The Future of CX

The Challenges Of Survey-Only CX

Customer experience (CX) measurement programs report that their most common challenges are driving action to improve experience quality and proving the financial importance of CX. One primary cause is their reliance on soliciting customer feedback, usually through surveys. Surveys don’t often provide definitive root causes that compel business functions to make changes, and the relationship between survey scores and financial performance remains theoretical in most organizations.

The Quantitative Future Of CX

Integrating advanced quantitative analytics into their strategy helps CX programs drive action and prove value. This involves shifting from treating survey score metrics as their primary output to using feedback data as an input to more advanced techniques. When CX programs combine customer feedback data with other metrics like operational interaction data, financial outcome data, and additional non-survey perception data, these inputs to advanced analytics can produce more actionable and financially connected insights than survey feedback alone.

Executing On The Promise Of Advanced Analytics In CX

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:

• Enabling a comprehensive experience dataset. This includes ensuring the availability, quality, and validity of a comprehensive dataset of customer perceptions, interactions, and the financial outcomes of their behavior. Most experts agree that this is the most critical and challenging aspect of implementing an advanced CX analytics strategy.
• Operationalizing insights from advanced analytics. While insights from advanced analytic techniques can prove fascinating in many organizations, acting on the outputs is crucial. This means using advanced analytic insights to take a proactive approach to CX, where organizations use diagnostics, predictions, and prescriptions to manage the experiences of all customers rather than reacting to feedback from a small percentage who respond to surveys.

Avoiding Missteps In The Adoption Of Advanced Analytics In CX

For our recent research, we have defined advanced CX analytics as “advanced analytic techniques — including diagnostic, predictive, and prescriptive machine learning — that identify how customers’ experiences affect their behaviors.” The terms “advanced analytics” and “predictive analytics” are used somewhat loosely in the CX ecosystem. While useful, language analytics, conversational and digital intelligence, and sentiment analysis differ from advanced diagnostic, predictive, and prescriptive methods. CX leaders should ensure that they understand these differences when pursuing quantitative CX strategies.

Final Advice

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.

Conclusion

In conclusion, advanced analytics is the future of CX, and it is essential for CX programs to leverage more advanced quantitative analytics to drive action, increase financial impact, and prepare for a more analytics-driven future. By integrating advanced analytics into their strategy, CX programs can shift from relying on survey feedback to using feedback data as an input to more advanced techniques, producing more actionable and financially connected insights.

FAQs

• What is advanced analytics in CX?
  Advanced analytics in CX refers to advanced analytic techniques — including diagnostic, predictive, and prescriptive machine learning — that identify how customers’ experiences affect their behaviors.
• What are the challenges of survey-only CX?
  The primary challenges of survey-only CX are driving action to improve experience quality and proving the financial importance of CX.
• How can CX programs leverage advanced analytics?
  CX programs can leverage advanced analytics by integrating customer feedback data with other metrics like operational interaction data, financial outcome data, and additional non-survey perception data to produce more actionable and financially connected insights.