What is ADINT? How to Collect and Analyze Ad Intelligence Data for OSINT

By H9 | Published on July 6, 2025
Category: Digital Marketing, OSINT
Ad Intelligence Image

Ad intelligence — the practice of collecting and analyzing information about competitors' digital advertising — has become a cornerstone of modern marketing strategy. Businesses of all sizes, from startups to enterprises, rely on it to benchmark performance, understand trends, identify opportunities, and refine their campaigns.

In this guide, we will explore what ad intelligence is, why it matters, and how to collect and analyze ad intelligence data from social platforms and websites — accurately and ethically.

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🌐 What is Ad Intelligence?

Ad intelligence is the collection and analysis of publicly available advertising data to uncover insights into your competitors' digital marketing strategies. It involves examining:

This insight is valuable for competitive analysis, campaign optimization, audience targeting, and market entry strategies.

💡 Why Is Ad Intelligence Important?

Benefit Description
Competitive Analysis See what your rivals are doing and adapt quickly.
Trend Forecasting Spot emerging advertising trends in your niche.
Creative Inspiration Discover high-performing ad formats and messaging.
Budget Benchmarking Estimate how much competitors are spending.
Market Entry Planning Learn what works in new geographies or industries.

🔍 Platforms to Collect Ad Intelligence From

1. Social Media Platforms

2. Websites & Display Ads

🧰 Tools for Ad Intelligence Collection

A. No-Code Tools (UI-based)

Tool Platform Coverage Use Case
Meta Ad Library Facebook, Instagram View all active ads by any page
TikTok Ads Library TikTok See top ads by country & industry
Moat Web, Display, Video Track creatives & impressions
SEMrush Display Advertising Web Competitor banner ads
SimilarWeb Web Traffic sources and ad networks
AdSpy FB, IG Massive searchable ad database
BigSpy All Good for dropshipping & affiliate ads

B. Technical/Custom Collection (for developers)

Tool Tech Stack Use Case
Python + Selenium/Scrapy Web scraping Automate competitor website monitoring
Facebook Graph API Facebook Fetch ad accounts, page ads (with permission)
Twitter API v2 Twitter/X Ad campaign data (limited)
Google Ads Transparency Center API Google Ads Programmatic ad insights
BuiltWith/Wappalyzer Web See what adtech competitors use
Wayback Machine API Web Archive See older ad campaigns or site versions

⚠️ Important Note: Always adhere to platform terms of service. Unauthorized scraping or data extraction from certain platforms may be illegal or violate TOS.

🎯 Why Use Ad Intelligence in OSINT Investigations?

Ad data can expose:

AdINT is vital in:

🖥️ Website Ad Tracking Tools

�Satellite Ad Infrastructure and Surveillance Mapping

🧰 Step-by-Step OSINT Process for Ad Intelligence

✅ Step 1: Define Intelligence Objectives

Clearly state:

✅ Step 2: Identify and Collect Ad Artifacts

From Social Platforms:

From Websites:

✅ Step 3: Link Digital Ad Infrastructure

Connect ads to broader infrastructure using:

This helps you map digital ecosystems and potentially unmask coordinated campaigns.

✅ Step 4: Analyze Content and Messaging

Use NLP and visual recognition:

Useful Tools:

✅ Step 5: Analyze Targeting and Audience

Understand WHO is being targeted:

Key goal: Detect manipulation, marginalization, or over-targeting of specific groups.

✅ Step 6: Attribution

Link ad campaigns to:

Clues for attribution:

✅ Step 7: Report and Monitor Continuously

Create structured threat or influence reports

Log pixel IDs and ad accounts for recurring surveillance

Use alerts (e.g., Google Alerts, RSS on Ad Libraries)

🧩 OSINT Tips for Deeper AdINT Investigations

Next Steps

✅ Step-by-Step: How to Collect Ad Intelligence Data

Step 1: Define Your Goals

Ask:

Step 2: Choose Your Platforms

Decide:

Step 3: Use Public Libraries for Social Platforms

🔹 Facebook / Instagram

🔹 TikTok Ads Library

🔹 LinkedIn Ads

Step 4: Monitor Competitor Websites for Display Ads

Tools:

Step 5: Use API or Web Scraping (Advanced Users)

Example: Python + Selenium for Meta Ads

from selenium import webdriver
from time import sleep
driver = webdriver.Chrome()
driver.get("https://www.facebook.com/ads/library/")
sleep(5)
# Simulate input, search competitors, extract HTML, etc.

Example: Use Twitter API v2

import requests
bearer_token = "YOUR_TOKEN"
headers = {"Authorization": f"Bearer {bearer_token}"}
params = {"query": "ads", "tweet.fields": "author_id,created_at"}
res = requests.get("https://api.twitter.com/2/tweets/search/recent", headers=headers, params=params)
print(res.json())

📊 How to Analyze Ad Intelligence Data

Metrics to Focus On:

Metric Explanation
Impressions How often the ad was shown
Engagement Clicks, shares, comments, likes
Spend Estimates Use 3rd-party tools to estimate
Audience Targeting Gender, age, interest insights
Frequency How often the same person sees the ad
Format Static, video, carousel, story

Tools for Analysis

🔐 Legal & Ethical Considerations

🧠 Expert Tips

🧩 Sample Use Case

Let's say you're marketing a fitness supplement brand.

📚 Further Learning

Step A: Identify Trends

Step B: Generate Actionable Insights

Best Practices for Effective Ad Intelligence

Tool Comparison Table

Tool Comparison Table

Real-World Example: Applying Ad Intelligence

Scenario: You own a fitness e-commerce brand.

Goal: Boost sales via Instagram and Google Ads.

Tools Used:

Data Collection:

Findings:

Action Plan:

Conclusion

Ad intelligence is a game-changer for digital marketers in 2025 and beyond. Whether you're just starting or scaling up, collecting and analyzing ad intelligence data can uncover trends, improve targeting, and boost ROI. Start with free tools, scale to premium solutions, and always stay compliant. With consistent monitoring and a strategic approach, you'll be well-positioned to outperform the competition.

Sources

✅ Final Thoughts

Ad intelligence is no longer a luxury — it's a necessity in 2025's competitive digital landscape. By tracking what your competitors are doing — and more importantly, what's working for them — you can design smarter, higher-performing advertising campaigns.

Whether you're a startup, marketing analyst, or agency, leveraging ad intelligence can help you build data-driven, creative, and competitive marketing strategies.

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