Traditional NPS surveys vs. Glaut’s AI-powered approach

Customer experience surveys

When measuring Net Promoter Score (NPS) in general, traditional surveys often involve 30+ items, requiring respondents to rate their experiences on a scale of 1 to 10. This approach  presents several challenges:

• Survey fatigue: traditional surveys contain 30+ questions, leading to disengagement.
• Limited depth: numeric scores lack the context needed to understand user sentiment.
• Bias & inconsistencies: respondents may provide socially desirable or inconsistent answers.
• Missing out key insights: pre-defined answers might not include specific nuances which are important for the customer

Glaut’s AI-powered approach

Glaut streamlines the process by asking just one question, but that’s only the beginning. Our AI-driven follow-ups dive deeper, capturing the why behind each response in real-time. By dynamically adjusting based on user input, we extract rich qualitative insights that traditional surveys miss, all while keeping respondents engaged.

Briefing and data collection

For this use case study, we focused on understanding user sentiment toward Prime Video compared to Netflix. Our key objectives were:

1. Brand awareness: understand Prime Video’s market position relative to competitors.
2. Emotional impact: identify key emotions that influence NPS.
3. User sentiment analysis: highlight what delights and frustrates users.

For this example, we used synthetic answers to test and refine the research design; they have no analytical value but ensure structural soundness.

Glaut integrates with any panel provider, allowing researchers to use their trusted suppliers while maintaining data integrity and fraud detection. Once real participants engage in AIMI interviews, Glaut collects and structures responses automatically.

Screening criteria

Participants must be subscribed to at least one streaming service.

We added these 3 screening questions:

1. In which of the following categories do you identify with?
2. What is your age?
3. Are you currently subscribed to one or more streaming services?

We identified 3 key questions to ask to gain deep insights from respondents:

1. Which streaming service do you watch most frequently?(open-ended)
2. How many hours per week do you use this service?(multiple choice: <2h, 2-5h, 5-10h, >10h)
3. How likely are you to recommend this service?(NPS question + AI-driven follow-ups)

The single question that matters:

How likely are you to recommend this streaming service to a friend or colleague? (0 = not at all likely, 10 = extremely likely)

AI-powered follow-ups: Glaut allows researchers to customize follow-up questions based on predefined criteria. This means you can tailor responses to dig deeper into specific aspects of user sentiment, ensuring richer insights. In this case, we opted for a simple follow-up logic:

• If the score is ≥8, follow up with: “What do you love about this streaming service?”
• If the score is ≤7, follow up with: “What prevents you from giving this streaming service a higher score?”

Data analysis

Once responses are collected, Glaut automatically categorizes them into standard NPS segments:

• Promoters (9-10) → Highly satisfied users likely to advocate for the platform.
• Passives (7-8) → Neutral users who are content but not enthusiastic.
• Detractors (0-6) → Dissatisfied users who may discourage others from subscribing.

The AI then extracts key themes from open-ended feedback, surfacing emotional drivers behind NPS scores.

Analysis 1: platform awareness

Goal: identify the level of awareness for each streaming platform.

Approach: named entity recognition to capture the platforms mentioned by users. This helps in understanding which brands are top-of-mind for users and the relative visibility of each service in the market.

Analysis 2: consumption behavior

Goal: understand the relationship between platform preference and time spent on the platform.

Approach: break down the usage hours by platform to analyze content consumption patterns. This analysis helps identify user engagement across platforms, revealing which services are more frequently used and for how long.

Analysis 3: NPS visual report (recommendation score)

Goal: evaluate user loyalty and satisfaction with the platform.

Approach: segment users based on their NPS scores (Promoters, Passives, Detractors) and visualize the results in a report. This allows businesses to identify areas where user satisfaction can be improved and where strong loyalty exists.

Analysis 4: positive emotional drivers

Goal: identify what delights users and drives positive experiences.

Approach: conduct thematic analysis on open-ended feedback to extract key positive emotions (joy, satisfaction, excitement). This reveals the aspects of the platform that resonate most with users, such as content variety, interface usability, and new releases.

• Joy → “I love the variety of content.”
• Satisfaction → “The interface is very intuitive.”
• Excitement → “I always find new and interesting series.”

Analysis 5: negative emotional drivers

Goal: identify pain points and frustrations that users experience.

Approach: thematic analysis of negative feedback to extract key frustrations (e.g., content removal, pricing issues, lack of exclusive content). This provides insights into areas that need attention and could present opportunities for service improvement.

• Frustration → “They always remove my favorite movies.”
• Anger/Indignation → “The price is too high.”
• Disappointment → “I expected more exclusive releases.”

By conducting these analyses, businesses can gain a deeper understanding of user behavior, emotional drivers, and pain points, allowing them to refine their strategies, improve customer satisfaction, and differentiate their offerings in the competitive market.

Reporting with Glaut's report builder to extract key insight

Glaut turned this research into a visual report in minutes thanks to its Report Builder, mapping out user emotions and brand perception across Prime Video and its competitors.

You can build a goal-based report prompting Glaut to investigate each of your initial goal, in this case:

• What are Prime Video’s strongest emotional drivers?
• How does its audience differ from Netflix users?
• What gaps represent opportunities for improvement?

Take a look at the full report generated with Glaut.

Conclusion

Glaut’s AI-powered NPS approach revolutionizes traditional surveys by focusing on a single open-ended question and using AI-driven follow-ups to gather deep, qualitative insights. This method eliminates survey fatigue while providing richer context to understand user sentiment. Unlike traditional surveys, which often lack depth, Glaut offers real-time, actionable data on emotional drivers and pain points, enabling businesses to make informed decisions and improve customer satisfaction and loyalty.

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