Measuring Customer Satisfaction With Hard and Soft Data
Did you know satisfying your customers is an important part of running a business?
Sorry. That was a silly question. Of course you do.
I mean, it makes perfect sense:
If your customers aren’t satisfied with the service you’ve provided them, why would they continue to give you their hard-earned cash?
On the other hand, if you’ve done everything you promised to do—and more—for your customers, they’ll have no problem opening their wallets when they’re in need of your services.
Overall, ensuring your customers are satisfied is simply good for business. In more specific terms, customer satisfaction:
- Drives repeat purchases and brand loyalty
- Increases customer lifetime value and ROI
- Reduces instances of churn and/or negative word-of-mouth
Not only does focusing on satisfying your customers make those customers more likely to return, but leads and prospects will also be more likely to choose your brand over your competitors’ once they learn that their satisfaction is one of your top priorities.
Now, the question is:
How do you know your customers are truly satisfied?
From customer satisfaction to customer success
Before we get into the ways you can determine a customer’s level of satisfaction, it’s important that we clarify the difference between customer satisfaction and customer success.
First, let’s talk in terms of process versus outcome.
The process of using a product or service can be easy or difficult; exciting or boring; enjoyable or torturous. Needless to say, some of these experiences would be quite satisfying, and others would not be.
But all of this tells us absolutely nothing about whether or not a product or service effectively helped customers solve their problems.
A product that’s easy and fun to use might also be efficient—but it might not be. Similarly, a service (such as a training program) could be rather rigorous and not all that enjoyable for the customer—but it does end up helping them grow in some way.
While a customer’s level of satisfaction during the process of using a product or service is at least somewhat important (i.e., you wouldn’t actively want to make your customers uncomfortable while using your service), it’s much more important to know for sure that the service you offer does what you claim it does, and that it enables your customers to reach their goals.
Let’s say we’re looking at two people who have signed up for a rigorous 30-day program that promises to help entrepreneurs grow their mailing list. Customer A is looking for a quick and easy “hack,” while Customer B is prepared to dig into the nitty-gritty techniques the program has to offer.
Now, let’s say both customers successfully reach their respective goals by the end of the month. It’s a pretty safe assumption that Customer A probably didn’t enjoy the process, per se—but the program was exactly what Customer B was looking for.
In either case, regardless of their level of satisfaction, the objective truth is that the program was effective for both customers.
One last thing to note before we move on: along with customer satisfaction being a subjective quality, it can also be an unreliable data point. While one customer might shrug off a minor glitch in your service, another might take it much more seriously. Or, a customer might report being satisfied just to avoid ruffling any feathers—despite facing multiple problems with your service.
Again, this isn’t to say that customer satisfaction isn’t important—it is. However, while customer satisfaction depends largely on individual customers’ personalities (a factor not within your control), their success lies heavily on your ability to help them solve the problem they’re currently facing.
So, let’s talk about how you measure both customer satisfaction and customer success—and analyze them together to get the full picture on your users and the quality of your services.
Measuring customer satisfaction and success with hard and soft data
In the following section, we’ll discuss two types of data:
- Hard Data: Quantitative statistics relating to customer engagement and purchase behavior
- Soft Data: Qualitative information based on customer reports
Let’s take a deeper look at what each type of data entails, as well as some of the most effective measurements within each.
Hard customer satisfaction data
When discussing the hard data relating to customer satisfaction, it helps to break it down even further into concrete hard data and inferred hard data.
Concrete hard data is that which clearly relates to customer satisfaction and success without much need for analysis; what you see is what you get.
Examples of concrete hard data include:
Net Promoter Score
The Net Promoter Score determines the likelihood of a customer recommending a brand to their peers by asking them, quite simply:
“On a scale from 0 to 10, how likely are you to recommend our product/service to a friend, family member, or colleague?”
Respondents are then placed into one of three categories:
- Promoters: Those who responded with an answer of 9 or 10, showing a strong likelihood of making a recommendation
- Passives: Those who responded with an answer of 7 or 8, which, in this case, means they are rather indifferent in terms of making a recommendation
- Detractors: Those who responded with an answer between 0-6, meaning they are rather unlikely to make a recommendation
Once a sufficient amount of responses has been gathered, the amount of Promoters and Detractors is determined in terms of percentage points. The percentage of Detractors is then subtracted from the percentage of Promoters. The resulting figure is the company’s Net Promoter Score.
The highest NPS is 100 (100% Promoters, 0% Detractors), and the lowest is -100 (0% Promoters, 100% Detractors).
A “good” Net Promoter Score depends largely on your industry. In some cases, an NPS of 20 is actually considered rather high; in others, a score of 50 is par for the course.
NPS is undoubtedly an effective indicator of whether or not your customers are satisfied with the service you provide.
On the one hand, satisfaction is essentially a prerequisite to brand evangelism (i.e., if a customer is willing to recommend your brand to the people they care about, you can be sure they are satisfied with your service).
On the other hand, those who wouldn’t recommend your brand (and even those who are simply hesitant to do so) are almost certainly dissatisfied with your company’s ability to help them achieve their goals.
(Side note: You can use Autopilot to follow up with NPS respondents.)
Customer Effort Score
A Customer Effort Score survey asks customers to rate the amount of effort it took to complete a certain task while engaging with the company.
There are two versions of the CES question, with the latter being the updated, less confusing of the two. In either case, respondents will be asked to fill out a Likert Scale questionnaire.
The first version asks, “How much effort did you have to put forth to handle your request?” Respondents will then choose an answer between 1 (No Effort) to 5 (High Effort). In this case, a lower score correlates to more effective service on the part of your company.
The second version reads: “(Company) made it easy for me to handle my issue.” Respondents are then asked to choose between 1 (Strongly Disagree) and 5 (Strongly Agree). In contrast with the first version of the CES survey, the higher a customer’s reported score, the more effective your company was at helping them solve their problem.
Measuring Customer Effort Score is similar to measuring NPS. After determining the percentage of positive and negative results (ignoring neutral responses, for our current purposes), you then subtract the negative percentage from the positive percentage.
You can evaluate the Customer Effort Score as it pertains to a variety of your services (such as customer service, customer onboarding, the checkout process, etc.). In return, you’ll get a good idea of where your customer-facing processes are streamlined—and where hiccups in your service end up frustrating your customers.
Of course, it’s basically impossible to avoid having some customers reach out with complaints regarding your product or service.
But that doesn’t mean you can’t turn things around for them by doing whatever it takes to resolve the issue they’re facing.
Assessing your organization’s complaint-to-resolution ratio will give you a good idea of how well you’re able to mitigate customer-facing issues before your customers churn.
This, in turn, can be an incredibly effective way to measure your company’s overall ability to satisfy your customers. If you’re ultimately able to satisfy previously-unhappy customers, this certainly says something about your ability to please the rest of your audience.
As mentioned earlier, there are also some metrics that relate to customer satisfaction in a tangential manner:
There’s little denying that the higher your retention rate is, the better off you are.
And, at first glance, it’s easy to assume that a high retention rate means a decent amount of your customers are satisfied and successful.
But, that’s not necessarily the case. There are many other reasons that a customer may continue to make purchases from your company, such as:
- Your service is most affordable for their means
- Your service is most accessible to them in terms of location
- Switching brands isn’t a top priority for them
Think of it like this:
How many times have you, as a consumer, said something along the lines of “Yea, (XYZ Brand) isn’t the best, but at least…”
In cases such as this, though you’re still getting business from these customers, they certainly aren’t thrilled with the service you’re providing in return.
At any rate, the examples listed are most likely exceptions rather than the rule. The point is: be careful not to simply assume a high retention rate absolutely means your customers are 100% satisfied.
The same goes for churn rate, as well—albeit in an opposite way.
On the whole, you can probably assume that most of your lapsed or churned customers have left because they weren’t exactly satisfied with your services.
But, as with retention rate, there are a number of other reasons your customers may have abandoned ship:
- They’re no longer in need of your services
- They’ve relocated out of your area
- Extenuating personal circumstances
Again, though: these are likely just exceptions to the rule. If you notice your churn rate creeping up, you can assume most of these customers aren’t getting what they paid for out of your company.
In contrast to complaint-to-resolution ratio, which sees complaints as a separate entity altogether, complaint-to-customer ratio looks at complaints through the lens of your entire customer base.
Yes, a high complaint-to-customer ratio is a pretty good indication that your customers aren’t exactly ecstatic with the service you’ve provided.
But a low complaint-to-customer ratio doesn’t necessarily mean the opposite. For example, some customers might not be satisfied, but haven’t made their voices heard. In fact, as much as 96% of dissatisfied customers won’t reach out with a complaint—but they will recommend their peers stay away from your company.
Additionally, complaint-to-customer ratio just looks at complaints—not solutions. In other words, it defines customers as dissatisfied at a current moment, rather than at the culmination of their experience.
The complaint-to-customer metric can help you pinpoint specific shortcomings in your service, in turn allowing you to focus on improving these areas—and your customer’s overall experience.
Soft Customer Satisfaction Data
Soft customer satisfaction data refers to any qualitative information your customers have provided—either to you or to a third party—that provides insight into their level of satisfaction with your brand.
By nature, quantitative data is self-explanatory. As such, soft data doesn’t require any sort of calculation or interpretation of responses. This data can come from anywhere—as long as you’re paying attention when customers make their voices heard.
Some of the most common ways of collecting such data are:
- Asking for further explanation of responses within customer satisfaction surveys.
- Checking the comments sections of your blog posts (as well as third party blog posts that mention your brand), and your social media pages.
- Product and service reviews, whether on your company’s pages or on sites where your products are sold.
- On-the-fly conversations between customers and service representatives—either online or in person.
With soft data, your customers aren’t limited in terms of what they can and can’t say—meaning you get a much more accurate idea of their true level of satisfaction.
Also, for the most part, soft data is a collection of unsolicited, unfiltered information provided voluntarily by your customers. Whereas some hard data (such as Customer Effort Score and Complaint ratios) may be skewed due to unreliable responses, you can be pretty confident that information provided in customer reviews and blog comments accurately represents that customer’s honest level of satisfaction.
Clearly, understanding whether or not your customers are satisfied with your services is important.
But nailing “customer satisfaction” down to a single metric is not only near-impossible, but it’s also not very helpful, either.
Rather than attempting to simplify (or dumb down) customer satisfaction, it’s much more beneficial to analyze all that it entails. Along with your ability to provide your customers with a pleasurable experience, customer satisfaction is also affected by whether or not your service did what you claimed it would do—and what you did to help customers who fell short of their goals.
By taking all we’ve discussed into consideration, you’ll get a much clearer picture of how adept your organization is at satisfying your customers and helping them succeed.
About the author: Josh Brown is the Content & Community Manager at Fieldboom, the place to create beautiful forms and surveys in less than 5 minutes. He is a technologist, digital strategist, BJJ blue belt, and loves to travel.