Prompt Details
Model
(claude-4-5-sonnet)
Token size
1,653
Example input
[PRODUCT_IDEA]: Shopify app that automatically categorizes customer support tickets.
[TARGET_CUSTOMER]: Small to mid-sized Shopify store owners.
[STAGE]: Idea
[KEY_UNCERTAINTY]: Whether merchants are willing to pay for automation vs. manual tagging.
Example output
# 🎯 MODE SELECTED: **A - QUICK VALIDATION ⚡**
## REASONING:
- **Market Clarity: 9/10** - Shopify app ecosystem is extremely well-established. Customer support automation is a mature category with clear use cases and proven demand.
- **Data Availability: 9/10** - Abundant data on Shopify app economics, support ticket volumes for e-commerce, and existing automation tool adoption rates.
- **Decision Urgency: High** - You're at idea stage with a specific uncertainty about willingness to pay. Fast validation will save you weeks of building the wrong thing.
**This means:** This is a well-trodden path in a clear market. You need speed over depth—validate the specific pricing question quickly, then build or move on.
**⏱️ ESTIMATED TIME:** 7 minutes
**📊 OUTPUT LENGTH:** ~550 words
---
## ⚡ QUICK VALIDATION ANALYSIS
### **DECISION: GO (with pivot on positioning)**
**Key Insight #1: The market exists and pays**
Shopify stores struggle with support volume as they scale. Apps like Gorgias ($300-$900/mo), Richpanel ($150-$500/mo), and Zendesk integrate with Shopify specifically because merchants *already pay* for support automation. Auto-tagging/categorization is a standard feature in these platforms, proving willingness to pay.
**Key Insight #2: Your pricing challenge is real but solvable**
Merchants resist paying for "features" but readily pay for *outcomes*. Auto-categorization alone isn't compelling—it's a means to an end. The merchants who pay are those who see ROI in: faster response times, reduced labor costs, or better reporting. Position around the outcome, not the feature.
**Key Insight #3: Standalone vs. platform play**
Existing solutions bundle categorization with full helpdesks. Your opportunity: Either (a) be dramatically cheaper as a micro-solution ($19-49/mo for stores not ready for Gorgias, or (b) integrate INTO existing helpdesks as a superior AI categorization layer. Standalone "just categorization" is the hardest sell.
**Key Insight #4: Market timing is favorable**
AI categorization has improved dramatically in the past 18 months. Older tools use basic keyword matching; modern LLM-based categorization is noticeably better. If your accuracy is genuinely superior, there's an upgrade cycle opportunity.
**Key Insight #5: The real competition is "doing nothing"**
Small stores (<$100k/year) often manually tag because ticket volume is low (10-50/day). Mid-sized stores ($500k-$2M) hit the pain point where manual tagging breaks but full helpdesk feels like overkill. **Your sweet spot: 50-200 tickets/day.**
---
## ⚠️ TWO BIGGEST RISKS
1. **Feature, not product:** If merchants see this as "nice to have" rather than "must have," you'll struggle with churn even if you get signups. The test: Do merchants currently pay someone/something to do this task? If they're tolerating manual work, price resistance will be high.
2. **Integration complexity vs. willingness to pay:** To be useful, you need to integrate with wherever tickets live (email, Shopify inbox, Zendesk, Gorgias, etc.). Integration dev time might exceed what a $29/mo app can justify. If you need to charge $99/mo to make economics work, you're competing directly with full platforms.
---
## 🚀 NEXT IMMEDIATE ACTION
**Customer interview sprint (this week):**
Contact 15-20 Shopify stores doing $30k-150k/month in revenue. Ask:
- "How many support tickets do you handle daily?"
- "How do you currently organize/categorize them?"
- "What happens when tickets are mis-categorized or lost?"
- "Do you currently pay for any support tools? How much?"
- **The kill question:** "If a tool auto-categorized tickets with 95% accuracy for $49/mo, would you buy it TODAY?"
If 40%+ say "yes, I'd buy today," you have validation. If they say "maybe later" or "seems useful but...," that's a no-go signal.
---
## 🎓 CONFIDENCE ASSESSMENT
**Market Understanding: High**
├─ Based on: Extensive data on Shopify app ecosystem, clear competitive landscape, established customer support automation market.
**Recommendation Confidence: High**
├─ Based on: Proven merchant willingness to pay for support automation, but your specific angle needs validation of positioning and price point.
**Key Uncertainty:** Whether merchants perceive categorization as valuable enough *in isolation* to justify a separate subscription, or whether it needs to be part of a broader workflow tool.
---
## ⚠️ PROCEED WITH CAUTION IF:
- Fewer than 30% of interview prospects express immediate buying intent
- You discover most target customers use free Shopify inbox and resist ANY paid tools
- Integration requirements push your pricing above $99/mo to maintain margins
## âś… GREEN LIGHT IF:
- 40%+ of prospects commit to "would buy today" at your target price
- You can identify 3-5 clear use cases where mis-categorization causes real pain (lost revenue, slow response times, team confusion)
- You find stores already paying for limited tools and frustrated with accuracy
---
**Questions? Let me clarify any section.**
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CLAUDE-4-5-SONNET
*Thinks harder only when your market is unclear*
This system prompt helps evaluate market ideas by adapting the depth of analysis
based on how clear or unclear the market opportunity is.
Instead of applying the same level of analysis to every idea, the prompt
assesses market clarity, available data, and decision urgency, then selects
an appropriate validation depth:
- Quick validation for obvious markets
- Standard analysis for moderately clear markets
- Deeper research for unclear or emerging
...more
Added over 1 month ago
