Write an NPS follow-up survey question set
intermediateClaude SonnetCustomer ServiceCx Researchnpssurveycx-researchcustomer-feedback
Use case
Use this prompt to build the follow-up questions that appear after customers submit an NPS score. The NPS number alone tells you little — the follow-up questions are where the insight lives. This prompt generates questions tailored to score range (promoter, passive, detractor) that surface root causes and next actions.
The prompt
You are a customer experience researcher. Write a targeted NPS follow-up survey question set. Context: - Product/service:{{product_name}}- Customer segment:{{customer_segment}}(e.g., all customers, enterprise only, first 90 days, post-onboarding) - Key things you want to understand:{{research_priorities}}(e.g., what drives loyalty, what causes dissatisfaction, which features are most valued) - Survey platform:{{platform}}(e.g., Delighted, SurveyMonkey, Typeform, in-app) - Max questions per survey:{{max_questions}}Write three separate follow-up question sets — one for each score group: **Detractors (0–6): [Title your question set]** Goal: understand the source of dissatisfaction and open the door to recovery. Questions should: - Acknowledge the low score respectfully without being defensive - Ask specifically what led to the low rating - Ask whether they've tried to get help and what the experience was - Ask what would need to change for them to reconsider Max{{max_questions}}questions. **Passives (7–8): [Title your question set]** Goal: understand what's preventing them from being promoters, and what would tip them over. Questions should: - Acknowledge that things are okay but not great - Probe what's missing or could be improved - Identify which features or aspects are most/least valuable Max{{max_questions}}questions. **Promoters (9–10): [Title your question set]** Goal: understand what's driving loyalty and capture testimonial-quality insight. Questions should: - Thank them for their rating and ask what they love - Identify the specific moment when they became a strong advocate - Ask what they'd say to someone else considering the product - Gauge willingness to be a reference, case study, or G2 reviewer Max{{max_questions}}questions. For each question: - Write the question text as it would appear to the customer - Label the question type: open text, multiple choice, rating scale, or yes/no - Note the insight it's designed to surface (internal guidance) Also write: a brief analysis guide — how to use the survey results to prioritize actions.
Variables
{{{{product_name}}}}Replace with your {{product name}}{{{{customer_segment}}}}Replace with your {{customer segment}}{{{{research_priorities}}}}Replace with your {{research priorities}}{{{{platform}}}}Replace with your {{platform}}{{{{max_questions}}}}Replace with your {{max questions}}
Example
Input
product_name: Anchor Analytics customer_segment: all paying customers, surveyed 90 days after first login research_priorities: understand which features drive loyalty, what caused dissatisfaction, what prevents passives from becoming promoters platform: Delighted max_questions: 4
Output
**Detractors (0–6): Help Us Do Better** 1. "What's the main reason for your rating?" (Open text) Insight: Identifies the primary source of dissatisfaction — categorize responses into: product (bugs/missing features), support (unresolved issues), value (price vs. perceived value), onboarding (never got set up properly) 2. "Which part of Anchor hasn't worked the way you expected?" (Multiple choice: Connecting data sources / Dashboard setup / Anomaly alerts / Exports / Something else) Insight: Pinpoints the specific failure area for product and CS teams 3. "Have you reached out to our support team about this?" (Yes/No — if yes, follow with) "How was that experience?" Insight: Surfaces unresolved support issues; also identifies detractors who didn't seek help (missed intervention opportunity) 4. "What would need to change for you to give us a higher score?" (Open text) Insight: Direct recovery roadmap from the customer's perspective; often surfaces actionable, specific requests --- **Passives (7–8): Help Us Improve** 1. "What's been the most valuable part of using Anchor so far?" (Open text) Insight: Identifies what IS working for passives — often reveals that they haven't discovered the features that drive promoter satisfaction 2. "What would make you more likely to recommend Anchor to a colleague?" (Open text) Insight: The most direct answer to the promoter gap — often reveals missing features, price sensitivity, or onboarding gaps 3. "Which of these would make Anchor more valuable to you?" (Multiple choice: Faster setup / More integrations / Better reporting / More customization / Lower price / Better support) Insight: Quantifies the most common improvement priorities among passives 4. "How often does your team use Anchor for weekly reporting?" (Multiple choice: Daily / Weekly / Monthly / Rarely) Insight: Usage frequency is often the strongest passive-to-promoter predictor — low usage passives need engagement campaigns, not feature development --- **Promoters (9–10): Share Your Story** 1. "What made you give us a 9 or 10?" (Open text) Insight: Testimonial-quality language; identify which features, moments, or outcomes drive promoter status 2. "Was there a specific moment when you realized Anchor was really working for your team?" (Open text) Insight: The "aha moment" — feeds product onboarding optimization and marketing stories 3. "If a colleague was considering Anchor, what would you tell them?" (Open text) Insight: Word-of-mouth language; use verbatim in marketing materials (with permission) 4. "Would you be open to sharing your experience more broadly — as a G2 review, a case study, or a reference call?" (Multiple choice: Happy to do a G2 review / Open to a case study / Would do a reference call / Not interested right now) Insight: Populates your advocate pipeline without a separate ask --- Analysis Guide: - Detractor open text: run monthly and tag responses into 5–6 categories; top category = highest priority fix - Passive gap question: treat as a product wishlist; top answer each quarter = roadmap input - Promoter "aha moment": feed directly into onboarding design — if promoters cite a specific feature, make it impossible to miss in the first 30 days - Advocate pipeline: export promoters who said yes to G2/case study into a dedicated workflow the CS team owns
Tips for best results
- 1Send NPS surveys at consistent moments in the customer lifecycle (90 days, 12 months, post-support resolution) — not randomly. Triggered surveys produce higher response rates and more comparable data.
- 24 questions is the right maximum for post-NPS surveys. Response rate drops sharply after 4 questions — you'll lose respondents and the data quality will drop.
- 3Never send an NPS survey without following up on detractor responses. An NPS program that doesn't respond to detractors is data collection theater.
- 4The promoter 'aha moment' question is gold for product and marketing. Build a repository of these answers — they're better marketing copy than anything your team will write.
- 5Benchmark your NPS quarterly, not monthly. Monthly variance is noise; quarterly trends are signal.
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