look at the trend over a period of time.
A great practice is to tag the tickets with by the type of request (bug, feature requests, suggestions, questions, and other). Every time you see an escalation in the number of tickets raised, analyzing the tags would help you understand the actual problem.
Number of interactions per ticket
The ideal number of interactions per ticket is ZERO. Because you’d ideally want to resolve customer issues even before they arise. But for operational purposes, you still need to define an ideal number of interactions in which you’d want to resolve your customer’s issues.
Too many interactions can often mean that your support staff is not asking the right questions about the customer’s issue, or the customer is not being directed to the right people. So if you see the average number of interactions per ticket rising, you may need to look closely and find out the reasons for it.
Any ticket that requires the customer to write more than one email to support is the reflection of an underlying inefficiency.
Average first response time
It is the average time your support team takes to get in touch with the customer after they have submitted a request.
There is no better way to make a customer’s day than to be able to solve their problem quickly. Not only do they tend to forget about the problem, they’d become raging evangelists.
Average first response time = Total of all response times / Number of requests opened
Now, this metric is closely related to measuring customer satisfaction. The more your customers have to wait to get a problem addressed, the more will they lose faith in you. In other words, the lower your response time, the more satisfied your customers will be.
This is an important function of your staffing too. You will have to plan it well to scale with the customer count. Many SaaS companies fail to project the growth of support volumes – this is when customers have to bear the brunt. You should hire and train support people before you need them – accurate projection is inevitable.
It is very important time for your managers to keep a close eye on the resolution processes and the email conversations with customers. If your team, in an effort to bring down the first response time, is sending out vague first replies instead of the actual solution, it becomes counter-productive.
Looking to bring down the average response time of your support team? Hiver – the world’s first customer service software for Google Workspace, lets you delegate tasks in seconds and communicate seamlessly. Know more.
Average resolution time
Responding to users quickly is a job only well begun. It is critical to resolving users’ problem quickly too. A quick first response can leave a lasting memory only when you are also able to solve the problem quickly.
Average resolution time is the average time your support team takes to successfully solve the customer’s problem and close the ticket.
Average resolution time = Total of all resolution times / Number of requests resolved
But, quick issue resolution times can mislead you as well. It’s a known practice among many services based companies where the support staff tags tickets as resolved without actually resolving the issue completely, only to meet their targets.
So you need to have a strong QA system that ensures that the resolved tickets actually represent resolved issues.
Monitoring social media for measuring customer satisfaction
Customers are more vocal than ever, particularly online. They like to share everything they experience on their favorite social networks, including their experiences with products. Facebook group engagement posts are an effective way of gathering valuable customer insights online.
Social media is where they celebrate great experiences with products, and where they vent their frustration when a product does not perform as they would have expected.
Monitoring what your customers say on social media will definitely help you understand what your customers really think about your product.
Let’s dive in.
Tracking brand mentions
Given that customers are extremely likely to share any extreme emotion they experience while using your product on social media, it would make sense to monitor it. This is the most important social metric you would want to track.
Using the right tools, you can monitor and analyze the number of times your brand is mentioned on social networks, even when your company is not tagged. Mention is a great app which will help you track all your mentions across social networks. It can track the mention of your company name, or phrases that are associated with your offering.
Analyzing those mentions, you will be able to determine what customers think about specific aspects of your offering. For example, “I hate that the app takes ages to load” is an indication that the customer is dissatisfied with the app and you also know the reason behind it. You can now have the product team work on the problem.
The greatest advantage brands can have here is participating in those discussions in real time. The app sends you alerts as the conversation happens. Even when you are not able to redress their frustration right away, the act of being there in the very moment and taking responsibility goes a long way in establishing trust and credibility.
Measuring the sentiment behind a mention
Sentiment refers to the emotion behind a social media mention. It’s a great way to mention the tone of a conversation – whether the person is happy, or frustrated, or annoyed. Without measuring sentiments, the measurement of mention alone would not be very useful.
Hootsuite Insights is just what you need to perform this analysis. The tool is based on machine learning technology which determines the sentiment of the mention based on the description words they use.
For example, “Walmart is the worst place to shop” will be registered negative, and “I just love Walmart” will be registered positive.
Using such a tool on a regular basis will help you understand how satisfied customers are with your product.
A sentiment analysis tool will also help you prevent catastrophes. A sudden spike in negative mentions is an indication of a developing crisis. It will be a good time to involve your PR department and prevent the wildfire that it can cause.
Call deflection
Call deflection is the process of re-routing customer calls to an alternative service channel. Let’s begin by seeing how it’s done. Customer service departments prepare a list of top reasons why customers have to reach out to them by phone or email. Then, they produce content (videos or FAQs) which can address these problems and populate the social media pages with them. The ideal outcome is the customer relying on these elements and not having to call or email.
In essence, call deflection is a measure of traffic on social media versus the number of calls received. The ratio is the number of customer problems that have been resolved through information on the social media, and without the customer having to call or email.
How do we measure it:
- See if the engagement (likes, replies) on these elements have increased over a period of time.
- See if the number of calls and emails about similar issues has gone down.
- See if calls around trivial issues have gone down.
- See if call and emails you are answering are of higher value or are customers still reaching out for login issues.
If you notice a growing popularity of the social media elements, it is a strong indicator that you have been able to satisfy your customers better.
It is always good to remember that reducing customer effort is one of the best ways of keeping them satisfied.
You can’t improve your service satisfaction standards unless you know where you currently stand. Measuring customer satisfaction is no longer a hygienic practice, it’s becoming a mandate.
By measuring the customer satisfaction metrics, you’ll get a clear understanding of your existing service standards and how you compare with the industry benchmarks.
Once you have these numbers on your dashboard, you can make calculated moves to improve each metric and enhance the overall satisfaction standards of your company.
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