First, understand the difference between agent-level monitoring and business-level monitoring. When we think about a business-level form design:
- Identify reporting and analysis needs and define the necessary data fields (e.g., type of transaction, reason, channel, line of business, etc.).
- Differentiate between critical and non-critical errors, focusing first on critical errors for better performance.
- Measure and report each type of critical error individually. Separating these errors is important because they all have different impacts.
- Customer-critical (impacts the customer experience)
- Business-critical (impacts the business)
- Compliance-critical (legal/compliance violations)
- Identify customer-critical attributes (affect the customer positively or negatively):
- To understand and quantify these attributes, use a key driver survey or multiple regression analysis of overall satisfaction and attributes from your current CSAT survey.
- Including these drivers on the quality form ensures that quality results align with customer satisfaction (CSAT) and can serve as predictors.
- Find these drivers using key driver surveys or other customer feedback methods, such as complaints, survey data and social media analysis.
- Prioritize the drivers that have the most significant impact on the customer, as these are the critical attributes.
- Determine the related causal factors that lead to each critical error.
- For example, if understanding the customer’s issue is critical, identify reasons an agent might not understand the customer, such as not listening or not asking the right questions.
- For example, if understanding the customer’s issue is critical, identify reasons an agent might not understand the customer, such as not listening or not asking the right questions.
- Identify business-critical errors with business leaders:
- Result in unnecessary costs to the business
- Loss of revenue
- Lack of critical documentation, etc.
- Identify compliance-critical errors with the legal/compliance department:
- Breach of industry or governmental regulations, including privacy requirements
- Improper disclosures
- Anything that increases company liability
Attributes vs. Sub-Attributes
- Attributes capture the “what.”
- Sub-attributes capture the “why” and should be actionable.
- Sub-attributes may have multiple levels if the data needs to be broken out to be actionable.
Examples of attributes and sub-attributes:
- Attribute: Was the issue resolved?
- Sub-attributes: Why wasn’t it resolved? Was it agent-related (e.g., not understanding the issue, not asking the right questions)? Was it non-agent-related (e.g., company policy, system issues)?
Guidelines
- The wording of attributes and sub-attributes matters.
- Satisfier attributes should focus on maximizing performance.
- Dissatisfier attributes should focus on meeting minimum acceptable standards.
- Scoring should be binary (yes, no, not applicable).
- Each attribute should have a single focus.
- Ensure sub-attributes do not become attributes.
- Avoid prescriptive requirements/scripts.
Business Intelligence
Capturing the information above provides insights into customer behavior, company policy, products, marketing, competitor activities, self-service opportunities, etc. Discuss with business leaders what information would be useful and include it as a non-scored attribute that doesn’t impact overall results.
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Customer Satisfaction
Tonya Webber, Director at COPC Inc., specializes in process gap analysis, knowledge management, project management, and quality. With over 16 years in the customer experience industry, she has led major performance improvement initiatives, supported product launches, and managed third-party relationships.
Before COPC, Tonya was the Director of Operations at RealPage, leading a team of business and operations analysts. She holds a BA in Criminal Justice from the University of Texas at Arlington and has a rich operational leadership and customer success history.