As you prioritize insights to drive Customer Experience (CX) changes, you will also need to consider a measurement that will reflect the impact of those changes and translate to return on investment (ROI) through increased revenue, reduced churn, reduced cost, and optimized productivity.
According to a survey by CX thought leader Forrester, “nearly one out of two organizations use Net Promoter Score (NPS)* to gauge CX success.” While Net Promoter Score or other similar survey metrics are designed to measure customer loyalty to the organization it might not be ideal in directly measuring customer experience changes. Companies should not anticipate survey metrics, like NPS alone, to significantly shift with each CX improvement although improvements over time may result in an eventual lift.
Why Not Rely On Survey Metrics Alone for CX Improvements?
There are some challenges and limitations to using survey metrics to measure CX changes namely the method to gather feedback. In order to calculate a survey based metric it must be solicited from the customer through standardized questions and needs to be solicited often, think pre- and post-improvement, which can lead to survey fatigue and small sample sizes. Depending on survey practices, it might take time to gather responses, analyze, and report upon the results. Additionally, no matter how delighted a customer is they might never recommend certain products, services, or types of companies to others so asking their likelihood to recommend will not be the best indicator of experience. This can be the case with some B2B companies, financial services, utilities or companies with a very specific range of customers.
As your CX program is looking to trend and measure the impact of changes there should be a greater focus on project metrics designed to specifically measure improvements as they align to strategic goals and returns.
Language-Based Metrics Are Best Indicators of CX Success
Measuring the impact of CX improvements should move beyond the survey for collection and be measurable across all sources of customer feedback to cast the widest net and remove sample size concerns. Moving to language-based indicators of success and improvement in all customer feedback sources such as calls, chats, emails, in addition to surveys will allow for measurement even when not solicited from customers. Unlike solicited metrics language-based measures allow for tuning for accuracy of intended measurements. This process provides an opportunity for stakeholders to engage with the data and be part of the sign off process which brings trust and credibility to the measurement results.
This can be designed as a composite of measurements and tuned specifically to the experience to be improved. For example, support centers might look to measure and improve the customer experience by reducing customer effort, improving customer emotion, and driving issue resolution. To define high-effort experiences, language based metrics can measure the percentage of contacts which indicate a frustrating or difficult process and result in channel switching or transfers. CX programs can look to improve customer effort by focusing on transfers which occur early in the contact and building improvements to the IVR or web chat flows. Additionally, frustrating experiences mentioning the website or customer portals might indicate issues with current self-service experiences which in turn drive contacts to the support center. Measuring experience in this manner helps to provide tactical improvement opportunities which lead to reduced operating costs and a positive customer experience.
At Farlinium, we have helped CX programs for world class organizations to identify and measure the impact of customer experience improvements as they relate to strategic goals through text analytics. If interested, please reach out and we’ll be happy to assess your program and let you know how we can help.
* Net Promoter and NPS are registered service marks, and Net Promoter Score is a service mark, of Bain & Company, Inc., Satmetrix Systems, Inc., and Fred Reichheld.