Source: Visit websiteWhile a survey-reliant CX strategy is holding CX programs back, we aren't advocating that they stop surveying customers. Instead, they should reduce their reliance on surveys and use that feedback data as part of a more comprehensive quantitative approach.
After discussions with dozens of CX leaders, top vendors, and service providers in CX analytics, we found a consensus on several steps organizations must take to implement advanced CX analytics successfully. Among the five key components presented, two demand considerable attention:
Another variation in CX analytics is leveraging machine learning models to predict common CX survey metrics like Net Promoter Score℠ (NPS) or customer satisfaction (CSAT). While novel, most organizations would be better served predicting the actual outcomes of customer behavior with direct financial impacts rather than making the effort to develop these capabilities only to reinforce challenges associated with relying on customer perceptions to manage experiences.
While advanced analytic techniques are uncommon in CX practices today, CX programs and leaders should challenge themselves and find a path to facilitate, collaborate, or expand the CX mandate to pursue a more quantitative approach that will prepare them for the future of CX.
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