Paula Schäfer and Frank Ohnesorge
The customer experience (CX) is more relevant today than ever before. CX excellence is closely related to business performance and is a key priority in many organizations. In light of the Covid 19 pandemic, the digital CX, in particular, has become even more critical as many physical interactions have shifted to online. For this reason, organizations must provide a high-quality digital customer experience to be successful in the long term.
To ensure digital customer experience quality (CXQ) superiority, companies must first assess the status quo of their CX and then make improvements as needed. Determining the status quo requires companies to define appropriate metrics for measuring CXQ along the customer journey. The understanding follows the famous economist Peter Drucker who said, “If you can’t measure it, you can’t manage it.” In other words: If you want to deliver great digital CX, you need to first measure it and then strategically manage it.
For this purpose, we compiled a set of Key Performance Indicators to measure digital CXQ. The collection includes metrics for CXQ at various touchpoints in the pre-purchase, purchase, and post-purchase phase of the customer journey, as well as metrics for CXQ assessment across the customer journey phases.
To assess CXQ in the pre-purchase phase, satisfaction with information search and evaluation must be evaluated.
Online information is available at various touchpoints, such as search engines, customer reviews, online forums, or social media. The construal score measuresthe satisfaction with information in search advertisements on search engines. Based on the MRC database, the score evaluates the concreteness of search queries and search advertisements. The closer the two construal scores are to each other, the higher the customer satisfaction, since the degree of concreteness of the search advertisement corresponds to what the customer is looking for in terms of concrete information in his information search phase.
The satisfaction with the opinion of social others in the form of electronic word-of-mouth (eWOM), is determined by the perceived usefulness of the source. This depends on two factors: review extremity and review depth. The extremity of rating is the degree to which eWOM is extremely positive, negative, or reflects a moderate and similar opinion. The review depth refers to the number of reviews available which can be measured with the eWom volume.
The browsing time, which is the duration of customer web browsing time after clicking an offering, measures the degree of involvement. Involvement describes how much customers are motivated to learn about a product or service. High-involved consumers search more extensively for information than low-involved customers. If high-involved customers buy a product, they are more likely to be truly satisfied and loyal. Thus, the longer the browsing time, the higher the involvement in the information search and thus the satisfaction.
The information evaluation is based on available information, such as observable product characteristics, marketing mix activities, or word-of-mouth. In evaluating information, consumers rate the information sources’ credibility, likeability, attractiveness, trustworthiness, and information quality. The attributes likability and attractiveness are straightforward to measure through the social media key performance indicators likes, followers, and comments. The website quality indicates trustworthiness and can be measured through the eQual index which is based on customer surveys. In the survey (responses measured on a 7-point Likert scale), respondents assess the websites’ usability, design, information quality, trust, and empathy and rate these qualities’ importance. The final eQual index is the percentage of the total weighted score achieved to the total possible score.
The purchase phase in the online customer journey comprises the process of the consumer’s decision-making up to the delivery of the product. It includes brand consideration, customer choice, and order fulfillment.
Brand consideration can be measured by the click-through rate (CTR) on online search ads and the number of organic website visits which are the number of visits by customers to a website without influence from paid or external sources. The higher the click-through rate and the organic website visits are, the higher the customer’s familiarity, positive associations, and satisfaction.
Customers are satisfied with their product or service choice if the product meets or succeeds their expectations about all tangible and non-tangible product attributes. The return rate, i.e., the proportion of returned items to the total number of items sold, measures satisfaction with product choice. The reason is that product returns result from dissatisfaction with the product or service. A low return rate in turn reflects a high satisfaction with the product or service choice.
Customers value the convenience of online ordering, seamless last-mile delivery, and excellent customer service. The last mile delivery aspects that drive customer satisfaction are the number of carrier and time-related delivery options, the number of delivery fees, the on-time delivery rate, delivery speed, and order tracking options. A failure in those aspects will negatively affect CX perceptions.
The customer service also belongs to the order fulfillment process. Usually, customers only contact customer service when something has gone wrong. For this reason, it is important to have vital customer service to comfort customers and maintain a high level of satisfaction. To ensure customer service satisfaction, the first contact resolution rate should be high, whereas the average wait and resolution time should be low. The first-contact resolution (FCR) rate is the share of resolved conflicts during the first contact with customer service and the average wait time (AWT) is the total hold time divided by the number of calls that have placed customers on hold. The average resolution time (ART) is the average time that is needed until a customer complaint is resolved.
The post-purchase stage comprises all customer interactions beyond the purchase. To track the customer’s perceptions about these interactions, metrics to measure the customer mindset and customer behavior post-purchase should be employed, categorized as customer satisfaction, loyalty, and recommendation intend/behaviors metrics.
A relatively novel metric for the reverse measurement of customer satisfaction online is the customer frustration rate which captures the customer’s negative emotions about the CX post-purchase. It is the number of words referring to frustration in reviews divided by the total number of review words. To determine the number of words with frustration, text mining programs are used.
Effortless experiences drive customer loyalty. The customer effort score (CES) operationalizes the effort and is based on a customer survey where customers rate the effort required for the transaction based on the question, “How much effort did you have to put forth to handle your request?”. The answering options range from 1 “very little” to 5 “very high.” The lower the score, the smaller the customers’ effort, and the greater customer loyalty.
The customer churn rate (CR) is another metric to measure customer loyalty. When churn is high, loyalty is low, because churn means that a customer switches from one company to another. Due to the availability of extensive customer data online, the CR can be determined for subscription and non-subscription products. In contrast to the churn rate, the retention rate measures the proportion of loyal customers who remain active customers of the company as a result of their satisfaction with the CX.
Recommendations and referral behavior
Customers’ recommendations and referral behavior reflect their satisfaction with the company and its offerings. The customer referral value (CRV) measures the degree and the value of customers’ referrals. The CRV is calculated on an individual customer basis and is the present value of value added by the customers who joined due to the referral plus the acquisition costs saved through referral for customers who would have joined anyway. The higher the CRV, the more satisfied are the customers as their willingness to refer is high.
The Customer Influence Effect (CIE) and the Customer Influence Value (CIV) measure the influence of customer recommendations on others, as well as the degree of positivity and thus satisfaction with the social media experience. The CIE is the net influence wielded by a user (in a social network) in terms of his or her ability to spread positive or negative word-of-mouth (WOM) through direct and indirect connections. The CIE of an individual is the sum of his posted messages plus the influence on the CIE of the users with whom the user engaged. Calculating the CIE is an ongoing process, starting from the last observed influence. The metric is particularly useful for measuring the extent to which a person spreads information. The CIV builds on the CIE and determines the monetary value of the individual’s influence. It is calculated by adding the share of the customer lifetime value (CLV) plus the share of the CIV of all individuals for which the impact can be traced back to the individual for which the CIV is calculated. Due to their nature, the CIE and CIV work well in the online context. For example, if online shops tie their login with social network IDs such as Facebook, Twitter, or Google, they can directly trace the WOM to the respective customer.
General customer experience metrics
Organizations should focus on the CXQ at the individual touchpoints but consider the connectivity and multiplicity across touchpoints. The following metrics measure CXQ along the customer journey and are not attributable to a single touchpoint.
Customer lifetime value (CLV) is the value a customer provides a company. Excellent CX will maximize satisfaction, leading to a high CLV. The CLV is the present value of the difference between the estimated gross contribution of the customer and the estimated marketing costs over the total lifetime of a customer.
The Net Promoter Score (NPS) is one of the most prominent and widely used metrics. The NPS question “How likely is it that you recommend (company x) to a friend or colleague?” is a predictor of customer loyalty. The customers answer the questions by indicating their level of agreement on a scale from 0 to 10, where 0 means “not at all” and 10 is “very likely.” Based on the answers, customers are grouped into three categories: detractors (answers from 0 to 6), passives (answers from 7 to 8), and promoters (answers from 9 to 10). To calculate the NPS, the share of detractors is subtracted from the share of promoters. Hence, the higher the NPS the higher the overall satisfaction. Tracking the NPS for current and future customers provides a better picture of customer behavior towards the company than surveying only current customers as future customers have a significant impact on the company’s future performance.
Customer satisfaction is well-known for assessing customer mindset. Throughout the previous part of the article, it has been used to measure satisfaction at individual touchpoints. However, it can also be applied to measure the overall satisfaction with the CX. It can be measured with various scales developed by external agencies such as the American Customer Satisfaction Index (ACSI) or through customer surveys which enable customers to be considered on an individual basis.
This article provides an overview of the state-of-the-art metrics to evaluate online CX. The metrics are applicable in a broad online environment, in B2B and B2C settings, and across many industries. However, there is a variety of metrics that they differ in their effort to be measured. For this reason, managers need to consider the extent to which the benefits of measuring the CXQ are more significant than the costs. For example, in some cases, it might be challenging to obtain the data when relying on a third party to provide it or secondary data may not fit the theoretical constructs or is not compatible with the available data.
The metrics serve as a foundation for CXQ assessment and aid in identifying areas for improvement. There is no all-in-one solution applicable across companies, as the objectives of the CX differ with customers, products, companies, and industries. Those objectives should be defined in advance and appropriate metrics should be selected in accordance. This implies that organizations do not necessarily need to perform well on each touchpoint, but on those strategically relevant to them. To account for the individual character of a firm and its CX, it might be necessary to additionally develop its own, context-specific key performance indicators.
This article categorizes the metrics along the customer journey. Note that the structure ignores the connections and blurred boundaries between the individual phases of the customer journey, firm-controlled and non-firm-controlled touchpoints, and online and offline touchpoints. Further, be aware that customer, situational and socio-cultural aspects need to be considered as well. Additionally, the article did not provide any benchmarks. As benchmarks set the standard against which performance is evaluated, the setting of the benchmark determines the observed level of performance. Since the benchmarks vary from industry to industry and depend on the situation, they are not given, yet they are indispensable and must be considered for practical application in any case.