Operations & Content
Customer Feedback Synthesis#customer feedback#synthesis#NPSCustomer Feedback Synthesis · 50 Reviews → 3 Real Problems
Synthesize 50 raw items (tickets, NPS, interviews, community) into 3 problems worth solving, priority, and 1 to NOT solve.
Pain addressed · Ops sees feedback daily but can't tell which ones matter. Single comments = noise. Synthesis = signal. Without a tool you default to 'go with your gut.'
Customer Feedback Synthesis · 50 Reviews → 3 Real Problems
You're my customer feedback synthesis partner. I'm an ops lead. Help me compress 50 raw items into an actionable brief.
# My raw feedback (mix of tickets / NPS / interviews / community)
{paste_raw_feedback}
Tag each: [source][user type][summary][intensity 1-5]. Order doesn't matter. ~50 items is the sweet spot.
# Product + current roadmap priorities
{product_and_roadmap_context}
# Output four sections
## 1. Theme clusters (3-5 themes, 60 words each)
- Theme name (verb-led: "reduce onboarding friction", not "onboarding issues")
- Count of feedback in theme + user type distribution
- Average intensity (1-5)
- One representative direct quote in the user's actual language
## 2. 3 problems worth solving (80 words each)
Pick the top 3 from the themes. Ordered:
- Problem statement (in user voice)
- Why it's worth solving (frequency × intensity × roadmap fit)
- Suggested first step (MVP / setting / comms)
- Expected ROI (user-felt + business metric)
## 3. 1 problem explicitly NOT to solve (50 words)
- High-frequency but not worth it (outlier / out of scope / niche user)
- Why we won't + how to reply to users (protect experience)
## 4. Signal vs noise (60 words)
- What's real signal (multiple users, multiple channels) vs single-source noise.
- One sentence: based on these 50 items, what did we learn or unlearn about our users?
# Boundaries
- "Users want more features" isn't a problem; it's a description.
- Quote users in quotes; never paraphrase into corporate voice.
- The "not to solve" item must be real — ops's hardest job is saying no.Open directly on your favourite AI
One click copies the prompt and opens the platform in a new tab — just paste (⌘/Ctrl + V). Recommended platforms are ordered by content fit.
Workflow · 5 steps
- 1
Pull the last 4 weeks of 50 raw items from your tickets, NPS, and community. Don't pre-edit; the model needs the noise to find signal.
- 2
Run in Claude (best at synthesis) or ChatGPT. Fill the 2 placeholders.
- 3
Audit the theme clusters yourself. Bad theme names cascade into wrong actions downstream.
- 4
The 'not to solve' section is the one the model most often skips. If it's missing, push back: 'name one high-frequency item we should explicitly NOT do'.
- 5
Send the 3 problems to product + engineering leads; send the 'not to solve' to your support lead (they need it most for user replies).
Verify before you ship
AI's "almost right" is the #1 pain. Tick these off so reviewers can't find the obvious holes. (Checkbox state stays local — we don't track it.)
Why this prompt works
This prompt isn't a generic “write me a Customer Feedback Synthesis”. It folds in the concrete context a Operations & Content actually faces (target reader, info density, deliverable format). LLMs deliver an order-of-magnitude better answer when they get role × scenario × constraints together — they can make the right tradeoffs about what to spotlight and what to cut.
When to use
Best moment: you know roughly that you need to do a Customer Feedback Synthesis, but you're stuck on “how do I even ask the AI?” Muscle memory has no template. Copy this card, tweak 2-3 fields per the workflow, and get a first revisable draft in 30 seconds.
Common pitfalls
- Send without tweaking placeholders · the draft reads as default-GPT and your reviewer spots it in 3 seconds.
- Skip the verify checklist · “almost right” failures usually hide in a thing you assumed the model handled but it didn't.
- Stop after the first answer · a single follow-up like “make section X tighter / more formal” usually pushes a 70 → 90.
Variants & extensions
Want to use this card more aggressively? Three extensions:
- Swap languages: both EN/ZH prompts ship in the card — use the EN version when shipping to a Western audience.
- Swap platforms: the same prompt has slightly different taste on ChatGPT / Claude / Kimi. The recommended-platform pill marks the best fit.
- Stack the checklist: paste the verify checklist back into the chat and ask the AI to self-audit — error rate drops sharply.
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