Root Cause Analysis: Understand what really drives customer satisfaction

Key Driver Analysis (KDA) and Root Cause Analysis (RCA) both identify factors impacting customer experience or satisfaction, but they differ in purpose and approach. KDA pinpoints influential factors affecting satisfaction using statistical techniques, guiding businesses in prioritizing resources for maximum impact on customer experience.

Conversely, RCA systematically uncovers underlying causes of customer experience issues, moving beyond symptoms to find fundamental reasons. This process includes data collection, cause-and-effect analysis, and solution identification, aiming to prevent recurrence and improve customer experience by addressing root causes and implementing corrective actions.

Many companies we work for find the KDA doesn't give them enough details regarding actions they need to do to improve customer experience hence they look into the more detailed Root Cause Analysis models.

The model for Root Cause Analysis in customer experience and satisfaction relies on a combination of survey data and, optionally, internal data to provide a comprehensive understanding of the factors affecting satisfaction levels.

Minimum requirements:

1. Survey data: This includes responses from customers, typically collected through various customer satisfaction measurement tools such as NPS (Net Promoter Score) or CSAT (Customer Satisfaction Score).
2. Reasons for dis/satisfaction: Understanding customers' key reasons for being satisfied or dissatisfied with a product or service, which can be collected through surveys.
3. Closed-end statements: Quantitative measurements derived from questions with predefined answer choices, offering clear, concise insights into customer preferences.
4. Open-end questions: These provide a qualitative perspective on customer experience. Existing topic categorization should be used, or additional text analytics can be run to identify and categorize themes within customer feedback.

Optional items for a more comprehensive model:

1. Internal data: This can provide additional context and help identify trends or correlations between customer satisfaction and internal processes.
2. Behavioral and/or operational data: Integrating information on customer behavior or operational aspects of the business can help uncover hidden patterns, leading to a more robust and insightful analysis.

By incorporating these data sources, the Root Cause Analysis model can effectively identify underlying causes of customer experience issues and guide the implementation of targeted solutions for improving satisfaction.

Root Cause Analysis (RCA) is a versatile method that can be effectively applied across various industries and business models to improve customer experience and satisfaction. It is particularly beneficial for industries where customer feedback plays a crucial role in driving business success. If you have any type of customer feedback program, customer experience program or other type of program that includes customers giving you a score, Root Cause Analysis will be beneficial to you.

Both depend on the amount of data, markets, business units, products or other details you want to delve in. A standard delivery timeframe would be between 6 and 8 weeks. As to pricing, we offer a flexible model with one-time set up fees and quarterly subscription for updates afterwards.