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Media buyer morning routine, automated: an overnight competitor scan, diff logic, and a 7:30 Slack digest replace 20 minutes of tabs. Working code inside.
Replace the morning ad-library tab cycle with four API scripts: inspiration sweep, competitor watch, format trends, and brief feeding, in 10 min a day.
Every competitor ad carries a destination URL. Extract and cluster landing page URLs at scale to map competitor funnels, offers, and launch signals.
Give your LLM agent ad research tools: function schemas for ad search and advertiser resolve, credit-economy system prompts, result compression, and evals.
Ad transparency data compared across Meta, Google, TikTok, LinkedIn, Snapchat, Pinterest & X: fields, retention, APIs, DSA effects, and unified access.
Every estimated ad spend number is modeled, not billed. See how impression buckets and CPM models build the estimate, the error bands, and the safe uses.
Build a custom GPT that searches live competitor ads by chat: the exact OpenAPI Actions schema, bearer auth setup, credit-aware instructions, and real limits.
Build vs buy ad intelligence, priced honestly: DIY scrapers, managed actors, commercial APIs, and manual research compared on real TCO, ToS risk, and time.
TikTok ad library API options in 2026: what the official Commercial Content API requires and excludes, and how to query TikTok ads programmatically.
Build a weekly competitor ad email digest your team actually reads: scheduled API scan, diff, LLM summary, and HTML email via Resend, SES, or SMTP.
Build a Looker Studio competitor ads dashboard: pull ad data via API into Sheets or BigQuery, map the fields, and ship the 6 charts your intel deck needs.
Build Discord competitor ad alerts with one webhook and a poll script: first-seen filtering, embed previews, role mentions, rate limits, and cron options.
Build a Streamlit marketing app for competitor ad research in ~150 lines of Python: sidebar filters, cached API search, ad grid, watchlists, CSV export.
Build a Notion competitor ad hub fed by an ad library API: database schema, sync script with dedup, gallery views, team annotation, and the real limits.
Build a BigQuery competitor ads warehouse: four-table schema, Cloud Function load pipeline, partitioning, dedup, and six SQL analyses incl. share of voice.
