--- name: Ads Intelligence slug: ads-intelligence category: Data description: Ads Intelligence routes ad research questions to Apify Actors and synthesizes results across Meta, Google, TikTok, LinkedIn, and X. Use it for competitor ads, creative analysis, landing page audits, and public ad library checks. github: "https://github.com/apify/awesome-skills/tree/main/skills/apify-ads-intelligence" language: Python stars: 248 forks: 61 install: "npx degit https://github.com/apify/awesome-skills/tree/main/skills/apify-ads-intelligence ~/.claude/skills/apify-ads-intelligence" installs_to: ~/.claude/skills/apify-ads-intelligence source_path: skills/apify-ads-intelligence/SKILL.md collection_size: 14 category_size: 678 collection_url: "https://dirskills.com/collections/apify/awesome-skills" added: 2026-09-02T05:21:11.390Z last_synced: 2026-09-02T05:21:11.390Z canonical_url: "https://dirskills.com/skills/ads-intelligence" --- # Ads Intelligence Ads Intelligence routes ad research questions to Apify Actors and synthesizes results across Meta, Google, TikTok, LinkedIn, and X. Use it for competitor ads, creative analysis, landing page audits, and public ad library checks. **Install:** ```bash npx degit https://github.com/apify/awesome-skills/tree/main/skills/apify-ads-intelligence ~/.claude/skills/apify-ads-intelligence ``` ## README # Ads Intelligence Cluster Answer natural language questions about ads, ad libraries, and competitor advertising activity by routing to the right Apify Actor and delivering a synthesized answer. **CLI rules:** Always pass `--user-agent apify-awesome-skills/apify-ads-intelligence`, `--json` (or the relevant `--format` flag on `datasets get-items`), and `2>/dev/null`. The `--user-agent` flag is critical for telemetry — never omit it. ## Note on platform coverage - **Meta, Google, TikTok, LinkedIn**: real public ad libraries with rich data (creatives, targeting, dates, reach where disclosed). - **X (Twitter)**: no public ad library exists. Coverage is a **best-effort workaround** that scrapes a brand's tweets and flags items with non-empty `card` field or `source` containing "Ads" as likely promoted. Always include the caveat in synthesis output. ## Note on overlap with `apify-ecommerce` That skill has an `ads-intelligence` intent that routes to `apify/facebook-ads-scraper` for shallow Meta-ad lookups. This skill is the deep dive across all five platforms. If you only need Meta ads as a side detail of an ecommerce question, stay in `apify-ecommerce`. If ads are the main task, use this skill. ## Prerequisites (No need to check it upfront) - Apify CLI v1.5.0+ (`npm install -g apify-cli`) - `jq` (recommended for response parsing and filtering; `brew install jq` on macOS, `apt install jq` on Linux) - Authentication via one of: - `apify login` (OAuth, opens browser) - `APIFY_TOKEN` env variable (e.g. `export APIFY_TOKEN=...` or `.env` file) - Token from [Apify Console → Settings → Integrations](https://console.apify.com/settings/integrations) Verify auth: `apify info --user-agent apify-awesome-skills/apify-ads-intelligence` — should show username and userId. ## Workflow Copy this checklist and track progress: ``` Task Progress: - [ ] Step 1: Detect intent and select Actor(s) - [ ] Step 2: Fetch Actor schema - [ ] Step 3: Ask user preferences (output format, result count, country) - [ ] Step 4: Run the Actor (or Actors in parallel for cross-platform-audit) and fetch results - [ ] Step 5: Synthesize a direct answer (not a data dump) ``` ### Step 1: Detect Intent and Select Actor Classify the user's message into an intent, then pick the right Actor. **Intent signals:** | Signals in user message | Intent | |-------------------------|--------| | "what ads is X running", "competitor [brand] ads", "[brand] FB/Google/TikTok/LinkedIn/X/Twitter ads", "show ads from [page]", "promoted tweets from [brand]" | `competitor-ads` | | "ads about [topic]", "find [keyword] ads", "ads for [vertical]", "fitness/fintech/saas ads" | `keyword-ads` | | "trending ads", "winning ads", "top ads", "best performing", "long-running ads", "creative inspiration" | `top-creatives` | | "where do these ads go", "landing pages from ads", "click destinations", "ad funnels" | `landing-page-audit` | | "compare X's ads across platforms", "all ads from [brand]", "cross-platform ad audit" | `cross-platform-audit` | If multiple intents detected, ask: *"Do you want [intent A] or [intent B]?"* **Actor routing — always try Primary first, switch to Fallback only if it fails or returns 0 results:** | Intent | Platform | Primary Actor | Fallback Actor | |--------|----------|---------------|----------------| | `competitor-ads` | Meta (FB/IG) | `apify/facebook-ads-scraper` | `brilliant_gum/facebook-ads-library-scraper` | | `competitor-ads` | Google | `dz_omar/google-ads-scraper` | `solidcode/ads-transparency-scraper` | | `competitor-ads` | TikTok | `brilliant_gum/tiktok-ads-library-scraper` (`source: library`) | `silva95gustavo/tiktok-ads-scraper` | | `competitor-ads` | LinkedIn | `silva95gustavo/linkedin-ad-library-scraper` | `dz_omar/linkedin-ads-scraper` | | `competitor-ads` | X (workaround) | `apidojo/twitter-scraper-lite` (`twitterHandles: []`) + heuristic filter | `apidojo/tweet-scraper` | | `keyword-ads` | Meta | `brilliant_gum/facebook-ads-library-scraper` | `apify/facebook-ads-scraper` | | `keyword-ads` | Google | `apify/google-search-scraper` (`focusOnPaidAds: true`) | — | | `keyword-ads` | TikTok | `brilliant_gum/tiktok-ads-library-scraper` | — | | `keyword-ads` | LinkedIn | `silva95gustavo/linkedin-ad-library-scraper` | — | | `keyword-ads` | X (workaround) | `apidojo/twitter-scraper-lite` (`searchTerms: []`) + heuristic filter | `apidojo/tweet-scraper` | | `top-creatives` | Meta | `brilliant_gum/facebook-ads-library-scraper` (rank by `daysRunning`) | — | | `top-creatives` | TikTok | `burbn/tiktok-top-ads-spy` (sort by CTR / impressions / likes) | `brilliant_gum/tiktok-ads-library-scraper` (`source: creative_center`) | | `top-creatives` | Google | n/a — fall back to `competitor-ads` route, filter to active ads | — | | `top-creatives` | LinkedIn | n/a — fall back to `competitor-ads` route, rank by `impressionsPerCountry` reach | — | | `top-creatives` | X | n/a in v1 — no reliable promoted-content signal across timelines | — | | `landing-page-audit` | Meta | `brilliant_gum/facebook-ads-library-scraper` (`resolveSnapshotUrls: true`) | — | | `landing-page-audit` | Google | `apify/google-search-scraper` (`focusOnPaidAds: true`, `directUrl`) | `dz_omar/google-ads-scraper` (`destinationUrl`) | | `landing-page-audit` | X | n/a in v1 — heuristics not reliable enough for landing-page extraction | — | | `cross-platform-audit` | All five | Run Meta + Google + TikTok + LinkedIn primaries in parallel; X workaround runs separately with caveat. Merge by advertiser. | — | **X (Twitter) heuristic filter** — after scraping, flag a tweet as *likely promoted* if any of the following hold: - `card` field is non-empty (website cards / CTAs are commonly attached to promoted tweets) - `source` field contains "Ads" (e.g. "Twitter Ads") Surface results with the explicit caveat: *"X has no public ad library; results below are tweets from the brand's own timeline that match promoted-content heuristics. They will miss promoted-only ads that appear in other users' feeds."* ### Step 2: Fetch Actor Schema Fetch the Actor summary, input schema, and README: ```bash # Summary (title, description, pricing, stats) apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-ads-intelligence --json 2>/dev/null # Input schema (required and optional parameters; schema lives in # .taggedBuilds.latest.build.inputSchema as an escaped JSON string) apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-ads-intelligence --input --json 2>/dev/null # README (capabilities, examples, gotchas) apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-ads-intelligence --readme 2>/dev/null ``` Replace `ACTOR_ID` with the selected Actor (e.g., `apify/facebook-ads-scraper`). ### Step 3: Ask User Preferences Before running, ask: 1. **Output format**: - **Quick answer** (default) — synthesized answer in chat, no file saved - **CSV** — full export saved to disk - **JSON** — full export saved to disk 2. **Result count** — defaults by intent: | Intent | Default count | |--------|---------------| | `competitor-ads` | 30 | | `keyword-ads` | 30 | | `top-creatives` | 20 | | `landing-page-audit` | 50 | | `cross-platform-audit` | 15 per platform | 3. **Country** — default `US`. For TikTok library specifically, default `DE` (EU-only) and warn the user; for global TikTok use `source: creative_center`. X routes are global by handle/keyword, no country parameter. **Cost safety**: Always set a sensible result limit in the Actor input (e.g., `maxResults`, `resultsLimit`, or the equivalent field per Actor schema). Warn the user before runs of 500+ ads — `apify/facebook-ads-scraper` charges per ad and X primaries charge per tweet. ### Step 4: Run the Actor and Fetch Results Two steps: run the Actor (blocks until done), then fetch dataset items in the requested format. **Run the Actor** — returns run metadata as JSON; extract `defaultDatasetId` for the next step: ```bash apify actors call "ACTOR_ID" -i 'JSON_INPUT' \ --user-agent apify-awesome-skills/apify-ads-intelligence --json 2>/dev/null ``` From the output use `.id` (run ID), `.status` (should be `SUCCEEDED`), and `.defaultDatasetId`. **Fetch results** — pick the variant based on the user's preference: ```bash # Quick answer: total count + fields + top 5 in chat (no file) apify datasets info DATASET_ID --json \ --user-agent apify-awesome-skills/apify-ads-intelligence 2>/dev/null \ | jq '{itemCount, fields, consoleUrl}' apify datasets get-items DATASET_ID --limit 5 \ --user-agent apify-awesome-skills/apify-ads-intelligence --format json 2>/dev/null # CSV file apify datasets get-items DATASET_ID \ --user-agent apify-awesome-skills/apify-ads-intelligence --format csv 2>/dev/null > YYYY-MM-DD_filename.csv # JSON file apify datasets get-items DATASET_ID \ --user-agent apify-awesome-skills/apify-ads-intelligence --format json 2>/dev/null > YYYY-MM-DD_filename.json ``` Other `--format` options: `jsonl`, `xlsx`, `xml`, `rss`, `html`. Use `--offset N` to paginate large datasets. **Tip:** for anything more than a quick peek, save the dataset to a local file first (with `> file.json` / `> file.csv`) and run further analysis from disk. `apify datasets get-items` always streams over the network, so piping it straight into `jq` re-downloads the whole thing every iteration. **Cross-platform audit (parallel runs):** For `cross-platform-audit`, kick off Meta + Google + TikTok + LinkedIn primaries in parallel by backgrounding each `apify actors call ...` invocation with `&` and calling `wait` before fetching results. Example: ```bash apify actors call "apify/facebook-ads-scraper" -i '' \ --user-agent apify-awesome-skills/apify-ads-intelligence --json 2>/dev/null > meta_run.json & apify actors call "dz_omar/google-ads-scraper" -i '' \ --user-agent apify-awesome-skills/apify-ads-intelligence --json 2>/dev/null > google_run.json & apify actors call "brilliant_gum/tiktok-ads-library-scraper" -i '' \ --user-agent apify-awesome-skills/apify-ads-intelligence --json 2>/dev/null > tiktok_run.json & apify actors call "silva95gustavo/linkedin-ad-library-scraper" -i '' \ --user-agent apify-awesome-skills/apify-ads-intelligence --json 2>/dev/null > linkedin_run.json & wait # Then extract each .defaultDatasetId and fetch items per platform; X workaround runs separately with caveat. ``` **Combining with `jq` for quick extraction:** Treat `jq` as a complement to `apify datasets get-items`, not a replacement: server-side `--limit` / `--offset` / `--format` keeps cost and bandwidth down. Use `jq` on a sample item or on a file you already saved. ```bash # Discover real field names from one sample item (Actor outputs vary — # use this before composing further jq queries) apify datasets get-items DATASET_ID --limit 1 --format json \ --user-agent apify-awesome-skills/apify-ads-intelligence 2>/dev/null \ | jq '.[0]' # X heuristic filter on a saved tweets file: keep items with non-empty card # or source containing "Ads" jq '[.[] | select((.card != null and .card != "") or (.source != null and (.source | contains("Ads"))))]' \ YYYY-MM-DD_x_tweets.json ``` ### Step 5: Analyze Results and Deliver Answer Synthesize, don't dump. Patterns by intent: | Intent | What the synthesis surfaces | |--------|------------------------------| | `competitor-ads` | Total ads found, active vs inactive split, top creative formats, top 5 ad copy snippets, list of unique landing-page domains. For X specifically: total tweets scraped, count flagged as likely-promoted, top 5 flagged tweets with the heuristic-detection caveat. | | `keyword-ads` | Top 5 advertisers running ads on this keyword, total ads, country split | | `top-creatives` | Top 5 by `daysRunning` (Meta) or CTR (TikTok), with creative summary, link to Ad Library entry | | `landing-page-audit` | List of unique landing URLs, grouped by domain, with ad counts pointing at each | | `cross-platform-audit` | Per-platform ad count and tone summary, then a "where they're spending most" inference | **Suggested follow-ups** — keyed off the intent that just ran: | If user just ran… | Suggest next | |-------------------|--------------| | `competitor-ads` (Meta) | Stack with `apify-competitor-intelligence` to add their FB Page posts, IG profile, and Google Maps reviews | | `landing-page-audit` (any) | Stack with `apify-ecommerce` (`tech-stack` intent) to detect the platform behind the landing pages, or with `apify-lead-generation` to enrich destination domains with contact info | | `top-creatives` (TikTok / Meta) | Stack with `apify-influencer-discovery` if any creatives are influencer collabs | | `keyword-ads` (Google / Meta) | Stack with `apify-trend-analysis` to see whether the keyword is rising or falling on Google Trends / Instagram / TikTok | | `cross-platform-audit` | Stack with `apify-content-analytics` for the brand's organic content side; combined paid + organic picture | ## Quirks - **TikTok keyword search is loose.** Searching "Nike" can return ads from unrelated advertisers (Interactive Brokers, Shopify in our test). Always post-filter by `advertiserName` matching the user's intended brand; warn the user if zero matches after filter. - **TikTok Ads Library is EU/EEA/UK only.** The `library` source needs an EU country code (DE / FR / IT / ES / NL / PL / SE etc.). For US/global coverage, switch to `creative_center` source — different fields (CTR, impression ranges, no targeting data). - **`dz_omar/google-ads-scraper` requires `resultsPerQuery >= 10`.** Smaller values fail validation. Always set 10+ even for small intents. - **`apify/facebook-ads-scraper` takes URLs, not keywords.** For `competitor-ads`: build `https://www.facebook.com/` from the brand name. For `keyword-ads`: build a Meta Ad Library URL with `q=&country=`. - **`apify/google-search-scraper` paid-ads mode** has a built-in retry (up to 3) when no paid results are found — sometimes a query genuinely has no paid results. Treat empty `paidResults` as a valid answer, not an error. - **LinkedIn Ad Library URL construction:** company URL `https://www.linkedin.com/company//` is allowed but slow and ignores filters. For `competitor-ads` use `https://www.linkedin.com/ad-library/search?accountOwner=&countries=`. For `keyword-ads` use `?keyword=&countries=`. - **X has no public ad library.** Coverage is heuristic only. The route uses `apidojo/twitter-scraper-lite` to scrape a brand's own tweets (or keyword search results), then flags items with non-empty `card` field or `source` containing "Ads" as *likely* promoted. This will miss promoted-only tweets that never appear in the brand's own timeline. - **X session sensitivity.** If the primary X Actor returns only `noResults` sentinels, switch to the fallback before declaring zero results. - **Pricing.** Most primaries are FREE in our pricing tier; `apify/facebook-ads-scraper` charges per ad ($0.001 - $0.0058); X primaries charge per tweet (~$0.0004 / 1k). Default counts (30 / 20 / 50) keep cost negligible. Warn before runs of 500+ ads. ## Error Handling - Auth error → run `apify login`, or set `APIFY_TOKEN` env var - `Actor not found` → check Actor ID against the routing table - Run status `FAILED` → open the console URL (`.consoleUrl` from run metadata) for logs - Timeout / very long run → pass `--timeout ` to `apify actors call`, or reduce result count - 0 results → switch to the Fallback Actor; if still 0, try a different country code - TikTok library: no EU country supplied → default to `DE` and warn the user - `dz_omar/google-ads-scraper`: validation error on `resultsPerQuery` → bump to 10+ - X scraper: only `noResults` sentinels → switch to the fallback X Actor - `proxy is required` error → add `"proxy": {"useApifyProxy": true}` to the input