Customer experience (CX) measurement has been on the edge of an evolutionary tipping point for a few years now. Advancements in technology and accessibility across platforms have created higher levels of connectivity, sophistication, customization and speed. The improvements have revolutionized how a customer’s experience can be measured, refined and optimized.
Even though many of the same evaluation criteria used historically are active today, the depth and breadth of visibility required to meet customer’s evolving needs have changed dramatically.
Traditional CX Metrics Are Table Stakes
Despite their widespread use, traditional evaluation metrics such as goal attainment, desirability, effort, satisfaction and response times do not provide the most accurate measurement of CX. Most feedback mechanisms commonly used today intrinsically possess gaps and inconsistencies in the data and information they provide. These fundamental flaws require marketers to make assumptions and inferences to be able to tell a compelling story and generate actionable insights. Modern approaches to measurement seek to fill these gaps and look more holistically at the customer's interactions, interpretations and influences on the brand experience. Some of the more recent advancements in customer experience management (CXM) include performance evaluation metrics such as progressive engagement ratios, attribution model percentages, journey performance indexes, contextual feedback responses and usage patterns through autonomous response platforms.
To be fair, “traditional evaluation metrics” still provide valuable insight into CX performance. We hear a lot about Net Promoter Score (NPS), Customer Effort Score (CES), Customer Satisfaction Score (CSAT), First Response Time and sentiment monitoring. Additionally, many other metrics exist in specialized industries and environments, such as the bevy of data points included within the customer support and service realm, or any custom, service- or product-specific evaluation criteria. Finally, we have the hard number metrics. These are the numbers that directly support business outcomes, such as: customer lifetime value, cost of acquisition, growth rate, retention, attrition and churn, market share, as well as top and bottom line financial trends.
Consider the previously listed items as prerequisites and components that have created a baseline for the evolution of CX measurement.
From a high level, CX metrics have been transformed by technology that provides the ability to track more exhaustively across all channel touch points within the customer's lifecycle. The primary flaw in the previously listed measurement activities is they are all based on historical, single moments in time and do not capture the true value of the customer’s comprehensive experience. Leveraging more sophisticated analytics platforms with autonomous feedback mechanisms, marketers are able to gain a contextualized understanding of the customer’s experience, anywhere within the customer lifecycle. Below are five CX measurement methodologies and metrics that provide unique insight into both the path and the totality of the customer’s experience. Many of these metrics require visibility, access and control across the entire customer journey. You will need a minimum tech stack of products with offerings similar to Google Analytics, Google Tag Manager, Google Search Console, Qualtrics and HotJar.
5 Customer Experience Measurements for Today
Progressive Engagement Ratios
One of the biggest challenges for marketing and communications professionals is proving return on investment (ROI). Unfortunately, ROI is a single number, calculated from the sum of many complex activities and decisions, in support of a single business outcome. Proving strong ROI across many activities with little visibility or cohesion is no easy task.
As people become introduced to a brand, measuring an individual’s engagement and experience with a brand can theoretically begin. A progressive engagement ratio is the engagement performance of users against a single channel or touchpoint within a specific stage of the customer journey. That performance is then compared to the engagement performance of the channel or touchpoint within both the previous and subsequent stage of the customer journey. By calculating these ratios and identifying the difference between each, visibility and insight can be gained to areas of opportunity, friction or fall-off, through the entire customer experience being provided.
Although these metrics are relatively new in concept, our team uses these values to gain visibility into the impact each channel has on a customer’s affinity and efficacy toward a brand.
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Attribution Modeling Percentages
Understanding the value each touchpoint has on conversion is essential to know where to place credit where credit is due. By understanding the entire customer journey, percentages can be applied to touchpoints that contribute to conversion. In attribution models, the value of the conversion is distributed across all touchpoints along a conversion path. These numbers enable the ability to understand the true value each activity had on conversion. Marketers can use these percentages for allocation of future spend and focus, or to test new ideas.
Depending on the intent, attribution models can be organized around the beginning of a customer experience, critical milestones within the conversion journey, or at the moment of conversion. Each model provides insight into the activities that are attributed to the completion of a specific goal.
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Journey Performance Index (JPI)
Using the outcomes of progressive engagement ratios and attribution models, with reference to the “traditional evaluation metrics,” brands are able to evaluate the CX performance of the entire journey. By calculating this number at each stage of the customer journey, companies are able to determine the journey performance between awareness, consideration, decision, conversion and loyalty.
This number can also be applied to a singular pathway or stream of touchpoints within a customer lifecycle. By looking sequentially at connected marketing, communications, or support-related activities, the JPI can provide benchmarking capabilities to monitor the path’s performance based on a single number.
The JPI is based on a benchmark value of 1.0, with company or goal-specific range of fluctuation. Influences that affect the customer’s experience raise and lower this number in relation to the original index value. For example, a positively trending experience may be measured as a 1.2, meaning that all activities are netting a positive customer experience. Conversely, a negatively trending experience may be tracked as a 0.65. In this instance the average experience is still positive overall, but should be flagged as below the index value and should be proactively investigated and re-aligned. These numbers are dependent on audience, industry, spend (if applicable, for paid activities), and goal(s) for the touchpoint and/or channel being evaluated.
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Contextual Feedback Responses
Numbers can only provide so much visibility into the mindset and behaviors of customers. Obtaining feedback through some of the previously mentioned surveying techniques (e.g. NPS, CSAT, CES) leaves much room for question and interpretation. However, employing single-question surveys within an active experience can provide contextual insight to the actions and decisions of a customer in that moment.
Typically, survey instruments are employed at the completion of conversion or culmination of an experience. However, evaluating a customer’s experience at the culmination of many activities leaves little insight in the performance of activities to get to that milestone. By incorporating non-invasive feedback mechanisms, brands are able to gain a deeper level of insight into the performance outcomes in that singular moment.
Platforms, such as Qualtrics and others, inject micro-surveys (one to two questions) natively into a digital experience. These feedback instruments are designed to weave seamlessly into the experience and provide immediate feedback from the user. Paired with other evaluation criteria, these surveys provide context for the other data points being tracked.
Usage Patterns with Autonomous Response Platforms
Customer service and support has been transformed by the introduction of autonomous response platforms, such as chatbots. An individual's experience before and after purchase relies heavily on the relationship that is built with the brand over time. As brands are looking to find efficiency and cost savings, the adoption and use of chatbots, in lieu of larger support staff, has grown significantly.
The interactions users have with chatbots will be critical in fostering the growing needs of markets, where accurate responses, received promptly will increase in importance. A 2018 Deloitte AI report (pdf) predicted, “by 2020, the average person will have more conversations a day with bots than they do with their spouse.”
A wealth of insights exist in how customers interact with chatbots today and how brands can optimize experiences based on those responses. The depth and value of these interactions will continue to grow in importance as many autonomous response platforms begin leveraging artificial intelligence and tap other, larger neural networks.
Google, among other AI providers, has built recognition and response platforms capable of identifying real-time sentiment and emotions based on words, phrases and response patterns. It is only a matter of time before CX practitioners are able to monitor these trends and provide real-time optimizations to a customer’s experience.
Complex Customer Experiences Require Better Metrics
It is no surprise that the evaluation criteria of measuring a customer’s experience have become much more complex. The visibility into the behavior patterns of customers across digital and non-digital channels is revolutionizing how we continue to meet customer needs quicker and more accurately. As technology continues to allow for more breadth, depth and pace of trackable performance metrics, brands will have the opportunity to proactively meet their customer’s needs.
Our responsibility, as creators of experience, is to identify the ideal metrics that provide value and meaning to support both our customers and our companies.