Relationship measurement studies have long been at the heart of organizations’ customer experience (CX) efforts. They not only establish a baseline for customer relationship health, but the insights they generate drive the strategic direction and vision of the CX program and help to correlate improvements in CX with tangible financial impact.
However, despite widespread use, relationship measurement programs have failed to evolve in recent decades, remaining stuck in the past with outdated processes and legacy systems. Even as other areas of CX have capitalized on recent technological and operational innovations, most relationship measurement programs still:
- Follow a rigid cadence and structure. Most relationship measurement programs continue to distribute identical surveys to all customers on an annual or bi-annual basis. This periodic cadence limits the strategic value of the survey as it only surfaces insights about poor experiences after it’s too late to take meaningful action. Plus, the static question structure and lack of personalization means that these surveys also often ask customers outdated or irrelevant questions. This lack of flexibility not only creates poor experiences for customers, but because some customers are inherently more valuable to the business, asking all customers the exact same questions and weighting their responses equally makes identifying the most impactful experience improvements difficult.
- Obsess about scores. While relationship metrics – such as NPS, satisfaction, or likelihood to return – are undeniably important for tracking and improving customer experiences, existing measurement programs tend to treat these metrics as the ultimate goal defining CX success, rather than what they actually are… a tool that helps organizations take meaningful, targeted action. This obsession with numbers often leads organizations to waste time and resources debating and comparing scores, preventing them from implementing the changes that would actually lead to improved relationships and better business results.
- Lack meaningful context. While topline metrics, like NPS and OSAT, are simple and easy to understand, they are narrowly focused on the company’s own performance, assessed by its current customers. Organizations generally contextualize their scores by benchmarking them against the performance of the broader industry. While this benchmark can provide some value, it doesn’t explain enough of the variance in relationship health, which is impacted not just by the experience a company delivers to its customers, but by how it performs relative to top competitors and whether or not it lives up to its brand promises.
Evolve Your Relationship Management Program
Many of the limitations of current relationship programs stem from a core issue – they’ve been built as measurement programs. Rather than focusing on creating better experiences, these programs have been fine-tuned to deliver the same metric over and over again. We believe that it’s time to rethink these efforts and shift the focus from reporting to driving action.
In order to produce richer insights that ultimately lead to better customer experiences and smarter business decisions, organizations need to evolve their relationship measurement programs into relationship management systems.
To transform your relationship measurement program into a relationship management system, you need to establish the following capabilities:
- Dynamic and Always-On Listening. Rather than sending a survey to every customer on an arbitrary date once or twice per year, modern relationship management continuously collects health data by staggering invites and attaching them to moments that are meaningful in an individuals’ customer life cycle, such as the anniversary of their first purchase or immediately prior to a subscription renewal. To determine both when to send a request for feedback and which experiences, journey touchpoints, or other areas to request feedback on, organizations should use operational data (O-data), like the customer’s purchase or usage data, interaction history, customer tier or segment, and demographic information, which should live in customer profiles that are created and dynamically updated for each individual.
- Comparative Insights. Traditionally, “relationship health” has been defined fairly narrowly, limited to the organizations’ performance on absolute metrics around operational effectiveness and customer sentiment like NPS or OSAT. While this data might produce valuable insight into customer attitudes and pain points, it doesn’t offer any insight into how an organization performs relative to other brands a customer might be using or how a brand’s positioning might impact customer expectations around experiences. Modern relationship management systems expand their view of “relationship health” to include any influences or experiences that may affect a customer’s relationship with an organization. This includes things like the strength of a brand’s promise and an organization’s ability to execute consistently on that promise, as well as an organization’s CX performance relative to its top industry competitors. This broader conception of relationship health will not only help the CX team improve the organization’s internal customer experience efforts, it will also help the larger organization make better strategic decisions about where, how, with whom, and on what it competes.
- Financial Linkage. To be successful over the long term, CX programs need buy-in from employees and leaders across the organization, which requires CX teams to clearly connect their work to the financial outcomes that matter to other stakeholders. Technical and financial constraints have historically hampered efforts to link relationship measurement results with key business metrics. However, modern programs – equipped with advanced analytics capabilities – are able to easily and inexpensively make this connection by combining the experience data (X-data) captured through the relationship study with O-data from customer profiles, as well as any relevant external benchmark data. Housing all of this information in a single system allows the CX team to not only understand and forecast, but also measure how improvements in the experiences of certain customers or segments results in business impact. This type of analysis allows CX teams to draw a direct connection between customer attitudes, behaviors, and key financial metrics like revenue, attrition, customer lifetime value, and average customer spend. Ultimately, the ability to correlate CX and business results helps to both guide cross-functional investment and develop buy-in and engagement for CX efforts across the organization.
- Action-oriented. Modern relationship management systems emphasize taking action on insights rather than just chasing higher metrics. This evolution is driven by technological advances in data collection, workflow integrations, and analytic capabilities. These new capabilities are built on the combination of X- and O-data, which allows the program to produce automated actions and predictive insights. For example, CX teams can now monitor aggregate or segment-level relationship health trends and set up alerts that automatically route information to the relevant teams or individuals. In addition to surfacing existing issues, these programs also use the X- and O-data to generate suggested actions, which allow employees to quickly respond to the feedback in a way that’s personalized to both that customer’s segment and their individual preferences and historical experiences. And because the data a modern program collects builds up over time, it becomes increasingly predictive in nature, with the ability to forecast future customer behavior like churn or increased purchase frequency. These predictive insights not only allow the CX team to take meaningful action to improve individual customer’s experiences, but they are also able to feed that information back to the broader organization to improve the business’s broader products, services, and communications.
The bottom line: Drive better experiences and business decisions with a relationship management system.
Sarah Alio is a Product XM Scientist with Qualtrics, specializing in Relationship Health
Isabelle Zdatny, XMP, CCXP, is an XM Catalyst with the Qualtrics XM Institute