What you need to know about customer experience analytics

Consumers are no longer content with great products and services. They demand a quality customer experience from companies in exchange for their money, loyalty, and referrals.

In recent years, firms across industries have invested heavily in customer experience to attract and convert consumers and retain and upsell existing customers. How can business leaders know their investments in CX are yielding the desired outcomes, or what to change about their CX if needed?

CX analytics is the answer. These can provide companies with the insights they need to keep customers satisfied.

Customer experience (CX) analytics is the gathering, analyzing, and interpreting of customer data and feedback to learn about interactions and perceptions across various touchpoints. It helps businesses identify opportunities to improve and enhance their customers’ overall experience and increase customer satisfaction and loyalty.

For example, the hospitality industry is fiercely competitive and requires high-quality customer service. A hotel could easily lose customers for various reasons, including abrupt front-desk staff and poor housekeeping services. Using their smartphone, a customer can immediately post a bad review online or find a different hotel. Therefore, hotels must regularly measure and evaluate the quality of their customer experience.

Every industry, including auto sales, accounting firms, and online stores, should track CX data to more effectively attract and retain consumers, and increase their customer lifetime value (CLV).

Given the time and resources involved in tracking CX analytics, is it really worth doing? In short: Yes! Firms who track their CX see several key benefits:

Data-driven decision-making

CX analytics can help companies dive deeper into their customers' perspectives, behaviors, and pain points to help them make informed decisions based on objective data rather than assumptions. The more you understand how customers experience your brand, retail store, promotional event, product, or support service, the more effectively you can allocate resources to increase their satisfaction.

When analyzing customer data from various sources, you can identify patterns and trends that will help you tailor products, services, sales, and marketing strategies to better align with your customers’ needs.

Increased retention and revenue

CX analytics not only contain insights that are helpful in marketing and sales conversion, but they can also help you retain customers. For example, insights from CX analytics might reveal that a company's customer support is most effective when delivered through social media channels. By investing more heavily in online support, the company may be able to reduce customer churn.

Another example: a company with several membership rewards options can use CX analytics to determine which option gives the highest ROI and customer lifetime value.

Acquiring customers is expensive, but CX analytics can help businesses proactively address issues, resulting in reduced customer attrition and increased repeat purchases.

Improved customer support

One of the most important aspects of a customer's experience with a firm is the quality of support. Despite this, many companies struggle to provide the level of support their customers expect.

CX analytics can tell managers how well they are supporting their customers which agents may need to be retrained, and which support aspects may need to be reconfigured to meet customer expectations.

Enhanced CX

CX analytics' insights can yield rapid and substantial improvement in certain areas like customer support. However, one of the main benefits of leveraging CX analytics is giving firms a holistic view of the experience they provide to customers. This enables them to not only improve existing CX at each brand touchpoint but also to create of seamless, consistent, and high-quality CX across all touchpoints. This enables compelling marketing throughlines at every level of company–customer interaction.

To successfully use CX analytics, you need to start by knowing what to track. When you have clear objectives, you can gain tremendous insights into customer behavior, sentiment, and loyalty from the following metrics:

Customer satisfaction score (CSAT)

Customer satisfaction is ultimately what your firm is aiming for with great CX. A high customer satisfaction score (CSAT) means you're achieving that objective. The CSAT measures customer satisfaction with a specific product, service, or brand after a recent interaction.

Net promoter score (NPS)

The Net Promoter Score (NPS) helps you gauge your current standing with customers and identify brand advocates, which can lead to positive word-of-mouth and organic growth. Its calculation relies on survey responses to the following question:

• "On a scale of 0 to 10, how likely are you to recommend our [product/brand/business] to others?"

There are three easy steps for working out your NPS:

1. Divide your responses into three categories:

• Detractors: Those who have given your firm a score of 6 or below.

• Passives: Those who have rated the firm a 7 or 8.

• Promoters: Those who rated it a 9 or 10.

1. Calculate what percentage of respondents fall into each category.

2. Subtract the percentage of Detractors from that of Promoters to arrive at your NPS.

Calculating and tracking NPS may not yield much in the way of actionable insights. The score is a snapshot of consumer sentiments at a particular time – sentiments that may have changed by the time you're evaluating their data. It also disregards customers identified as Passives. And it does not take into consideration repeat-purchase behavior. An alternative metric, the customer loyalty index, addresses some of these deficits.

Customer loyalty index (CLI)

Like the NPS, the CLI relies on customers to predict and self-report their future behavior. It is a broader measure than NPS as it not only asks customers to share their likelihood to recommend a product but also their likelihood to make additional purchases of the same and other goods. 

Customers are asked to rank their answers to the following three questions on a scale of 1 to 6:

• "How likely are you to recommend our [product/brand/business] to friends and family?"

• "How likely are you to buy our product[s] again?"

• "How likely are you to try other products and services we offer?"

Averaging the responses provides you with a CLI score. While it still represents a snapshot in time, it does offer a more comprehensive view of your customers' sentiments towards your products and business.

Customer effort score (CES)

The customer effort score (CES) is another vital measure that can show firms that immediate and substantive CX changes are needed. CES evaluates the ease of completing tasks or resolving issues at a particular brand touchpoint. Measuring this metric starts with a clear and direct question or statement about the customer's effort to resolve their problem.

For example, you could ask customers, "How easy was it for you to solve your problem?" and give them a numerical scale, such as 1 to 5 or 1 to 7. If you provide your customers with a scale from 1 to 10, you can measure the CES by adding up all the responses and dividing the sum by the total number of responses. With a 1 to 7 scale, divide the total number of positive responses (those from 5 to 7) by the total number of responses, then multiply by 100.

How you evaluate your CES depends partly on how you've measured customer effort. If you've asked customers how easy it is for them to solve their problems, you want a high CES. If you've phrased the statement, "It is difficult to solve my problem," you'll want a low CES. It's also important to consider your CES over time. Changes in your CES may indicate that changes in your website, customer support, or other operations are making things easier (or more difficult) for your customers. So, evaluate your CES relative to your customers' experience, expectations, and operational changes to get the most from this measure.

Website and app engagement metrics

There are lots of different metrics you can track to measure customer engagement on your website and mobile app. Some of the most common and effective metrics include:

Average session duration

This metric refers to how much time a visitor spends browsing your website or app in total.

Average time on page

Average time on page is how much time a visitor spends on a particular webpage. Longer times typically signal interest.

Bounce rate

Bounce rate is the percentage of your visitors who only load one page of your website before leaving. High bounce rates indicate disinterest or technical issues.

Conversion rate

The conversion rate tells you how many times a visitor has converted online. A conversion may refer to a sale or other actions, such as email list sign-ups or content downloads.

Event tracking

Event tracking involves evaluating a visitor's various actions while on your site, such as downloading a form or clicking on an article. Doing so can give you a clearer picture of the online aspects of the customer journey.

Exit rate

The exit rate is the percentage of your visitors who leave your site from a particular page. If a specific page has a high exit rate, you should determine whether customers are turned off by its content or if there are performance issues.

New visitors

This metric provides the number of times a unique and new visitor initiates a session on your website within a set period.

Pages per session

The pages per session metric is important to evaluate in tandem with average session duration. This metric tells you whether visitors are spending time exploring your whole site or spending long periods on just one or two pages.

Page views

Page views refers to how often a page on your site is viewed.

Returning visitors

Returning visitors are the number of visitors who visit your website or app more than once during a set period.

Revenue attribution

Revenue attribution tracks a visitor's activity from the moment they land on your website or app until they make a purchase, as well as how much income their transactions produce.

Social media referrals

Social media referrals are referrals to your site from either organic or paid social media. Given how essential social media marketing is to small businesses, this metric is especially important for small businesses to track.

Top pages

Top pages refer to your site's pages with the most traffic, conversions, and viewership duration. Understanding which pages are most heavily visited is an important part of understanding the customer journey and can help you identify improvements to those or other pages that may be needed.

Top exit pages

Top exit pages are the last pages that visitors view before they leave. Like top pages, understanding top exit pages can help you identify needed improvements to increase engagement and conversions.

Traffic sources

Understanding whether visitors came to your site directly, through organic search, paid search, or referrals can better help you understand your customers' interests and overall journey. It's also important to understand the nature of the referrals, which may come from social media, email, or external websites. 

Customer lifetime value (CLV)

By investing in CX, firms hope to retain customers and increase the amount they spend during the whole length of their relationship. Acquiring new customers is almost always more expensive than upselling existing, long-term customers. Existing customers who are thrilled with your firm's products, services, and support are most likely to add more products to their cart when pitched.

The measure of revenue a customer generates during their relationship with a company is known as customer lifetime value (CLV). And analyzing CLV is also important when it comes to evaluating and improving customer experience. Ideally, your CLV will increase across customer segments over time. But what if your average CLV remains flat or declines during a period in which you've introduced multiple promotions?

A flat or declining CLV might signal one of several problems:

• Your promotional efforts are not resonating enough with your customers

• Your customers may be resistant to buying more because they aren't currently fully satisfied with what they've bought or some interaction(s) along their customer journey (look at CSATs too)

• A stagnant average CLV coupled with a high CES score may indicate some pain points during the purchase process.

Digging into the average CLV for each customer segment may help you identify unique pain points. Even if your total average CLV is increasing, examine CLV data in depth to ensure your success with one or more segments is not masking problems with others.

Churn rate

A high churn rate is one surefire signal that something is wrong with your CX. The churn rate is the rate at which you lose customers. A high churn rate won't tell you where the CX problem is, whether in sales, marketing, web UX, products, support, or another area. But it indicates customers are dissatisfied with one or more aspects of your interaction.

Calculating the churn rate for a firm is relatively simple. You'll need to take a period, such as a month, quarter, or year, then divide the number of customers you lost during that period by the number you gained. Then, multiply the quotient by 100 to get your churn rate for that period. 

Measuring your churn rate at set intervals regularly and frequently can flag early warning signs that an aspect of your CX needs immediate improvement.

Customer retention rate

As you clearly want to retain customers, it's important to measure your customer retention rate as well as your churn rate. Customer retention rate refers to the percentage of customers you keep over a fixed period. For example, if you have 1,000 customers in June but lose 110 of them by July, you have an 89 percent retention rate.

A high customer retention rate indicates your customers are satisfied with and loyal to your products and business. A low customer retention rate and a high churn rate signal that your customers are not loyal to your brand, are dissatisfied with some aspect of your business, or both. Businesses must engage their customers effectively to keep their customer retention rate high.

Customer journey mapping

Another essential component of understanding CX is customer journey mapping. This is not a specific metric but rather the process of charting the entire customer experience. When you depict the steps a customer takes from their first interaction with your brand to purchase, you can identify pain points that need improvement and create a more seamless experience. Visual representations of the customer journey are especially effective in this regard.

For example, a firm may begin experiencing an increasing bounce rate on its sales landing page. Consequently, data analysts may seek to identify and evaluate pain points on that page. They may also examine the pages from which a customer was referred to the landing page to identify possible issues. An analyst might find that an abrupt shift in tone between a referral page and the sales landing page might be turning off customers. Or they may find inconsistencies between what was promised on the referral page and what is being said on the landing page.

Companies use various touchpoints to collect CX analytics, including:

• Customer surveys

• Online feedback forms

• Social media interactions

• Customer support interactions (such as call recordings and chat logs)

• Website and app usage analytics

• Purchase history and point-of-sale data

• Digital newsletters, blogs, and content downloads

• Customer feedback through email or phone communication

• Customer relationship management (CRM) data 

Some of this data, such as website and social media usage statistics, is easily accessible through analytics dashboards. Valuable customer information can be gleaned from your support operations. Essential financial data, such as customer transaction histories, can also be found in your sales platforms. However, to best understand your customers, you'll need to collect additional data using some of the methods already mentioned.

One of the most common methods for collecting customer data is surveys. You can provide surveys at various times during customers’ interactions with your company. For example, you could ask them to take a survey after they make a purchase, receive customer support, or sign up for a newsletter. You can also periodically provide customer surveys through email, social media, or your website and mobile app.

You can also collect important contact information and insights about customer preferences when customers sign up for your newsletter, subscribe to your blog, or download gated content. Offering promotions and competitions can also help you collect this kind of information.

Collecting and leveraging CX analytics to make improvements can substantially improve a firm's revenue, reduce its customer support workload, and decrease customer churn. Moreover, it can help firms create increasingly personalized and compelling customer experiences that help increase customer satisfaction and lifetime value.

Investing the time and resources into measuring and using CX analytics should be a top priority of any firm. Firms should examine internal processes and workflows to begin to collect CX-relevant data, identify in-house or outside data analysts to evaluate their CX analytics and explore which CX platform would be a good fit for their organization.

Customer experience analytics is a win-win for the customer and the business. When a firm uses customer experience analytics to improve its operations, the customer benefits from a more satisfying customer experience. The business usually also benefits when increased customer satisfaction results in higher sales from customers over time and lower customer attrition.

A CX analyst is responsible for collecting and interpreting data about a customer's experience with a business. A CX analyst may actively solicit customer feedback through surveys and other tools, as well as gather and analyze data already collected by a firm, such as customer support metrics. The analyst will evaluate this data and recommend changing specific aspects of a firm's operation to improve customer satisfaction, experience, and other metrics.