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Advanced Analytics: The Future Of CX
Despite the recent setbacks in overall experience quality as seen in Forrester’s Customer Experience Index (CX Index) benchmarks, customer experience (CX) remains a top priority for many organizations. Unfortunately, these companies have struggled to realize tangible benefits from their CX initiatives.
It is essential that CX programs leverage more advanced quantitative analytics to drive action, increase financial impact, and prepare for a more analytics-driven future.
Challenges In Survey-Only CX
CX measurement programs often report that their most common obstacles are inducing action to improve experience quality and proving the financial significance of CX. The primary cause of this issue is the reliance on soliciting customer feedback, typically through surveys. Surveys rarely provide definitive root causes compelling business functions to make changes, and the connection between survey scores and financial performance remains theoretical in most organizations.
While a survey-reliant CX strategy holds CX programs back, it’s not suggesting they stop surveying customers entirely. Rather, they should reduce their reliance on surveys and utilize that feedback data as part of a more comprehensive quantitative approach.
The Quantitative Future Of CX
Integrating advanced quantitative analytics into their strategy enables CX programs to drive action and demonstrate value. This involves shifting from treating survey score metrics as the primary output to using feedback data as an input for more sophisticated techniques. By combining customer feedback data with other metrics like operational interaction data, financial outcome data, and additional non-survey perception data, these inputs can produce actionable and financially connected insights that surpass those generated by surveys alone.
Implementing Advanced Analytics In CX
After engaging in discussions with dozens of CX leaders, top vendors, and service providers in CX analytics, a consensus emerged on several steps organizations must take to successfully execute advanced CX analytics. Two key components require significant attention:
1. Enabling a comprehensive experience dataset. This includes ensuring the availability, quality, and validity of a comprehensive dataset of customer perceptions, interactions, and financial outcomes of their behavior. Most experts agree that this is the most critical and challenging aspect of implementing an advanced CX analytics strategy.
2. Operationalizing insights from advanced analytics. While insights from advanced analytic techniques can be fascinating in many organizations, taking action on the outputs is crucial. This means using advanced analytic insights to take a proactive approach to CX, where organizations utilize diagnostics, predictions, and prescriptions to manage experiences across all customers rather than simply reacting to feedback from a small percentage who respond to surveys.
Final Advice
While it’s tempting to rely solely on advanced analytics techniques like language analytics, conversational intelligence, sentiment analysis, or even predicting common CX survey metrics such as Net Promoter Score℠ (NPS) or customer satisfaction (CSAT), we recommend that organizations prioritize the actual outcomes of customer behavior with direct financial impacts.
Source: https://www.forbes.com/sites/forrester/2025/03/21/advanced-analytics-the-future-of-cx/
