UX SURVEY

What does a Customer Effort Score (CES) survey measure?

• How much effort customers put into solving an issue

• How satisfied customers are with the product

• How likely customers are to recommend the product

• How frequently customers use the product

When is a CES survey typically used?

• After a customer support interaction

• Before a product launch

• During brainstorming sessions

• After competitor analysis

What does a high Customer Effort Score indicate?

• The customer had difficulty completing a task

• The customer is very satisfied with the experience

• The customer recommends the product to others

• The customer used the product frequently

What is the primary purpose of a Customer Satisfaction Score (CSAT) survey?

• To measure how satisfied customers are with a service or product

• To understand customer effort in resolving issues

• To calculate the likelihood of customer referrals

• To explore customer demographics

How is a CSAT survey usually structured?

• A simple rating scale such as 1 to 5

• Open-ended narrative responses

• Complex branching logic

• Time-based performance tracking

A low CSAT score suggests:

• The customer is dissatisfied with the product or service

• The customer effort was low

• The customer will likely recommend the product

• The customer’s usage patterns are inconsistent

What question is commonly asked in a Net Promoter Score (NPS) survey?

• “How likely are you to recommend our product to others?”

• “How much effort did you spend using our service?”

• “What features do you prefer?”

• “What is your age and location?”

How are NPS responses typically categorized?

• Promoters, Passives, and Detractors

• Enthusiasts and Critics

• Satisfied and Dissatisfied

• Frequent and Rare users

What does a high NPS indicate?

• Many customers are likely to recommend the product

• Customers struggle to complete tasks

• The product has frequent technical issues

• Customers are unsure about using the service

Closed-ended questions are best suited for:

• Gathering measurable data quickly

• Exploring deep emotional experiences

• Encouraging detailed feedback

• Understanding complex user behavior