In this article, we’ll guide you through the various customer experience metrics and how best to measure and optimise your customer experience.
We now live in a world where customers have an infinite supply of products and services to choose from, and it’s getting harder and harder to stand out from the crowd. Customers have become less responsive to the endless conveyor belt of product releases, and the countless ads and marketing campaigns pinged to their screens daily.
People now care more about relationships and experiences with brands and CEOs are starting to take notice, according to “Closing the Customer Experience Gap,” by HBR nearly three-quarters of business leaders (73%) said that delivering a relevant and reliable customer experience is critical to their company’s overall business performance today.
Think back to a time where you went to a restaurant based on a giant ad? Most likely very few times. How many times, in contrast, have you followed the recommendation of a friend or a positive review in a magazine or newspaper? Unbiased references by friends, experts and families carry tremendous power.
The most innovative companies understand that success is closely correlated with creating an end-to-end customer experience that delights customers. Happy customers have the potential to be the strongest troops in your marketing team. Satisfied customers promote your brand and can be a huge asset as their recommendations hold significant influence over potential buyers. They also buy more, stick around and cost less to serve, helping improve the bottom line in ultra-competitive markets.
When setting out to improve your customer experience, you cannot afford to drive blind when carrying out initiatives to enhance your customer experience. You need to make sure you track and measure metrics accurately so you can understand your performance in delivering outstanding experiences for your customers.
As the great management thinker Peter Drucker is often quoted as saying,
“If you can’t measure it, you can’t improve it.”
So it’s crucial you measure what matters.
In this article, we’ll guide you through the various customer experience metrics and how best to measure your customer experience.
Focusing on metrics that are imperfect or not meaningful can have a severe negative impact on your business. Optimising for the wrong metrics and not having in-depth knowledge of your customers will lead to erroneous decisions that hurt your business.
Usually, the root cause of poor customer experience measurement is when companies use metrics defined along functional lines that only tell you part of the story. Creating misalignment between what is being measured and what is driving the underlying economics and customer experience. Choosing the wrong metric can also generate misalignment between the underlying moral purpose of the person doing the work and what is being measured. Both of these can create serious problems for your organisation.
For example, measuring the success of a support rep based on the total number of calls they respond to per day does not align their work to making the customer happy. A support agent will be conscious of their manager assessing individual performance based on the number of requests completed per day. It is within their self-interest to keep calls short and sidestep challenging customer problems. Forcing behaviour such as offloading hard to solve problems to a different team, or avert solving a problem because it will be too timely or complicated to fix. A situation where all the actors from the employee, customer and organisation lose out.
The customer loses out by receiving a miserable experience, annoyed they turn into a detractor sharing their experiences with friends, family and acquaintances taking their business elsewhere. The company now loses out on all the economic benefits of happy customers, and employee morale dips as they fail to delight customers and knowingly deliver a rubbish experience.
First developed in 2003 by Bain and Company, it’s now used by millions of businesses to measure and track how they’re perceived customers. Net Promoter Score (NPS) measures the loyalty of customers to a company. NPS scores are measured with a single question survey and reported with a number from 0-100, a higher rating is desirable.
The survey question gauges customer loyalty by asking a straightforward question, “On a scale of zero to ten, how likely are you to recommend X product/service to a friend?” Respondents answer with either 0-10 or “not at all likely” to “extremely likely.” Brands can come up with an aggregate score by removing the neutral responses, and subtracting the percentage of detractors from promoters.
You can measure almost anything using an NPS score – so as well as understanding the overall NPS for your organisation, you can track scores for everything from individual products, stores, web pages or even staff members.
NPS is an excellent way of understanding the overall customer perception of your brand. You should measure NPS regularly so you can continuously learn and track customer loyalty over time.
For more information on NPS read our guide to Net Promoter Score here.
Where NPS measures a customer’s overall perception of a brand, customer satisfaction (CSAT) measures how satisfied a customer is with a specific product, service, or interaction with a brand.
CSAT targets a ‘here and now’ reaction to a specific interaction, product or event, but it is limited when it comes to measuring a customer’s ongoing relationship with a company.
CSAT is measured by one or more variation of this question that usually appears at the end of a customer feedback survey:
“How would you rate your overall satisfaction with the [goods/service] you received?’
Respondents use the following 1 to 5 scale:
The results can be averaged out to give a Composite Customer Satisfaction Score, although CSAT scores are more usually expressed as a percentage scale: 100% being total customer satisfaction, 0% total customer dissatisfaction.
Brands can gauge customer satisfaction overall by presenting surveys at various customer interaction episodes, asking customers to rate their experience or a specific product. From there, brands have an opportunity to identify problem areas and link them to a particular phase in the customer journey.
Customer Effort Score (CES) measures a customer’s ease of an experience with a company. It’s typically measured by sending customers an automated post-interaction survey asking them to rate a specific statement on a defined scale by asking the question “on a scale of ‘very easy’ to ‘very difficult’, how easy was it to interact with [company name].” The statement will depend on the interaction they just completed.
Companies can then analyze the potential points of friction in the journey. For example, low CES scores might reveal that a website’s checkout process is too complicated. Or that their experience submitting a support ticket was confusing.
By acting on this insight and removing obstacles for the customer, companies can reduce customer service costs and attrition rates (and by extension, loyalty) by making things more convenient for the customer.
Customer churn describes the rate at which a customer abandons a brand, unsubscribes, or stops visiting a website. You can calculate churn by dividing the total number of customers lost by the total number of active customers over a specific timeframe. For subscription-based companies, churn is easier to measure than it is with an online store where all items are purchased on a one-off basis. It’s essential for e-commerce brands to define what churn means within the context of their company.
Customer retention rate refers to the percentage of customers that the company retains over a specific period. Retention is, in essence, the opposite of churn, meaning gathering feedback from customers who stick with you can reveal what you’re doing well.
First response time is the average amount of time that it takes for customers to receive an initial response to a support issue. Generally, this is measured by customer support team, it’s calculated by taking the average response rate time between a customer opening a support ticket and when a rep acknowledges their request.
Average handling time is the amount of time to resolve a support issue from start to finish. This includes every interaction from calls to emails and chat, plus time spent waiting between interactions. The “ideal” handling time varies by organization and complexity of the issue, but it’s good to get a sense of how long people are waiting, on average, for a fix. Remember, this could be a root cause for churn.
How can you turn survey results into action?
Customer feedback holds all the answers. Countless businesses fail to extract actionable insights from their unstructured data.
When trying to deliver a customer experience that your competitors can’t match, focusing on quantitative metrics alone is a huge opportunity missed for customer experience practitioners.
Collecting quantitative data is essential to benchmark customer experience performance over time but acting on quantitative metrics is ill-advised without understanding the why behind the score.
Your customer experience data needs to be actionable enough to change engineering and product roadmaps across an organisation. You should be able to understand whether a potential change in product strategy will meet the needs of a specific customer segment.
To get to the why behind the score you need to capture open-ended feedback from customers to evaluate why your NPS or CSAT is going up or going down. Customer feedback is a great way to build a continuous improvement feedback loop that encourages employee learnings and behavioural change throughout an organisation to make it more customer centric.
Today, touchpoints—and data sources—have multiplied exponentially to include mobile apps, call centers, kiosks, all kinds of social media, and pretty much anytime anyone ever interacts with a screen. It’s possible to capture customer feedback across multiple sections of the customer journey targeting different customer segments on different channels.
Customer experiences once involved was limited number of not easily tracked touchpoints, including magazine and television ads, store visits, purchases at cash registers, and communications received by mail, such as bills or claims responses.
Surveys with additional questions or adding space for verbatim responses at the end of an NPS, CSAT, or CES survey can be sent to customers. Feedback can also be found in unsolicited forms like social media mentions, App Store reviews, or long-form reviews on sites like TrustPilot, Yelp, or G2 Crowd.
Ask customers what they think, in their own words, and make it easy for them to share. The quality of insights gathered is dependant on the quality of data captured. It’s essential to ask the right questions at the right time to correct customers. The better the questions you ask, the more meaningful and richer insight data to analyse.
However, collecting data to ensure insights that can drive actions is a topic that deserves its own attention and something you can find out more about on our blog page.
Which handful of actions will generate the most impact on the customer’s experience? If you had the answer to that question, you’d have a serious competitive advantage in your industry.
Customer experience improvement initiatives can comprise of multiple uncoordinated plans that emerge with good intent from different parts of an organisation. The problem is that there is little clarity which action will offer the most value for customers.
Optimising customer experiences means understanding all the possible combinations of sequential interactions that a customer can take and identifying opportunities for improvement.
To identify opportunities for improvement, you need to understand how your customer’s think and feel. Imagine if you had insight into the mind of the customer? You could quickly enhance your marketing messaging, product roadmap and support experiences.
However, the challenge of breaking down the mountain of feedback across multiple data sources can make even the most hardened executive shudder with fear. Companies today have numerous systems, databases and tools siloed across different functions all geared towards collecting feedback. Teams are sitting on colossal data sources failing to take advantage of the opportunity it presents.
Analysing these large data sets and providing insights and recommendations has, for a long time, has been a headache for customer experience practitioners. The quick and easy solution to this problem is integrating disparate data sources into one platform.
Okay, this is all well and good, but you may be wondering how do I get over the line?
What may appear as a monumental task is quite simple, and it’s a problem we can take care of for you. With our platform powered by the latest in Machine Learning, you can integrate all your feedback channels and analyse your data at scale.
We can identify topic and sentiment in each piece of customer feedback with the same level of detail as you and I reading this text right now. Breaking down that information into clear insights, so you understand the key drivers behind your customer experience metrics. Ensuring you have actionable insights to shape decision making and build experiences that delight.
For instance, from our recent analysis of the UK retail banking sector (link here), we can identify significant detraction causes include poor app security and unintuitive UI. On the upside, the variables that turn customers into promoters include helpful support and ease of use on the app. We can then dive deeper into topics such as app security and identify sub-topics such as login, auto log-out and verification/identification.
Must-win battles in the banking industry, thus often involve creating a seamless UI and improving customer pain points such as app security and contact centre accessibility. Identifying topics that matter most to customers can help improve aspects of the customer experience that you wouldn’t have had visibility of without the help of text analytics. The more data we have, the more granular insights we extract. It’s important to remember the system is only as powerful as the quality of input.
Combined with other sources of customer data, you can perform effective customer segmentation. Segmentation adds a lot of context to customer data so you can better understand how different customer groups feel about some very prominent parts of the customer journey.
You may have different competitors challenging you for different customer segments in different markets. If you could segment how different customer groups such as 16-25 think and feel you can begin to build personalised customer experiences and delight customers.
Customer experience teams need to share detailed reports on metrics both at a journey-level and at an overall level.
Create custom dashboards for different teams so they can keep track all of the feedback relating to their area of responsibility – by product, by marketing, by customer care team or agent etc. View an example dashboard here.
Custom dashboards can help multiple teams operate more collaboratively. A dashboard will be able to explain to the rest of the business the relative impact of solving a problem or making a change to the customer experience in a way that is understandable to multiple stakeholders. Set up alerts, so the right team member is notified when there is a change in the data that require recognition.