| name | kai-retarget |
| description | Design retargeting and remarketing campaign architecture across platforms — audience segmentation, creative strategy, frequency caps, and platform-specific setup with ad policy compliance. Use when "retargeting", "remarketing", "retarget", "re-engage visitors", "abandoned cart", "pixel setup", or any request to bring back visitors who didn't convert. |
Objective
A retargeting architecture that is ready to build in the ad accounts: audience segments defined by intent and recency, creative matched to each segment's intent level, frequency caps, exclusion rules, sequence timing, budget split, and platform-compliant ad copy. The plan states which pixel events and URL rules define each audience, so someone can implement it without guessing.
Retargeting fails in two ways — showing the same ad to everyone regardless of how close they got, and showing it so often that it burns the brand. Segmentation and frequency caps exist to prevent both.
Done when
Work type paid-ad-campaign — floor E5/C4/O4 (harness/eco-floors.yaml), spend_authority: true.
- E5 — the platform returns ad object ids and a read-back of the live entities confirms targeting, budget, schedule, and creative match the approved bundle field for field. Hard stop: live-account mutation without recorded human approval is never SHIPPED, whatever the rest of the evidence shows.
- C4 — every platform's policy reference was loaded before the ad was written and the ad was checked against it; Four U's at 10/16 (ad threshold),
banned_word_check clean, mutation_risk_lint clean; frequency caps set per segment; converters and exclusion lists verified in place. Max 2 auto-retry cycles, each naming the specific failure.
- O4 — CAC, CPL, ROAS, or qualified-lead rate against a threshold declared before launch, read from the ads connector no earlier than the conversion window plus learning phase. Platform-reported ROAS is not attribution; a holdout or geo-split is what supports O5 (
knowledge/frameworks/marketing-science/attribution-and-incrementality.md).
Constraints
- Read
MARKETING.md from the project root first. If it does not exist, build it from the codebase — CLAUDE.md, README.md, PROJECT.md, package.json, landing pages, email/ad/analytics config — using the template from /kai-email-system, and confirm the draft. Do not ask the user what the product is.
- Seven things must be known before designing segments: traffic sources; conversion points that matter; where drop-off happens; which platforms have pixels or tags installed; monthly retargeting budget; which platforms to run; and product shape (B2B or B2C, high-ticket or impulse, long or short sales cycle).
- Load the policy reference for every active platform before writing a single line of ad copy. Compliance is not a review step applied afterward.
- Exclude converters from every retargeting pool. Also suppress existing customers, employees, and competitors.
- Frequency caps are mandatory per segment — typically 3–5 impressions/day maximum.
- Segment by intent level, not just by "visited the site": homepage visitors, pricing or product viewers, and cart or form abandoners are three different audiences with three different messages. Set recency windows at 1–3, 3–7, 7–30, and 30–90 days.
- Budget skews toward higher intent, and copy respects each platform's character limits and format rules.
- No live-account mutation. This skill produces the plan and the copy; building or editing audiences, budgets, and creative in a live account goes through human approval first.
Context
| Need | Load |
|---|
| Retargeting and remarketing mechanics | knowledge/playbooks/retargeting-remarketing.md |
| FTC, GDPR consent, pixel and tracking law | harness/references/advertising-compliance.md |
| Ad copy structural guardrails | harness/references/ad-write-guardrails.md |
| Paid ad format contract and gate minimums | harness/skill-contracts/meta-ads.yaml |
| Product, ICP, voice, current channels | MARKETING.md (project root) |
Platform policy — load the row for each active platform before writing:
| Platform | Reference |
|---|
| Meta | harness/references/meta-ads-rules.md |
| Google | harness/references/google-ads-policy-reference.md |
| LinkedIn | harness/references/linkedin-ads-rules.md |
| TikTok | harness/references/tiktok-ads-policy-reference.md |
| Microsoft/Bing | harness/references/microsoft-ads-rules.md |
| Pinterest | harness/references/pinterest-ads-rules.md |
| Snapchat | harness/references/snapchat-ads-policy-reference.md |
| Amazon | harness/references/amazon-ads-policy-reference.md |
| X/Twitter | harness/references/x-ads-policy-reference.md |
Creative by intent level:
| Segment | Signal | Message |
|---|
| Low intent | Homepage visitors | Brand awareness, social proof |
| Medium intent | Product or pricing viewers | Value props, comparison, objection handling |
| High intent | Cart or form abandoners | Urgency, incentive, friction removal |
Deliver: campaign architecture (segments, creative, timing), platform-ready audience definitions (pixel events, URL rules, time windows), ad copy per segment per platform, budget allocation table, frequency cap settings, exclusion rules, a per-platform policy compliance checklist, and the gate pass/fail summary.
Output goes to workspace/ as retarget-campaign-YYYY-MM-DD.md. Same path as v1.
Escalate when
- Pixels or conversion tags are missing on a platform the plan depends on.
- Drop-off data does not exist, so segments would be guessed rather than observed, or consent basis for tracking is unresolved in a jurisdiction the audience covers.
- The product falls in a Special Ad Category (housing, employment, credit) or another restricted vertical where retargeting is limited or banned.
- Budget is too small to sustain frequency across the proposed segment count.
- Anyone asks for the campaign to be built or edited in a live account without recorded approval.
