Analyzing Competitor Customer Reviews In Ecommerce

Surveys are great for growth optimization. But what about the 95% who never fill them out? They're leaving reviews everywhere - Reddit, Amazon, Trustpilot. This prompt finds them ALL and shows you exactly what's blocking growth. Your best research is already written 👀 -------- Prompt: "I want you to conduct a comprehensive review mining analysis for [BRAND NAME] [BRAND URL/PRODUCT]. Please follow these steps: 1. INITIAL RESEARCH: - Use web search, Reddit search, Amazon reviews, and any available review platforms - Search for: "[brand] reviews", "[brand] complaints", "[brand] customer service", "[brand] Reddit" - Look for recent reviews (last 6-12 months) and overall patterns - Find both positive and negative feedback - Get actual customer quotes and specific examples - 2. CREATE A REVIEW MINING SUMMARY with these sections: ## What People LOVE About [Brand]: - List main positive themes with specific customer quotes - Include citations for all claims - Rank by frequency of mention - Note specific benefits users report - ## What People DON'T Like: - List main complaints with specific examples and quotes - Focus on: customer service issues, subscription problems, product quality, pricing concerns, transparency issues - Include severity and frequency of complaints - Note any business practice concerns - ## Mixed Reviews On: - Features with divided opinions and why - ## Overall Sentiment: - Star ratings across platforms - General reception summary - Key takeaways - 3. ENHANCE WITH CUSTOMER PERSONAS: - ## Customer Personas & Their Experiences Create 5-6 distinct personas based on the reviews, including: ### [Persona Name] (Age range) Quote Examples: [Real quotes representing this persona] What They LOVE: [Specific benefits valued by this persona] What They HATE: [Specific pain points for this persona] Include sections for: - Most Satisfied Customer Types - Most Dissatisfied Customer Types - Common Threads Across All Personas - IMPORTANT REQUIREMENTS: - Use exact customer quotes whenever possible - Cite all sources - Look for red flags: subscription issues, hidden fees, poor customer service, lack of transparency - Note positive patterns: specific benefits, value propositions, success stories - Include dates/recency of reviews when relevant - Provide platform sources (Reddit, Amazon, Trustpilot, etc.) - Bold key insights - Use bullet points for easy scanning - The goal is to provide a complete picture of customer sentiment that would help someone make an informed decision about this brand, understanding both what works well and what problems they might encounter."

Founder: "I can't find the right leads." Me: "What about the unhappy customers from your competitors?" Here's the exact system we built 👇 (We've seen 15-25% reply rates when messaging hits documented competitor weaknesses) G2. Capterra. Trustpilot. They're full of pain points, written by people actively looking for a better option. We've turned that into a repeatable outbound system. 1️⃣ Review Scraping Start by scraping negative reviews from 2-3 core competitors. a. n8n (starts at $20/mo): Build custom scraping workflows for G2, Capterra, and Trustpilot. We use this to power the majority of our review mining workflows. b. Apify (starts at $49/mo): Pre-built scrapers for most review platforms. 2️⃣ Pain Point Analysis Start by clustering hundreds of complaints into themes like feature gaps, support response time, UX issues, security concerns, and pricing. ↳ ChatGPT-4 ($20/mo) / Claude ($20/mo) / Perplexity ($20/mo) You now have a live database of what your prospects hate about their current tool. 3️⃣ Positioning Alignment Map those complaints to your actual value props. If their reviews mention "hidden fees" and your pricing is transparent, lean into that. ↳ Google Sheets (free) / Airtable ($20/mo) for mapping pain points to your positioning. Now you're not just pitching features. You're presenting a clear solution to a known frustration. 4️⃣ Data Enrichment & Targeting Once you know who's unhappy and why, you need to find the decision makers at companies using those competitors: ↳ Clay ($149/mo) / FullEnrich ($29/mo) The messaging angle is already validated, and the frustration warms the list. You're simply showing up with a better option. 5️⃣ Outbound Execution Once the data part is covered, the next step is to engage your leads and ensure your message delivers: a. Instantly.ai(starts at $37/mo) for unlimited email outreach b. lemlist (starts at $69/mo) for multi-channel outreach c. Expandi.io or HeyReach.io for LinkedIn-focused campaigns 6️⃣ System Automation Nothing replaces good strategy when it comes to outbound... but automation makes it scalable. We've built versions of this using n8n (for scraping) + ChatGPT (for clustering complaints) + Google Sheets (for inputs) + Clay + Instantly (for execution). The system runs on autopilot. Every week, we analyze what's working, tweak our messaging, and pull in fresh prospects. Once it's live, it becomes one of your highest-converting outbound motions. Why? Because you're focusing on real pain points and providing a better solution. Want to see this level of systematic outbound in action? Like and comment “competitors” and I will send you a training on how to send 1,000 personalized cold emails with AI ♻️

Stop guessing what customers want. Your competitors' reviews have the answers. Here's my exact process for extracting opportunities from your competitor reviews: Step 1: Gather competitor reviews automatically Use this prompt on Chat GPT Deep research: "Task: Collect up to 100 English-language customer reviews (or as many as are publicly available if fewer than 100) for [Competitor Product/Service] from the following platforms: Amazon Google Reviews Industry forums (e.g., Reddit) [Companies official website] Etc. Requirements: Include both positive and negative feedback for each platform. Only include reviews written in English. There is no restriction on date range – include reviews from any time. If fewer than 100 reviews are available on a platform, include all available. Organize the reviews into a table grouped by platform, with two columns: one for Positive Reviews and one for Negative Reviews." Why it works: → Ensures comprehensive data across multiple platforms → Captures both praise and complaints for complete picture → Structured format makes analysis easier in next steps Step 2: Extract key customer pain points Prompt: "Analyze these reviews and identify the top 5 recurring pain points. For each, include customer quotes and rate the emotional intensity on a scale of 1-10." Why it works: → Focuses on patterns, not outliers → Captures authentic customer language → Prioritizes by emotional impact Step 3: Identify unmet needs across competitors Prompt: "Create a comparison matrix showing which customer needs remain unmet by all analyzed competitors. Highlight the biggest market gaps." Why it works: → Visualizes patterns across competitors → Identifies true market gaps → Prioritizes highest-value opportunities Step 4: Validate findings with targeted research Prompt: "Based on these unmet needs, create 5 survey questions I can use to validate these findings with my own audience." Why it works: → Connects directly to identified gaps → Keeps surveys focused and completion-friendly → Validates before investing resources Step 5: Prioritize opportunities by impact and effort Prompt: "For each opportunity, help me estimate: 1) Revenue impact, 2) Development complexity, 3) Time to market, and 4) Competitive advantage duration. Then rank them." Why it works: → Balances reward against effort → Considers long-term competitive advantage → Forces clear prioritization What product would you like to enhance using this method? Share below and I'll help you craft the perfect prompts for your specific situation.