NPS reasons
A focused follow-up technique that turns a Net Promoter Score into a conversation. Rather than accepting the score and moving on, this methodology asks participants to explain it – capturing both the experiences that shaped the rating and the feelings those experiences produced. The result is richer, more actionable data than a score alone can provide.
The qualitative theory
Section titled “The qualitative theory”NPS surveys are good at capturing a number. They’re less good at explaining it. A score of 7 from one person can mean something entirely different from a score of 7 from another – one may have had a fine but forgettable experience, the other a genuinely positive one that their competitive loyalties held back from a 10. Without the reasoning behind the score, the number tells you little about what to do.
This methodology works with two interconnected dimensions: experiences (concrete things that happened – interactions, moments, product features, service encounters) and feelings (the emotional responses those things generated). These are not the same. A participant can describe a long wait time as a negative experience while also noting it was handled with warmth – the experience and the feeling it produced are distinct pieces of insight, and both matter for understanding the NPS score.
The EVE Qual Pro strategy is to break out experience probes by experiences and things – these can then be explored and related back to how they make the respondent feel and their effect on advocacy. We then have a generic emotional probe that seeks to explore any emotional references. If there are no emotions expressed, this is likely to be prompted for depending on what else is mentioned, building up an interconnected understanding between emotions, experiences and advocacy. We then always close by prompting for a suggested improvement to improve advocacy.
Configured settings
Section titled “Configured settings”This section documents every setting in the methodology so you can understand the intent behind each choice.
Research framing
Section titled “Research framing”| Field | Value |
|---|---|
| Context & Background | The goal is to develop a rich and detailed understanding of the extent to which a person would recommend a brand, product or service to someone else using the NPS system |
| Research Objectives | Why people do or do not advocate for a brand, product or service |
| AI Moderator Tone | Friendly and polite |
The tone is warm but composed. NPS conversations often involve both praise and complaint – a friendly tone keeps the conversation open, while polite keeps it from becoming either too casual or too confrontational when participants are expressing dissatisfaction.
Conversation introduction
Section titled “Conversation introduction”Please share with me why you rated your likelihood to recommend
{brand question}
{brand question} is a placeholder – replace it with the piping syntax for your NPS question variable before publishing. For example, if your NPS question variable is NPS, use @NPS to pipe in the score, or @NPS_CurrentLabel to pipe in the label. This personalises the introduction with the participant’s actual score.
Laddering questions
Section titled “Laddering questions”One question, with Paraphrase on:
| # | Question | Purpose |
|---|---|---|
| 1 | Any further thoughts on your rating? | Extends beyond the participant’s immediate front-of-mind response before structured probing begins |
The goal here is extension of topics, not laddering into the first topic – that comes later through probing and prompting. A single open question gives participants space to add anything they haven’t mentioned yet before the AI moderator moves into structured follow-up.
Default probe
Section titled “Default probe”Tell me more about
{{topic}}?
Paraphrase on. A generic opener that works across all topics. Paraphrase is on because natural variation in follow-up phrasing is appropriate here – the specific wording matters less than the topic-level overrides, which carry the cross-dimensional structure.
Default prompt
Section titled “Default prompt”What about
{{topic}}, can you tell me more about that?
Paraphrase on. Kept open and neutral so it doesn’t signal what kind of response is expected.
Probe & prompt limit
Section titled “Probe & prompt limit”3 – balanced across four active topics. A limit of 3 keeps the conversation focused without over-questioning participants. Adjust upward if you add more topics.
Topics
Section titled “Topics”| Topic | Description | Probes | Prompts |
|---|---|---|---|
| Feelings and emotion | Feelings or emotions mentioned | 1 | On |
| Prices | Experiences or things mentioned | 1 | Off |
| Customer Service | – | 1 | Off |
| Products and solutions | – | 1 | Off |
Randomise probe order and Randomise prompt order are both on.
The Feelings and emotion topic has a probe override configured:
- Feelings and emotion: What makes you feel
{{topic}}?
This pushes from the emotional reference back to a concrete cause – grounding feelings in the specific experiences that produced them.
The Prices topic also has a probe override:
- Prices: How does
{{topic}}affect how you feel about them?
Customer Service and Products and solutions use the default probe.
Prompts are enabled for Feelings and emotion only. If a participant doesn’t mention emotions spontaneously, the AI moderator will introduce the topic. The experience topics (Prices, Customer Service, Products and solutions) rely on what participants raise naturally – you may wish to enable prompts on these to get more balanced coverage across the sample.
Conversation ending
Section titled “Conversation ending”- Closing question: What one improvement, if any, would make you more likely to recommend?
- Dynamic ending: On
The closing question is future-facing and solution-oriented, which shifts the tone from retrospective to constructive. “If any” is deliberate – it gives participants an easy exit if there’s genuinely nothing they’d change, which produces more honest data than a question that presupposes an improvement exists.
Dynamic ending is on so the AI moderator wraps up in a way that reflects the individual conversation, rather than a fixed outro that might feel abrupt or mismatched in tone.
Adapting this methodology
Section titled “Adapting this methodology”When you apply this methodology to a new conversation, these are the fields you’ll typically need to change:
- Conversation introduction – replace
{brand question}with your piping syntax (e.g.@NPS,@NPS_CurrentLabel). Make sure the NPS question precedes the EVE Qual Pro question in your survey. - Context & Background – add specific context about the brand, product, or service being evaluated.
- Topics – the four default topics cover common NPS drivers. Add, remove, or rename them based on what’s relevant to your category. Add topic descriptions to help the AI moderator identify when a topic is being mentioned.
- Prompts – consider enabling prompts on the experience topics (Prices, Customer Service, Products and solutions) if you need guaranteed coverage across the sample.
- Probe & Prompt Limit – scale up proportionally if you add more topics.
The probe override on Feelings and emotion is central to the cross-dimensional structure – avoid changing it unless you’re intentionally redesigning the methodology’s logic.
Frequently asked questions
Section titled “Frequently asked questions”Why is there only one laddering question?
The goal of the laddering question here is extension, not deep associative laddering. Participants have just given an NPS score and are primed to explain it – one open question gives them space to add anything front-of-mind before the AI moderator moves into structured probing. More questions would add unnecessary length without adding insight.
Why do the emotional probe overrides cross dimensions?
The methodology is designed to capture the relationship between experiences and feelings, not just lists of each. When a participant mentions a specific experience, the probe asks how it made them feel – grounding the emotion. When they mention a feeling, the probe asks what caused it – grounding the emotion in something concrete. That connection is where the most useful NPS insight lives.
Why are prompts only enabled for Feelings and emotion?
Participants tend to raise specific experiences (prices, service, products) spontaneously when explaining an NPS score. Emotions are less reliably volunteered – prompting for them ensures the emotional dimension is always covered, even when participants focus primarily on factual experiences. You may wish to enable prompts on the experience topics too if you need more balanced coverage across the sample.
What should I use for the brand question piping syntax?
Use the variable name from your NPS question in Survey Shaper. If the variable is Q1, use @Q1 to pipe the score or @Q1_CurrentLabel to pipe the label. If you’re unsure of the variable name, check the question properties in Survey Shaper. See Placeholders and piping.
Can I use this methodology for brand-specific NPS rather than a generic likelihood-to-recommend?
Yes. Update the conversation introduction and Context & Background to reference the specific brand or product, and consider whether the default topics are specific enough for your study. For brand-specific NPS, you may want to rename or replace topics to reflect known experience drivers in your category.