modbender Hidden Business Opportunity Detector Skill
Overview
This skill builds an automated business intelligence engine that:
- Apify scrapes App Store reviews, Amazon reviews, Reddit, niche forums, and Product Hunt
- Claude (OpenClaw) deep-analyzes the raw frustrations, recurring requests, and unmet needs
- Produces a structured market gap report with validated SaaS ideas, scored by opportunity size
This is how the best indie hackers and founders find their next product — systematically.
🔗 Apify: https://www.apify.com/?fpr=dx06p
What This Skill Does
- Scrape App Store & Google Play reviews to find what users hate about existing apps
- Scrape Amazon reviews (1–2 stars) to extract product frustrations at scale
- Mine Reddit niche communities for recurring complaints and feature requests
- Crawl niche forums and communities for unmet needs
- Scrape Product Hunt for emerging tools and gaps in the market
- Feed all raw data into Claude for structured opportunity analysis
- Output a ranked list of business opportunities with validation signals
- Generate SaaS idea briefs with positioning, features, and GTM angle
Architecture Overview
┌─────────────────────────────────────────────────────────────────┐
│ HIDDEN BUSINESS OPPORTUNITY DETECTOR │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ LAYER 1 — DATA MINING (Apify) │ │
│ │ App Store │ Google Play │ Amazon │ Reddit │ Forums │ │
│ │ Product Hunt │ G2 │ Trustpilot │ Indie Hackers │ │
│ └──────────────────────────┬──────────────────────────────┘ │
│ │ │
│ ┌──────────────────────────▼──────────────────────────────┐ │
│ │ LAYER 2 — OPPORTUNITY ANALYSIS ENGINE (Claude) │ │
│ │ │ │
│ │ • Frustration Extractor → what people hate/struggle │ │
│ │ • Pattern Detector → recurring complaints │ │
│ │ • Gap Analyzer → what nobody is building │ │
│ │ • Opportunity Scorer → market size x pain level │ │
│ │ • SaaS Idea Generator → concrete product briefs │ │
│ └──────────────────────────┬──────────────────────────────┘ │
│ │ │
│ ┌──────────────────────────▼──────────────────────────────┐ │
│ │ LAYER 3 — OPPORTUNITY REPORT │ │
│ │ Ranked ideas │ Validation signals │ GTM angles │ │
│ │ JSON export │ Markdown report │ Notion / Slack push │ │
│ └─────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
Step 1 — Get Your API Keys
Apify
- Sign up at https://www.apify.com/?fpr=dx06p
- Go to Settings → Integrations
- Copy your token:
export APIFY_TOKEN=apify_api_xxxxxxxxxxxxxxxx
Claude / OpenClaw
export CLAUDE_API_KEY=sk-ant-xxxxxxxxxxxxxxxx
Step 2 — Install Dependencies
npm install apify-client axios node-cron dotenv fs-extra
Layer 1 — Multi-Source Data Miner (Apify)
Mine App Store & Google Play Reviews
import ApifyClient from 'apify-client';
const apify = new ApifyClient({ token: process.env.APIFY_TOKEN });
// Define the niche and competitor apps to analyze
const TARGET_NICHE = "project management";
const COMPETITOR_APPS = [
{ name: "Notion", appStoreId: "1232780281", playStoreId: "notion.id" },
{ name: "Asana", appStoreId: "489969512", playStoreId: "com.asana.app" },
{ name: "Trello", appStoreId: "461504587", playStoreId: "com.trello" },
{ name: "Monday", appStoreId: "1298450011", playStoreId: "com.monday.monday" }
];
async function scrapeAppReviews() {
console.log("📱 Scraping App Store & Play Store reviews...");
const jobs = COMPETITOR_APPS.map(app =>
Promise.all([
// App Store — focus on 1-3 star reviews (the gold mine)
apify.actor("apify/apple-app-store-scraper").call({
appIds: [app.appStoreId],
maxReviews: 100,
filterStars: [1, 2, 3]
}).then(run => run.dataset().getData())
.then(d => d.items.map(r => ({
source: "app_store",
appName: app.name,
rating: r.rating,
review: r.review,
title: r.title,
date: r.date,
country: r.country
}))),
// Google Play Store
apify.actor("apify/google-play-scraper").call({
appId: app.playStoreId,
maxReviews: 100,
filterScore: [1, 2, 3]
}).then(run => run.dataset().getData())
.then(d => d.items.map(r => ({
source: "google_play",
appName: app.name,
rating: r.score,
review: r.text,
title: r.title || "",
date: r.date,
thumbsUp: r.thumbsUp
})))
]).then(results => results.flat())
);
const allReviews = await Promise.all(jobs);
return allReviews.flat();
}
Mine Amazon Reviews (1-3 Stars)
async function scrapeAmazonReviews() {
console.log("📦 Scraping Amazon negative reviews...");
// Target products in your niche
const TARGET_PRODUCTS = [
"https://www.amazon.com/dp/B08N5WRWNW", // productivity tool example
"https://www.amazon.com/dp/B09G9HD6PD"
];
const jobs = TARGET_PRODUCTS.map(url =>
apify.actor("apify/amazon-reviews-scraper").call({
startUrls: [{ url }],
maxReviews: 100,
filterByStar: ["one_star", "two_star", "three_star"]
}).then(run => run.dataset().getData())
.then(d => d.items.map(r => ({
source: "amazon",
productTitle: r.productTitle,
rating: r.ratingScore,
review: r.reviewText,
title: r.reviewTitle,
date: r.date,
helpfulVotes: r.helpfulVotes,
verifiedPurchase: r.verifiedPurchase
})))
);
const results = await Promise.all(jobs);
return results.flat();
}
Mine Reddit Niche Communities
async function scrapeRedditFrustrations() {
console.log("💬 Scraping Reddit communities...");
const SUBREDDITS = [
"r/Entrepreneur",
"r/SaaS",
"r/smallbusiness",
"r/productivity",
"r/projectmanagement",
"r/startups",
"r/indiehackers"
];
const [posts, searchResults] = await Promise.all([
// Hot/top posts in subreddits
apify.actor("apify/reddit-scraper").call({
startUrls: SUBREDDITS.map(s => ({ url: `https://www.reddit.com/${s}/` })),
maxPostCount: 30,
maxComments: 15,
sort: "top"
}).then(run => run.dataset().getData()),
// Search for frustration signals
apify.actor("apify/reddit-search-scraper").call({
queries: [
`${TARGET_NICHE} frustrated wish`,
`${TARGET_NICHE} hate problem broken`,
`${TARGET_NICHE} alternative looking for better`,
`${TARGET_NICHE} feature request need`,
`${TARGET_NICHE} why is there no tool`
],
maxItems: 50
}).then(run => run.dataset().getData())
]);
return [
...posts.items.map(p => ({
source: "reddit_post",
subreddit: p.subreddit,
title: p.title,
text: p.selftext,
score: p.score,
comments: p.numComments,
url: p.url
})),
...searchResults.items.map(p => ({
source: "reddit_search",
subreddit: p.subreddit,
title: p.title,
text: p.selftext,
score: p.score,
url: p.url
}))
];
}
Mine Product Hunt & G2 Reviews
async function scrapeProductIntelligence() {
console.log("🚀 Scraping Product Hunt & review platforms...");
const [productHunt, g2] = await Promise.all([
// Product Hunt — see what's launching and what comments say
apify.actor("apify/product-hunt-scraper").call({
mode: "search",
searchQuery: TARGET_NICHE,
maxItems: 30
}).then(run => run.dataset().getData())
.then(d => d.items.map(p => ({
source: "product_hunt",
name: p.name,
tagline: p.tagline,
description: p.description,
upvotes: p.votesCount,
comments: p.commentsCount,
topics: p.topics,
url: p.url
}))),
// G2 reviews for competitor software
apify.actor("apify/website-content-crawler").call({
startUrls: [
{ url: `https://www.g2.com/categories/${TARGET_NICHE.replace(/\s+/g, '-')}-software` }
],
maxCrawlingDepth: 1,
maxRequestsPerCrawl: 10
}).then(run => run.dataset().getData())
.then(d => d.items.map(p => ({
source: "g2",
text: p.text?.slice(0, 2000),
url: p.url
})))
]);
return [...productHunt, ...g2];
}
Layer 2 — Opportunity Analysis Engine (Claude)
Frustration Extractor
import axios from 'axios';
const claude = axios.create({
baseURL: 'https://api.anthropic.com/v1',
headers: {
'x-api-key': process.env.CLAUDE_API_KEY,
'anthropic-version': '2023-06-01',
'Content-Type': 'application/json'
}
});
async function extractFrustrations(allData) {
const prompt = `
You are a world-class product researcher and market analyst.
Analyze this raw data from app reviews, Amazon reviews, Reddit posts, and product listings.
Extract every customer frustration, unmet need, and recurring complaint.
NICHE: ${TARGET_NICHE}
RAW DATA (sample):
${JSON.stringify(allData.slice(0, 30), null, 2)}
Respond ONLY in this JSON format:
{
"frustrations": [
{
"theme": "short label",
"description": "what users are frustrated about",
"frequency": "how often this comes up (high/medium/low)",
"emotionalIntensity": "how angry/upset users are (1-10)",
"affectedSegment": "who experiences this most",
"evidenceQuotes": ["direct quote 1", "direct quote 2"],
"sources": ["app_store", "reddit"]
}
],
"featureRequests": [
{
"request": "what users are explicitly asking for",
"frequency": "high | medium | low",
"currentWorkaround": "what users do today instead",
"evidenceQuotes": ["quote"]
}
],
"recurringPatterns": [
"pattern 1 observed across multiple sources",
"pattern 2"
],
"underservedSegments": [
{
"segment": "who is being ignored",
"unmetNeed": "what they need",
"currentSolution": "what they use today despite it being bad"
}
]
}
`;
const { data } = await claude.post('/messages', {
model: "claude-opus-4-5",
max_tokens: 3000,
messages: [{ role: "user", content: prompt }]
});
return JSON.parse(data.content[0].text.replace(/```json|```/g, '').trim());
}
Market Gap Analyzer & SaaS Idea Generator
async function analyzeMarketGaps(frustrations, productIntel) {
const prompt = `
You are a serial entrepreneur and SaaS product strategist.
Based on these validated customer frustrations and market intelligence, identify
the highest-potential business opportunities and generate concrete SaaS ideas.
FRUSTRATIONS & PATTERNS:
${JSON.stringify(frustrations, null, 2)}
MARKET INTELLIGENCE (existing products):
${JSON.stringify(productIntel.slice(0, 10), null, 2)}
Respond ONLY in this JSON format:
{
"marketGaps": [
{
"gap": "what is clearly missing from the market",
"evidenceStrength": "strong | moderate | weak",
"estimatedMarketSize": "niche | small | medium | large",
"competitionLevel": "none | low | medium | high",
"urgency": "nice-to-have | important | critical"
}
],
"saasIdeas": [
{
"rank": 1,
"name": "working product name",
"oneLiner": "X for Y — one sentence pitch",
"problem": "exact problem it solves",
"targetCustomer": "specific ICP (ideal customer profile)",
"coreFeatures": ["feature 1", "feature 2", "feature 3"],
"differentiator": "why this beats existing solutions",
"monetization": "pricing model (per seat | usage | freemium | etc)",
"estimatedMRR": "rough MRR potential at 100 customers",
"validationSignals": ["signal from data that confirms the need"],
"gtmAngle": "how to acquire first 100 customers",
"buildComplexity": "low | medium | high",
"opportunityScore": 8,
"risksAndChallenges": ["risk 1", "risk 2"]
}
],
"quickWins": [
{
"idea": "simplest possible version of a solution",
"timeToMVP": "estimated days/weeks to build",
"validationMethod": "how to validate before building"
}
],
"topRecommendation": "single best opportunity with 1-paragraph reasoning"
}
`;
const { data } = await claude.post('/messages', {
model: "claude-opus-4-5",
max_tokens: 4000,
messages: [{ role: "user", content: prompt }]
});
return JSON.parse(data.content[0].text.replace(/```json|```/g, '').trim());
}
Validation Signal Scorer
async function scoreOpportunities(ideas, rawData) {
const prompt = `
Score each SaaS idea based on the evidence in the raw data.
Apply the Rob Walling (TinySeed) and Paul Graham opportunity frameworks.
IDEAS TO SCORE:
${JSON.stringify(ideas.saasIdeas, null, 2)}
RAW DATA SIGNALS:
- Total reviews analyzed: ${rawData.length}
- Sources: ${[...new Set(rawData.map(r => r.source))].join(', ')}
- Top frustration themes: ${JSON.stringify(ideas.marketGaps?.slice(0, 5))}
Respond ONLY in this JSON format:
{
"scoredIdeas": [
{
"rank": 1,
"name": "product name",
"scores": {
"painLevel": { "score": 9, "reasoning": "why" },
"marketSize": { "score": 7, "reasoning": "why" },
"competition": { "score": 8, "reasoning": "why" },
"buildability": { "score": 6, "reasoning": "why" },
"monetization": { "score": 8, "reasoning": "why" },
"founderFit": { "score": 7, "reasoning": "why" }
},
"overallScore": 7.5,
"verdict": "🔥 Build this | ✅ Worth exploring | ⚠️ Risky | ❌ Skip",
"nextStep": "concrete first action to validate this idea"
}
],
"winnerIdea": "name of the single best opportunity",
"executiveSummary": "2-3 sentence summary of the full analysis"
}
`;
const { data } = await claude.post('/messages', {
model: "claude-opus-4-5",
max_tokens: 2500,
messages: [{ role: "user", content: prompt }]
});
return JSON.parse(data.content[0].text.replace(/```json|```/g, '').trim());
}
Layer 3 — Opportunity Report Generator
import { writeFileSync } from 'fs';
function generateMarkdownReport(frustrations, gaps, scored, rawDataCount) {
const top = scored.scoredIdeas.slice(0, 3);
const date = new Date().toLocaleDateString('en-US', { year: 'numeric', month: 'long', day: 'numeric' });
return `# 🎯 Business Opportunity Report
**Niche:** ${TARGET_NICHE} | **Date:** ${date} | **Data Points Analyzed:** ${rawDataCount}
---
## Executive Summary
${scored.executiveSummary}
**🏆 Winner Idea: ${scored.winnerIdea}**
---
## Top Market Gaps Identified
${gaps.marketGaps?.slice(0, 5).map((g, i) =>
`### ${i + 1}. ${g.gap}
- **Evidence:** ${g.evidenceStrength} | **Market:** ${g.estimatedMarketSize} | **Competition:** ${g.competitionLevel}
- **Urgency:** ${g.urgency}`
).join('\n\n')}
---
## Top 3 SaaS Opportunities
${top.map(idea => `### ${idea.rank}. ${idea.name} — Score: ${idea.overallScore}/10 ${idea.verdict}
${gaps.saasIdeas?.find(i => i.name === idea.name)?.oneLiner || ""}
| Dimension | Score | Notes |
|---|---|---|
| Pain Level | ${idea.scores.painLevel.score}/10 | ${idea.scores.painLevel.reasoning} |
| Market Size | ${idea.scores.marketSize.score}/10 | ${idea.scores.marketSize.reasoning} |
| Competition | ${idea.scores.competition.score}/10 | ${idea.scores.competition.reasoning} |
| Buildability | ${idea.scores.buildability.score}/10 | ${idea.scores.buildability.reasoning} |
| Monetization | ${idea.scores.monetization.score}/10 | ${idea.scores.monetization.reasoning} |
**Next Step:** ${idea.nextStep}`
).join('\n\n---\n\n')}
---
## Top Customer Frustrations
${frustrations.frustrations?.slice(0, 8).map((f, i) =>
`**${i + 1}. ${f.theme}** (Intensity: ${f.emotionalIntensity}/10 | Frequency: ${f.frequency})
> "${f.evidenceQuotes?.[0] || 'No quote available'}"
${f.description}`
).join('\n\n')}
---
## Quick Wins (Ship in Days)
${gaps.quickWins?.map(q =>
`- **${q.idea}** | Time to MVP: ${q.timeToMVP} | Validate by: ${q.validationMethod}`
).join('\n')}
---
*Generated by Hidden Business Opportunity Detector • Powered by Apify + Claude*
`;
}
Master Orchestrator — Full Pipeline
async function runOpportunityDetector(niche = TARGET_NICHE) {
console.log(`\n🎯 Opportunity Detector started — ${niche}`);
console.log(`Timestamp: ${new Date().toISOString()}\n`);
try {
// STEP 1 — Mine all data sources in parallel
console.log("[1/5] Mining data sources...");
const [appReviews, amazonReviews, redditData, productIntel] = await Promise.all([
scrapeAppReviews(),
scrapeAmazonReviews(),
scrapeRedditFrustrations(),
scrapeProductIntelligence()
]);
const allData = [...appReviews, ...amazonReviews, ...redditData, ...productIntel];
console.log(` ✅ ${allData.length} data points collected`);
console.log(` App reviews: ${appReviews.length} | Amazon: ${amazonReviews.length}`);
console.log(` Reddit: ${redditData.length} | Product intel: ${productIntel.length}`);
// STEP 2 — Extract frustrations
console.log("\n[2/5] Extracting frustrations with Claude...");
const frustrations = await extractFrustrations(allData);
console.log(` ✅ ${frustrations.frustrations?.length} frustration themes identified`);
console.log(` ✅ ${frustrations.featureRequests?.length} feature requests found`);
// STEP 3 — Analyze market gaps and generate SaaS ideas
console.log("\n[3/5] Analyzing market gaps...");
const gaps = await analyzeMarketGaps(frustrations, productIntel);
console.log(` ✅ ${gaps.marketGaps?.length} gaps identified`);
console.log(` ✅ ${gaps.saasIdeas?.length} SaaS ideas generated`);
// STEP 4 — Score all opportunities
console.log("\n[4/5] Scoring opportunities...");
const scored = await scoreOpportunities(gaps, allData);
console.log(` ✅ Ideas scored | Winner: ${scored.winnerIdea}`);
// STEP 5 — Generate report
console.log("\n[5/5] Generating report...");
const report = generateMarkdownReport(frustrations, gaps, scored, allData.length);
writeFileSync(`./opportunity-report-${Date.now()}.md`, report);
const outputJSON = {
niche,
analyzedAt: new Date().toISOString(),
dataPoints: allData.length,
frustrationThemes: frustrations.frustrations?.length,
marketGaps: gaps.marketGaps,
saasIdeas: scored.scoredIdeas,
winnerIdea: scored.winnerIdea,
quickWins: gaps.quickWins,
executiveSummary: scored.executiveSummary
};
writeFileSync(`./opportunity-data-${Date.now()}.json`, JSON.stringify(outputJSON, null, 2));
console.log("\n✅ Reports saved to disk");
// Optional: push to Slack
if (process.env.SLACK_WEBHOOK_URL) {
await axios.post(process.env.SLACK_WEBHOOK_URL, {
text: `🎯 *Opportunity Report Ready — ${niche}*\n` +
`📊 ${allData.length} data points analyzed\n` +
`🏆 Top idea: *${scored.winnerIdea}*\n` +
`💬 ${scored.executiveSummary}`
});
}
return outputJSON;
} catch (err) {
console.error("Pipeline error:", err.message);
throw err;
}
}
// Run immediately
runOpportunityDetector("project management tools");
Environment Variables
# .env
APIFY_TOKEN=apify_api_xxxxxxxxxxxxxxxx
CLAUDE_API_KEY=sk-ant-xxxxxxxxxxxxxxxx
# Optional notifications
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/xxx/xxx/xxx
NOTION_API_KEY=secret_xxxxxxxxxxxxxxxx
Normalized Opportunity Output Schema
{
"niche": "project management",
"analyzedAt": "2025-02-25T10:00:00Z",
"dataPoints": 380,
"winnerIdea": "AutoStandup",
"saasIdeas": [
{
"rank": 1,
"name": "AutoStandup",
"oneLiner": "Async standups that actually get filled out",
"overallScore": 8.5,
"verdict": "🔥 Build this",
"targetCustomer": "Remote engineering teams 5-50 people",
"estimatedMRR": "$12,000 at 100 customers ($120/mo per team)",
"timeToMVP": "3 weeks",
"nextStep": "Post in r/remotework and r/SaaS — ask if this is a real problem",
"validationSignals": [
"47 Reddit posts complaining about standups being ignored",
"3-star Slack reviews: 'nobody fills them out'"
]
}
],
"quickWins": [
{
"idea": "Notion template for async standups",
"timeToMVP": "2 days",
"validationMethod": "Post on Gumroad, see if anyone pays $9"
}
]
}
Best Practices
- Focus on 1–3 star reviews — that's where the real pain lives
- Scrape at least 200+ reviews per competitor for statistically significant patterns
- Always include a "why is there no tool for X" Reddit search — goldmine for gaps
- Cross-validate: an idea is strong only if the same frustration appears in 3+ sources
- The Quick Wins section is perfect for validation before building — ship a landing page first
- Re-run the pipeline on a new niche weekly to build a pipeline of ideas
- Track which ideas get the most Slack/Notion engagement from your team
Error Handling
try {
const data = await scrapeAppReviews();
return data;
} catch (error) {
if (error.statusCode === 401) throw new Error("Invalid Apify token");
if (error.statusCode === 429) throw new Error("Rate limit — reduce concurrent scrapers");
if (error.message.includes("actor")) throw new Error("Actor not found — verify actor ID");
throw error;
}
Requirements
- Apify account → https://www.apify.com/?fpr=dx06p
- Claude / OpenClaw API key
- Node.js 18+ with
apify-client,axios,node-cron,fs-extra - Optional: Slack, Notion, or Airtable for team collaboration on the output