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.