0

Bot, or not? Find out whether your chatbot should pretend to be a human. Join the 15-minute Coffee Break webinar on Thursday, August 17 at 11:00 AM ET.

x

Blog

Dec 05, 2016

How to Measure Customer Satisfaction

how to measure customer satisfaction ask more questions sign

[Estimated read time: 6 minutes]

To measure customer satisfaction, you must collect and analyze quantitative and qualitative data from a wide variety of sources, including surveys, focus groups, unsolicited feedback (e.g., social media posts), and sentiment and topic trends gleaned from service interactions.

For even more detail, you can look at indirect sources. For example, some contact center metrics, such as first-contact resolution rates, are known to affect customer happiness. On the flip side, retention rates and loyalty are strongly influenced by satisfaction levels.

By tracking a combination of these measurements, you'll get a better picture of where you stand with your customers. If you limit yourself to only one or two sources, you’ll end up with a false understanding that can lead to misguided business decisions.

Surveys

First, remember that you’re measuring customer satisfaction—here, a survey refers to feedback solicited after a purchase or support interaction, not broad market surveys. (Those can be very useful for gauging consumer preferences to inform product development, marketing strategy, etc., but not for this purpose.)

Surveys can be presented with self-service results, at the end of a live chat, in a pop-up on your website or mobile app, in an order confirmation email, or even as an option after a phone call with a representative. The more immediately they follow an interaction, the more accurate results they’ll provide.

Net Promoter Score (NPS) Surveys

Net Promoter Score survey is a quantitative assessment of customer loyalty and overall satisfaction, measured by asking customers to respond (using a scale of 1 to 10) to the question, “How likely is it that you would recommend [Organization X] to a friend or colleague?” NPS surveys are thought to provide accurate results because customers have an easier time identifying intention than emotion (e.g., “How satisfied are you?”). Also, because they are standardized, you can compare your company against industry benchmarks.

Customer Satisfaction (CSAT) Score Surveys

CSAT score surveys are also quantitative, asking customers to rate their level of satisfaction with a product, service, experience, or company. Like NPS, CSAT score surveys only ask one question, but they don’t use a standardized scale and they’re directed at sentiment. One survey may ask customers to rate a service as “amazing, fine, not satisfactory, or terrible,” while another just offers happy, neutral, and sad emoji faces.

csat score and smiling face

Despite its name, a CSAT score is far from a true measurement of customer satisfaction. Even the customers themselves have trouble estimating their satisfaction in such simple terms, and sentiment is a notoriously unreliable indicator because it’s fleeing and dependent on mood. In addition, a real understanding of customer satisfaction has a direct correlation to loyalty, but CSAT scores don’t: 20% of “satisfied” customers in a Corporate Executive Board (CEB) study said they intended to leave the company, while 28% of “dissatisfied” customers intended to stay.

Customer Effort Score (CES) Surveys

This newer addition to the customer satisfaction game was developed by a team at CEB to quantitatively measure the effort it took a customer to get their issue resolved. A customer effort score is seen as a more accurate reflection of satisfaction because it has a stronger correlation to loyalty: an impressive 96% of customers with a high CES showed reduced loyalty in the future, while that was the case with only 9% of those who reported low effort scores.

Qualitative Surveys

Surveys can also be used to collect unstructured, text-based feedback that often gives a more detailed picture of customer happiness than structured, quantitative feedback. But while structured data fits neatly into predefined fields, unstructured information needs to be processed by natural language processing (NLP) and sentiment analysis tools in order to provide meaningful insights.

Focus Groups

customers in a focus group

Focus groups allow you to hear feedback from your customers firsthand. Depending on the information you’re seeking, those individuals can represent a specific demographic group or reflect the diverseness of the customer base as a whole. Because they take place in real-time, focus groups give you the flexibility to dive deeper into issues that come up. But they can also give skewed results if you have outspoken participants who dominate the discussion.

Unsolicited Feedback

Surveys and focus groups are considered “solicited” feedback, because you’ve asked customers to provide it. Unsolicited feedback, on the other hand, is unprompted. The biggest sources of this data are social media posts, comments, and reviews.

To successfully collect and analyze unsolicited feedback, you need a social listening tool that can track down any mentions of your company, brand, or products. The best tools then use NLP and sentiment analysis technology to filter out the noise and identify actionable information.

Unsolicited feedback has been considered more accurate because people tend to be more upfront with their opinions when they think the company isn’t listening. But as social media is increasingly used for customer service interactions, consumers are discovering that they are being heard. At the same time, they’re realizing that complaining in a public forum can get results when they’ve been failed by other channels. Therefore, this feedback could now reflect more negativity and anger than actually exists across the board.

Sentiment and Topic Trends

Sentiment tracking and analysis is the process of identifying whether unstructured feedback (from customer email, chat and voice interaction transcripts, qualitative survey responses, social media posts, etc.) expresses a positive, negative, or neutral attitude toward any given topic. When you look at trends in sentiment and topics together, you can gain valuable insights into customer satisfaction levels with specific products or aspects of your brand.

First-Contact Resolution (FCR) Rates

Many customer care and marketing leaders view high first-contact resolution (FCR) rates as the hallmark of call center success. And it makes sense that they should, because FCR has a direct impact on customer loyalty: Studies have consistently shown that whenever customers have to contact a company a second time, satisfaction is reduced by at least 10%.

Before you can feed a high FCR rate into your customer satisfaction measurement, though, you need to dive a little deeper and ask why it’s so high. Is it actually because your customers are getting what they need the first time, or is it because they just aren't calling back? They may have simply moved to another channel, but if you don’t have a 360-degree view of the customer, you won’t know that. Or they may have gotten fed up and switched to a competitor: 96% of unhappy customers don’t complain, but 91% of those will never buy from you again.

Almost one-quarter of repeat calls involve downstream issues related to the problem that prompted the original call. For example, one bank found that many customers who change their address follow up later to order new checks or ask about homeowner’s or renter’s insurance, so now representatives bring up those topics during the initial interaction.

Retention Rates and Loyalty

Similarly, higher customer satisfaction leads to higher retention rates and increased loyalty. According to Bain & Company, a customer is four times more likely to defect to a competitor if the problem is service-related rather than price- or product-related. And research has found that customers who rate you a 5 on a 5-point satisfaction survey are six times more likely to buy from you again, compared to giving you a score of "only" 4.8. This correlation lets you add to your view of customer happiness by inferring that a change in retention and loyalty indicates a change in satisfaction levels.

How Astute Can Help

Astute’s leading-edge software uses natural language processing (NLP) and sentiment analysis technology to provide actionable, omni-channel insights into where you stand with your customers. To see our products in action, request a personalized demo.

X

Featured Whitepaper: "Differentiate or Die"

What sets you apart from your competition?

Read the Whitepaper