Optimizing Customer Experience Through VOC and Web Behavioral Data
By integrating Voice of Customer (VOC) with web behavioral data, customer insights were visualized and used to optimize customer touchpoints and improve CX.
Customer Experience Optimization Through Integrated Data Analysis
A leading tobacco company in Japan was conducting various marketing campaigns but faced challenges in achieving the expected conversion rate. At the same time, its customer center was receiving a high number of inquiries related to marketing campaigns.
To address these challenges, Voice of Customer (VOC) collected through the customer center was analyzed together with customers' behavioral data on the website.
The insights gained from this analysis were used to improve web services, UI, inquiry support, and other customer touchpoints.
Addressing Challenges Across Marketing and Customer Support
Improving Conversion Rate
The company was running various marketing campaigns but struggled to achieve the expected conversion rate.
Reducing Customer Inquiries
The customer center received many inquiries related to marketing campaigns, creating a need to better utilize customer feedback and improve customer touchpoints.
Integrating Customer Feedback and Web Behavioral Data
Customer feedback collected through the customer center was analyzed together with web access logs and customers' behavioral history.
By combining these different sources of customer data, customer behavior and characteristics were analyzed and segmented. The resulting insights were then used to identify opportunities for improving customer experience.
CX optimization process from data analysis to implementation and performance evaluation
From Customer Data to Continuous CX Improvement
01 — Analyze Customer Data
VOC × Web Behavioral Data
Analyze customer inquiries and other VOC data together with website access logs and behavioral history.
02 — Identify Customer Insights
Customer Segmentation
Combine VOC analysis and behavioral history analysis to understand customer characteristics and identify customer needs and issues.
03 — Improve Customer Touchpoints
Implement & Evaluate
Use the insights to improve web-based customer services, UI, inquiry support, and systems, and evaluate the performance of these initiatives.
One-Stop Support Across Marketing, Customer Support, and Data Analytics
Rather than stopping at data analysis, the approach connects customer insights with actual improvement initiatives.
By working across marketing, customer support, and data analytics, customer touchpoints can be continuously optimized based on customer needs and behavior.
Marketing
Support the improvement of marketing initiatives based on customer insights and behavioral data.
Customer Support
Improve inquiry support and customer communication by utilizing VOC and customer feedback.
Data Analytics
Analyze VOC and web behavioral data to visualize customer insights and identify opportunities for improvement.
Continuous Improvement Through a High-Speed PDCA Cycle
Up to 80 initiatives and A/B tests in a year
Based on insights gained from customer data analysis, initiatives were designed, implemented, and evaluated through a continuous improvement cycle.
This approach enabled ongoing optimization of customer touchpoints, including web services, UI, inquiry support, and systems.
Improved Conversion Rate and Reduced Customer Inquiries
+4.5 points
Increase in Conversion Rate
Through CX optimization, the conversion rate increased by 4.5 points.
Approximately 75%
Reduction in Customer Inquiries
The number of customer inquiries decreased by approximately 75%.
From Data Analysis to Implementation and Continuous Improvement
L01 — Understand Analyze VOC and web behavioral data to visualize customer insights.
02 — Improve Translate insights into improvements across web services, UI, inquiry support, and other customer touchpoints.
03 — Optimize Evaluate performance and continuously improve initiatives based on customer data.
Looking to Optimize Customer Experience Through Customer Data?
transcosmos provides one-stop support across marketing, customer support, and data analytics to help businesses improve customer experience through data-driven initiatives.
