Ad Intelligence
Competitor ad research, creative analysis, and platform intelligence for growth teams.
Reddit Ads Library in 2026: The Ads Inspiration Library, Reddit Ad Examples, and Competitor Research
A complete 2026 guide to the Reddit Ads Library — why the closest official surface is Reddit's Ads Inspiration Library rather than a Meta-style transparency database, exactly what it shows and hides, how to find and read Reddit ad examples, how to judge community fit, a full competitor-analysis workflow, how it compares to other ad libraries, the honest limits of public ad data, and where a cross-network creative-intelligence layer like AdMapix fits.
LinkedIn Ad Library API: What Actually Exists, What Doesn't, and the Workflow That Works in 2026
A developer-grade, honest explainer of the LinkedIn Ad Library API question. There is no public Ad Library API; LinkedIn runs a browse-only transparency website and a separate Advertising API for managing your own accounts. This guide untangles the two, explains what each returns, covers access, the legal and technical reality of scraping, the EU DSA context, and the manual-plus-tooling workflow CI teams actually use.
Pinterest Ads Library in 2026: The Ads Repository, Its Limits, and How to Research Promoted Pins
A complete 2026 guide to the Pinterest Ads Library — why it is really the DSA-driven Ads Repository, why access is EU-focused, exactly what it shows and hides, how to research promoted Pins when the repository is region-locked, how to read Pinterest creative by Pin format and category, the third-party spy methods that fill the gaps, the honest limits of public ad data, and where a cross-network creative-intelligence layer like AdMapix fits.
LinkedIn Ads Library in 2026: How to Find Competitor Ads and What It Shows
A complete 2026 guide to the LinkedIn Ads Library — how to access it from a company Page or by advertiser name, exactly which fields it shows and hides, how to read run-window longevity as a soft signal, the EU targeting disclosure, how it compares to Meta and Google ad libraries, the third-party tools that fill its gaps, the honest limits of public ad data, and where a cross-network creative-intelligence layer like AdMapix fits.
LinkedIn Ads Competitor Analysis: A Complete B2B Workflow for Reading, Tagging, and Out-Positioning Rival Campaigns
A flagship 2026 guide to LinkedIn ads competitor analysis for B2B teams. How to use the LinkedIn Ad Library, read competitor ads as messaging and offer hypotheses, tag every creative on six dimensions, run offer and format analysis, build recurring competitor reports, and turn it all into briefs and tests — with an honest account of what LinkedIn's public data can and cannot prove, and where AdMapix fits as a creative-evidence layer.
Paid Social Intelligence Tools (2026): Build a Five-Layer Stack That Improves Decisions
A practical 2026 guide to paid social intelligence tools — the five-layer stack (official libraries, search, creative, reporting, decision) that turns competitor ads into briefs, tests, and budget moves; what public ad data can and cannot prove; how to judge each tool by the decision it improves this week; and a repeatable weekly workflow across Meta, TikTok, and Google.
TikTok Ad Spy Tools for TikTok Shop in 2026: Free & Paid Compared (Seller's Guide)
A 2026 seller's guide to TikTok ad spy tools for TikTok Shop — free official sources, paid tools compared (PiPiAds, Minea, Kalodata, FastMoss, AdMapix), a shoppable-video teardown framework, a repeatable research SOP, and what public ad data can and cannot prove.
Minea Ad Spy Review (2026): What It Does Well, Its Limits & When to Switch
A hands-on, honest Minea ad spy review for 2026 — what Minea genuinely does best (winning-products feed, multi-network ad library, influencer signals), where it runs out of room, who it fits, a tier-by-tier pricing reality check, a fair scoring model, and exactly when to add a creative-intelligence layer like AdMapix instead.
Atria Ad Library in 2026: What It Solves and What to Check Before You Buy
A 2026 buying-decision guide to the Atria ad library — what its AI-powered collect, summarize, and ideate stack actually does, the four criteria that decide whether it is worth paying for (channel coverage, filter speed, AI insight quality, and brief handoff), a test-before-you-buy method you can run in a trial, the honest limits of what any ad library can prove, and where it fits versus a cross-network creative-evidence layer.
Competitive Advertising Intelligence: What It Is, How It Works, and How to Turn Signals Into Decisions
A definitional, framework-first guide to competitive advertising intelligence: what the discipline is, where its evidence comes from, how to grade that evidence by reliability, the end-to-end workflow that turns scattered signals into decisions, and an honest line between what public ad data can prove and what it can never reveal.
Paid Ads Analytics Tools in 2026: Metrics, the Stack & Data You Can Trust
A 2026 guide to paid ads analytics tools — the four jobs your stack must cover, the core metrics that actually drive decisions, a data-trust hierarchy that separates first-party from modeled and public signals, how attribution and cross-channel aggregation break in a privacy-constrained world, the tool-stack layers from native reports to MMPs to BI to competitor intelligence, how to choose by the decision each tool supports, and a weekly workflow that turns data into the next test.
How to Find Recent Ads in 2026: A Competitor Creative Discovery Workflow
A 2026 workflow for finding and tracking competitors' newest live ads — how to search official ad libraries by advertiser and filter for freshness across Meta, TikTok, and Google, why a recent ad signals intent but not success, the survival check that separates winners from noise, a weekly monitoring cadence, the honest limits of what recency can prove, and where a cross-network discovery layer replaces opening three libraries by hand.