Campaign Discovery

Campaign discovery

One sentence in ("a campaign positioning us as the AI-native alternative for marketing ops teams"), one discovery report out. You compose the specialist skills; you do not decide whether the campaign happens.

Needs: strategy/ filled (positioning, messaging, competitive/). The keyword part needs a wired seo-data integration and the answer-engine part a wired ai-visibility one; which vendor fills each is the Wired table in integrations/README.md, and seo-analyst and brand-monitor resolve it. Both are optional: without them, run the parts that work offline and mark the rest as gaps, naming the export a person could drop into data/seo/snapshots/YYYY-MM-DD-<vendor>-<what>.csv.

Procedure

1. Frame the idea. Restate the campaign in one line, name the persona from strategy/personas.md and the messaging pillar from strategy/messaging.md it leans on. If neither fits, that is the first open question.
2. Competitive angle. Read strategy/competitive/ (the battlecards) for who competes on this idea and how they position. Ask seo-analyst for the SERP competitors on the campaign's two or three core terms, so the report lists both the known competitors and whoever actually owns the search results. Note the angle they leave open.
3. Keywords. Ask seo-analyst for volumes, difficulty, and our current rank for the core terms plus up to ten ideas; the pull lands in data/seo/snapshots/. Flag which terms are in keywords.csv already and which would be proposed additions.
4. AI answer-engine coverage. Ask brand-monitor to run the prompts in data/seo/prompts.csv that touch this idea (and to propose up to three new prompts for it). Report who is cited today and whether we are.
5. Content inventory. Run content-inventory and take its report: what already exists that this campaign could reuse, refresh, or must not duplicate, grouped by channel with status and owner.
6. Write the report to reports/adhoc/YYYY-MM-DD-<slug>-discovery.md from reports/_templates/report.md, with these sections after the answer: competitive angle, keywords (table), AI answer-engine coverage (table), content inventory (by channel), what we would need to produce (a list: piece, channel, why, reuse or new), open questions for the team, and Data used with every snapshot path.

Worked example

"Run discovery on a campaign about meeting transcripts turning into tasks automatically."

• Framing: persona "marketing operations lead"; pillar "meetings stop evaporating".
• Competitive angle: two battlecards mention note-taking tools; SERP competitors for "meeting notes to tasks" are three note-taking apps, none positions on the marketing team. Open angle: the whole team's memory, not one person's notes.
• Keywords: "meeting transcript to action items" 1,900/mo, difficulty 34, we do not rank; "ai meeting notes" 40,500/mo, difficulty 71, not realistic. Snapshot data/seo/snapshots/2026-09-03-dataforseo-keyword-overview.csv.
• AI coverage: for "Which platforms turn meeting transcripts into decisions and tasks?" two note-taking apps are cited, we are not.
• Content inventory: one published blog post on decision logs (reuse), one LinkedIn draft in review (refresh), no email.
• What we would need to produce: a guide on the transcript pipeline (blog, new), an email to existing users (email, new), a refreshed LinkedIn post (reuse).
• Open questions: is the operations lead the buyer or the user; do we have a customer quote we can use.

Rules

• Propose, never decide: the report ends with questions and a list, not a go / no-go.
• Every number traces to a snapshot; a skill you could not run is a named gap.
• Do not scaffold the project or any content from here; new-project and new-content are separate, human-triggered steps.