Company: Competitor A
- Monitor pricing: Yes (enterprise plan mostly)
- Monitor features: Yes
- Monitor messaging: Yes (especially SMB targeting)
- Monitor hiring: Yes
- Monitor content: Yes
- Monitor press: Yes
- Monitor executives: No

Company: Competitor B
[same]

You are a competitive intelligence analyst. Your job is to monitor [COMPETITOR NAMES] and extract signals that matter to our product strategy.

OUR CONTEXT:
- We compete in: [YOUR MARKET]
- Our main differentiators: [LIST 3]
- What we worry about: [e.g., "price pressure on SMB segment", "Salesforce integration becoming table stakes"]

COMPETITORS TO MONITOR:
[PASTE YOUR COMPETITOR TABLE HERE]

DATA TO INGEST:
You will receive:
1. Recent posts from competitor blogs
2. Tweets from competitor accounts
3. New features from changelogs
4. Job postings from LinkedIn/careers pages
5. Recent G2 reviews mentioning common complaints
6. Press releases and news mentions
7. LinkedIn updates from their company pages

YOUR ANALYSIS FRAMEWORK:
For each signal you detect, categorize it:

**Category:** Feature Launch | Messaging Shift | Pricing Change | Hiring Signal | Strategic Pivot | Customer Win | Market Comment | Executive Change

**Competitor:** Which competitor?

**Signal:** What changed? (1-2 sentences)

**Why It Matters:** How does this affect us? (Is it a threat? Does it validate our roadmap? Does it reveal a new segment they're targeting?)

**Our Response (if any):** What should we do about it? (Ship faster? Communicate differently? Explore new segment? Monitor more closely?)

**Confidence:** High / Medium / Low (based on how clear the signal is)

**Date:** When did this happen?

YOUR OUTPUT:
Return JSON format. Group signals by competitor. Highlight HIGH confidence signals.

{
  "competitor_name": {
    "signals": [
      {
        "category": "string",
        "signal": "string",
        "why_it_matters": "string",
        "our_response": "string or null",
        "confidence": "high|medium|low",
        "date": "YYYY-MM-DD",
        "source": "string"
      }
    ]
  },
  "summary": {
    "total_signals": number,
    "high_confidence_signals": number,
    "key_themes": ["string"],
    "threats": ["string"],
    "validations": ["string"],
    "action_items": ["string"]
  }
}

IMPORTANT RULES:
1. Only flag signals that matter to product strategy. Ignore marketing noise.
2. Don't flag every blog post. Only new product announcements and strategic themes.
3. If you see the same signal from multiple sources (e.g., feature mentioned in changelog + tweet + G2 review), flag it once with higher confidence.
4. Look for patterns. One pricing change = random move. Three pricing increases across their product = strategy.
5. Be conservative. High confidence only if the signal is clear. If you're unsure, mark as medium/low.

CONTEXT CLUES TO WATCH:
- Hiring in a segment we ignore = threat to our dominance there
- Messaging shift toward compliance = they're eyeing enterprise
- Repeated feature requests in G2 = pain point they're trying to own
- Executive hiring = strategic shift incoming
- Silent feature releases = testing something, might be significant

Return only valid JSON.

import requests
import json
import feedparser
from datetime import datetime, timedelta

# Configuration
COMPETITORS = [
    {"name": "Competitor A", "changelog_url": "...", "blog_rss": "..."},
    {"name": "Competitor B", "changelog_url": "...", "blog_rss": "..."}
]

SLACK_WEBHOOK = "https://hooks.slack.com/services/YOUR/WEBHOOK"
CLAUDE_API_KEY = "sk-..."

def fetch_competitor_data():
    """Collect data from all sources"""
    all_data = {}

    for competitor in COMPETITORS:
        data = {
            "blog_posts": [],
            "changelog": "",
            "recent_tweets": []
        }

        # Fetch blog RSS
        feed = feedparser.parse(competitor['blog_rss'])
        week_ago = datetime.now() - timedelta(days=7)

        for entry in feed.entries[:5]:
            entry_date = datetime(*entry.published_parsed[:6])
            if entry_date > week_ago:
                data['blog_posts'].append({
                    "title": entry.title,
                    "link": entry.link,
                    "date": entry.published
                })

        all_data[competitor['name']] = data

    return all_data

def analyze_with_claude(data):
    """Send to Claude for analysis"""
    client = requests.Session()
    client.headers.update({
        "Authorization": f"Bearer {CLAUDE_API_KEY}",
        "Content-Type": "application/json"
    })

    prompt = f"""[USE THE PROMPT FROM STEP 3 HERE]

DATA FROM THIS WEEK:
{json.dumps(data, indent=2)}

Analyze and return JSON."""

    response = client.post(
        "https://api.anthropic.com/v1/messages",
        json={
            "model": "claude-3-5-sonnet-20241022",
            "max_tokens": 2048,
            "messages": [{"role": "user", "content": prompt}]
        }
    )

    return response.json()['content'][0]['text']

def format_slack_message(analysis_json):
    """Convert JSON to Slack-friendly message"""
    data = json.loads(analysis_json)

    message = "📊 *Weekly Competitive Intelligence Brief*\n\n"

    for competitor, signals in data.items():
        if signals.get('signals'):
            message += f"🔍 *{competitor}*\n"
            for signal in signals['signals']:
                if signal['confidence'] == 'high':
                    message += f"🚨 {signal['category']}: {signal['signal']}\n"

    if data.get('summary'):
        message += f"\n*Key Themes:*\n"
        for theme in data['summary'].get('key_themes', []):
            message += f"• {theme}\n"

    return message

def send_to_slack(message):
    """Post to Slack"""
    requests.post(SLACK_WEBHOOK, json={"text": message})

if __name__ == "__main__":
    data = fetch_competitor_data()
    analysis = analyze_with_claude(data)
    message = format_slack_message(analysis)
    send_to_slack(message)
    print("Competitive brief sent to Slack")

0 8 * * 5 python /path/to/competitive-intel.py

{
  "Competitor A": {
    "signals": [
      {
        "category": "Feature Launch",
        "signal": "Released Slack integration for deal updates. Two-way sync.",
        "why_it_matters": "We ship Slack integration next month. They're moving faster on this surface area.",
        "our_response": "Accelerate our Slack roadmap. Consider more integrations in the announcement.",
        "confidence": "high",
        "date": "2026-03-24",
        "source": "changelog + blog post"
      },
      {
        "category": "Pricing Change",
        "signal": "Enterprise plan increased from $750 to $950/month. Added 'dedicated support' tier.",
        "why_it_matters": "Signals confidence in enterprise segment. Testing price elasticity. We have room to follow.",
        "our_response": "Monitor our enterprise churn closely. Consider similar tiering in next review.",
        "confidence": "high",
        "date": "2026-03-22",
        "source": "pricing page + Twitter post"
      }
    ]
  },
  "Competitor B": {
    "signals": [
      {
        "category": "Hiring Signal",
        "signal": "Posted 7 open roles: 4 in Sales (Enterprise focus), 2 in Product, 1 Data Scientist",
        "why_it_matters": "Aggressive hiring in enterprise sales. They're scaling up to chase upmarket. Real signal of growth and confidence.",
        "our_response": "Monitor if they're hiring away from us. Be ready to counter-hire if needed.",
        "confidence": "high",
        "date": "2026-03-23",
        "source": "LinkedIn jobs + their careers page"
      },
      {
        "category": "Messaging Shift",
        "signal": "Three recent blog posts focused on compliance and security certifications (SOC 2, ISO 27001). Previously focused on ease-of-use.",
        "why_it_matters": "They're pivoting messaging toward enterprise/regulated industries. New segment play.",
        "our_response": "Assess if we should emphasize our own compliance story. Could be table stakes soon.",
        "confidence": "medium",
        "date": "2026-03-20 onwards",
        "source": "blog"
      }
    ]
  },
  "summary": {
    "total_signals": 3,
    "high_confidence_signals": 2,
    "key_themes": ["Enterprise focus from both competitors", "Product feature parity pressure on integrations", "Messaging shift toward compliance"],
    "threats": ["Competitor A Slack integration shipping before us", "Competitor B enterprise hiring surge"],
    "validations": ["Our Q2 enterprise roadmap validated by competitor signals", "Slack integration demand confirmed by multiple sources"],
    "action_items": ["Accelerate Slack feature", "Monitor enterprise churn closely", "Prepare messaging about compliance posture"]
  }
}