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A data-driven approach to understanding and improving the customer experience is critical to company health. But ironically, the proliferation of customer experience (CX) metrics is making the practice of doing so more challenging. At a large organization, metrics may number in the hundreds — so many that it is difficult to manage them, apply insights from them across the whole customer journey, and communicate what they mean to top executives.
Today, a typical customer receives a CX survey within minutes of checking out of a hotel, ordering a product, or contacting a service center. What began with simple satisfaction surveys and customer interviews has evolved into a complex system of metrics encompassing customer perceptions (measures of customers’ feelings), operational indicators (measures of how well the company’s CX-related processes work), and financial outcomes (such as sales, profits, and market share). Companies often collect specific metrics because the measurements are well known or commonly tracked within their industry, without carefully considering whether they are relevant to improving their customers’ experience.
As a result, effectively using the plethora of CX metrics being collected is becoming increasingly challenging for managers. We will explain how to create more efficient and effective CX management programs by eliminating low-value metrics and mapping a smaller set of key CX metrics across the customer journey. Those practices emerged from our consulting work with a group of 14 companies in the subscription services sector that had come together to share data and practices. Our insights are also grounded in our experience and our review of the existing literature.
Managing CX Metrics Overload
According to research firm Gartner, most large companies use more than 50 CX metrics — with some using as many as 200 — with various metrics managed by different people in different parts of the organization.1 Among the 14 subscription services companies we observed, we found that across channels — call centers, chat, web pages, email, and brick-and-mortar retail locations — all of them employed multiple measures of CX performance, totaling well over 100 CX metrics used within the industry. Collecting, compiling, and analyzing the daily, weekly, monthly, quarterly, and annual data measurements required extensive human and financial resources. We set out to determine which metrics provide the greatest value and which are of low value and could be eliminated, starting with a deep look at the CX metrics used in the call center channel.
Call center performance data informs managers primarily about operational effectiveness and efficiency and, to a lesser degree, customer perceptions, which are typically measured through metrics such as net promoter score (NPS) and customer satisfaction score (CSAT). While operational and perception data are essential, companies are most interested in tracking how CX investments affect measures such as sales, customer retention, and market share. A key question for the companies was “Which call center metrics reveal valuable insights into customer knowledge, attitudes, and behaviors, and how do these affect company performance metrics?”
First, we created a list of all CX metrics used within the call center channel and narrowed the list to those metrics for which the subscription services companies had shared operating definitions and measurement methods. This resulted in a final list of 13 CX metrics that the companies agreed were the most relevant for key dependent variables of churn, contact rate, and NPS. For companies in a different industry, a CX manager conducting a similar analysis might use more than three dependent variables; the number of dependent variables depends upon the complexity of the business and marketplace situation. Companies that have an extensive product mix, serve multiple markets through an omnichannel strategy, and require complex customer journey mapping may identify dozens of relevant CX metrics.
Next, to identify potentially redundant or low-value CX metrics, we performed a regression analysis of the 13 metrics used to monitor call center performance and determined the strongest and weakest contributor metrics to the dependent variables. (See “Predictor Scores for CX Metrics.”) The aim was to learn whether one or more of the 13 metrics could be eliminated without sacrificing important information. Multiple regression analyses can be conducted to identify groups of CX metrics that account for 75% or more of the variance in the dependent variables. We recommend identifying at least six metrics that indicate customer perceptions, operational performance, and financial outcomes — two within each of those three metric categories.
Finally, we tested the regression outcomes to build internal collaboration and determine the companies’ comfort levels with deleting marginal CX metrics. Although this approach requires minimal resources and disruption to processes, conducting a trial to assess full-scale feasibility and identify potential benefits is recommended. During the trial period, we learned a great deal about the challenges and opportunities of full-scale implementation. For example, the CX managers realized that organizational communication would play a critical role in minimizing staff concerns that changes might lead to staff displacement or diminished role importance. By positioning the metrics reduction as an incremental innovation and proactively communicating the goals of the trial, the group of CX managers were able to maintain staff members’ trust.
Our analysis of call center metrics found that although several of them demonstrate substantial predictive power, only one explains the majority of the variance in the NPS-dependent variable: IVR deflection rate, the percentage of calls that are redirected from a live agent to an interactive voice response system. Three different metrics each explain 30% to 40% of the variance in churn and contact rate. The regression also shows that service level (the percentage of calls answered within 30 seconds) and call transfer (the percentage of incoming calls transferred to a different queue) are weak predictors of the variance for all three dependent variables. While we might speculate on the reasons for those low prediction rates, the two weak predictors should be considered for elimination from the CX metrics inventory. There may be other reasons to continue measuring service level and call transfer rate, but at a minimum, managers should consider deleting them.
Most subscription-based companies rely on contact centers as the primary channel for building and sustaining customer-company relationships, so using multiple measures is understandable. However, purging low-value metrics reduces costs and allows resources to be redirected to reducing customer pain points and improving the overall customer experience. In other words, there are multiple benefits in eliminating metrics that do not significantly affect a critical outcome.
How Reducing the Count of CX Metrics Creates Value
By identifying and eliminating metrics that contribute little to understanding the variance in key dependent variables, managers can save human and financial resources associated with tracking them. For example, in the subscription sector, two of 13 metrics are strong candidates for elimination — a potential reduction of approximately 15% of the industry’s metrics — and that is in the call center channel alone. Today, companies operate in an omnichannel environment, connecting with their customers both face-to-face and in multiple digital channels. Each channel uses multiple measures of customer experience, so there is potential to consolidate many metrics. Doing so should not only simplify management but also reduce the number of surveys that customers are presented with — potentially reducing the survey fatigue that has made survey data less reliable.
Among the 14 companies participating in our research, each eliminated at least one metric, and four eliminated three metrics. In post-trial meetings with the CX executives, the general sentiment was “Why didn’t we do this sooner?” Further, the statistical analysis of metrics had other positive effects, such as disrupting ingrained thinking about metrics and the “we’ve always done it this way” mindset. Breaking the legacy pattern also means avoiding the temptation to add new metrics — at least until they have been shown to provide insights into desired outcomes such as sales or churn reduction. In this sense, the statistical analysis method supports tying a metrics inventory to meaningful KPIs.
With a shorter list of CX metrics in hand, managers can look at how to use them more effectively. One way to do this is to map metrics to stages in the customer journey to gain insight into whether the company delivers the right experience at the right time and in the right channel as customers move through the buying process. The entire customer journey includes multiple touch points and all of the experiences a customer has with a company, from initial awareness and interest in the product category through selection, purchase, use, cancellation (churn), and recovery.
The metrics inventory the 14 companies used covered the entire customer journey within the call center channel — from onboarding (30 to 90 days after service activation) through churn and resubscription. Because delivering excellence during the onboarding stage is key to several financial outcomes, including lowering service delivery costs, enhancing customer retention, driving growth, and increasing profits, the companies elected to focus on that segment of the customer journey.2 Therefore, we set out to learn more about the onboarding process and its implications for CX metrics, including how and why customers use a range of touch points and how that information could help the companies align their metrics inventory with customer behavior.
Seeking Insights for Metrics Journey Alignment
The link between customer journey and CX metrics is often weak due to a disconnect between marketing and CX functions that leads to metrics that are not directly related to the most relevant customer knowledge, attitudes, and behaviors. While many marketing departments have built customer journey maps, strengthening this connection may require creating, or refreshing, a customer journey map for specific aspects of the customer experience.
We conducted such an exercise with our client group, choosing to follow a design-thinking approach in order to gain deep insight into the customer onboarding experience. We worked with 15 of our clients’ new customers, guided by three facilitators. The effort yielded a detailed understanding of the onboarding journey, including but not limited to information search, vendor selection, service activation, first billing, and first service incident. We then sought to align CX metrics across each step of the customer journey, including identifying which CX metrics were relevant to the customer’s knowledge seeking, attitude formation, and behavior across the prepurchase, purchase, and post-purchase stages. (See “Mapping CX Metrics to the Customer Onboarding Journey.”)
Making that connection between metrics and journey revealed a misalignment between what is measured and what should be measured — and also made it easier to identify metrics that were not well aligned with customer actions. This led to the addition of appropriate CX metrics at each phase (knowledge, attitudes, and behaviors) and across all three stages of the customer journey.
For example, some companies had tracked CX during the purchase stage (sales, wait/hold time, close rate) and the post-purchase stage (CSAT, repeat purchase rate, visits to customer premises) but not the prepurchase stage. Most companies also measure NPS at the end of the onboarding process. However, this metric is also useful for tracking customers’ knowledge and attitudes at the start of their onboarding journeys: Insights into customers’ reactions to their initial interactions with a company can enable real-time intervention, particularly when an NPS is low. Training staff and identifying opportunities for product development and improvement are two ways to turn around subpar customer reactions to their initial experience with the company. Conversely, a strong NPS can help a company recognize what it is doing well. Understanding what customers want in the knowledge phase and when their attitudes about the company are forming enables CX managers to capitalize on these insights at the start of the customer journey, thus enabling them to have a significant impact on the overall journey.
More broadly, metrics alignment enables targeted strategies that improve operational efficiency, customer satisfaction, and onboarding adoption rates. The figure “Mapping CX Metrics to the Customer Onboarding Journey” provides examples of suitable CX metrics at each phase and stage of the onboarding journey. These example metrics are drawn from established CX metrics practices and are further supported by scholarly and professional literature and what we have seen through our CX work with dozens of companies.
Mapping CX metrics to a customer’s stage in the buying process can reveal common measurement gaps. For example, financial services companies typically use NPS as the sole measure of CX. The “likelihood to recommend” score in NPS is valuable, particularly within an industry that relies heavily on recommendations; however, this reliance on NPS means that no metrics are used during the prepurchase or purchase (transaction) stages. Metrics for trust and brand ranking would be helpful for gaining insight into the prepurchase stage, while consumer sentiment and loyalty metrics would be helpful in the purchase stage. Also, given the significant customer effort required to complete a transaction, measuring customer effort is important, particularly measuring “expected effort” versus “experienced effort” during the purchase stage. Identifying the expected-experienced gap helps identify customers’ pain points along their journey.
Measurement gaps such as those described occur regularly and are often the result of companies becoming overly attached to one or two measures. Ideally, companies will periodically review and align CX metrics with specific customer behaviors along the customer journey.
Benefits Gained From CX Metrics Rationalization and Mapping
Applying the two easily implementable approaches we have described for managing CX metrics can provide many benefits to a variety of businesses, regardless of their size or industry. They are both relatively low cost and low tech and therefore do not require extensive resources to undertake.
Our straightforward statistical analysis gives companies a quick way to gauge the strength of each CX metric’s relationship to KPIs and subsequently streamline their inventory of metrics. Going further and mapping metrics to the customer journey ties measurement directly to customers’ wants and needs. As a result, CX metrics should provide deeper insights into how companies can build and improve customer-centric experiences.
The collaborative work we undertook with the group of subscription service companies also led to an intriguing and perceptive discussion among CX managers about how a company’s culture and business model shape what is measured. For example, profit-first cultures tend to focus on operational efficiency and thus turn to metrics that focus on identifying cost-saving opportunities that flow to the bottom line rather than reducing customer pain points. In contrast, customer-first cultures focus more on understanding customers’ motives and the emotions underlying their purchases, loyalty, and advocacy, with an eye toward improving the customer experience and, ultimately, sales.
On a broader level, the practices discussed in this article help employees develop their ability to assess CX, enhance their skills, and cultivate knowledge that will advance their company’s goals. Among the subscription service companies we worked with, two additional outcomes emerged from our two proposed solutions: Three companies built quantitative models to better understand the factors that drive customer turnover, and other companies used mapping to better align CX metrics across additional segments of the overall customer journey.
The thousands of brands that measure CX all have different priorities, organizational structures and processes, marketplace environments, and resources; however, they all face the challenge of creating the optimal inventory of CX metrics. The two solutions we have presented here can help CX managers improve their use of metrics, enhance company learning, and, ultimately, improve the customer experience.