By Paul Cole, President – inQuba N.America. Published by Marketing News Magazine, USA.
Today’s marketers are pressured to deepen their analytical capabilities in order to successfully compete in today’s Big Data economy. As such, I thought I would explore what’s known as “journey” analytics—that is, driving “insights into action” to deliver a better customer experience. Hopefully by now you buy into the premise and volumes of supporting data that demonstrates that how you treat your customers across the full lifecycle of interactions, from initial inquiry through repurchase, has major consequences on your company’s overall growth and profitability.
Within the customer experience (CX) field, there are two operative words that anchor our quest to deliver customer delight and company differentiation: journey and experience. A journey is the set and sequence of events that depicts the customer-to-company relationship, as seen through the eyes of the customer, from inquiring to purchasing to onboarding to consuming to repurchasing. This, in turn, produces emotions that characterize the customer experience. The experience then produces a memory that ultimately becomes the basis of both customer outcomes (brand supporter or detractor) and business outcomes (buy more/again, stay longer, or defect).
Journey analytics is all about interpreting customer input—be it structured (surveys) or unstructured (Facebook posts)—to enable you to improve those operational processes that most impact customers’ perception of the experience. If properly constructed, a journey data repository allows managers to drill down from the aggregated Net Promoter Score (NPS) or Customer Satisfaction Index (CSI) data to customer level in order to better understand root causes and predict potential consequences of alternative actions. As a case in point: Consider the example of an insurance company. The company’s analytics dashboard starts with NPS and CSI scores at the top and then cascades through a regional view, a decomposed journey view, and then down to the individual customers’ ratings and comments.
The most recent reporting revealed an unusual drop off in NPS and a corresponding increase in policy surrenders, signaling a potential customer service issue. During this same time period, this company had followed through on its plan to outsource its claims assessment sub-process to a third-party provider. An in-depth analysis of the customer input data was able to pinpoint that the source of discontentment was indeed their new third-party partner. More specifically, the CX analytics team was able to determine that a specific set of assessors in one particular region had been miscommunicating customer policy, resulting in customer alienation.
Learning this, the team then ran a series of sensitivity analyses based on embedded multivariate statistical routines to evaluate how impactful the quality and timeliness of communications is on policyholder behavior. Realizing its criticality, the field operations team then took immediate remedial action with its assessors by reinforcing training and setting new KPIs. It also launched a service recovery communications campaign targeted at affected policyholders to both apologize and clarify the claims process, thereby averting a potentially widespread and costly problem.
All of the above capability exists today and was applied in this real example, but ask yourself this question: Does our organization have this level of enterprisewide visibility into our customer journey and the (perceived) performance of the processes that we operate to support it? If you aspire to be a truly customercentric company, it is incumbent upon you to improve your customer IQ by investing in and formalizing your approach to journey analytics and management.