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AirMileAirMile/claude-config/skills/marketing-research/SKILL.md

marketing-research

Skill0 starsChanged 5 months agoMITView on GitHub

Research trends and audience signals for marketing. Use with /marketing-research.

3 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 7 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Search for .project/thinking/*-marketing-research.md.

    line 23
  2. Distinctive:

    Timing signals: when is the conversation most active?

    line 63
  3. Distinctive:

    Run WebSearch queries in parallel, derived from the scope angles.

    line 83
  4. Distinctive:

    Look for where consensus breaks — not "positive or negative?" but "where does sentiment fracture?" That breaking point is the most relevant …

    line 128
  5. Distinctive:

    Ask via AskUserQuestion which actor type is relevant:

    line 148
  6. Distinctive:

    Timing window: when — based on trajectory label

    line 163
  7. Very specific:

    NEVER blockquote syntax (>) — unreadable background in dark terminals

    line 240
  8. Distinctive:

    NEVER backticks for emphasis on regular words — use bold

    line 241
  9. Distinctive:

    Language: Follow the Language Policy in CLAUDE.md.

    line 244

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Marketing Research

Research marketing opportunities by analyzing trend signals, platform sentiment, and audience language. Identifies timing windows and produces actor-specific recommendations — no vague "keep monitoring" output.

Trigger: /marketing-research or /marketing-research [topic]

Complementary to /project-research (concept validation) — this skill actively searches for marketing opportunities, timing windows, and messaging entry points.

PHASE 0: Scope Definition

Existing report check:

Search for .project/thinking/*-marketing-research.md. If found, ask via AskUserQuestion:

header: "Existing report"
question: "A marketing research report already exists for this topic. What do you want to do?"
options:
  - label: "Load and continue (Recommended)", description: "Use existing report as basis for marketing-content"
  - label: "Research again", description: "Overwrite the existing report with new research"
multiSelect: false

On "Load and continue": show the SCOPE ANCHORS from the existing report and close PHASE 0. Go directly to PHASE 3 (Recommendations) or suggest next steps.

If $1 provided → use as starting point.

If no argument:

Ask via AskUserQuestion:

header: "Topic"
question: "What do you want to research for marketing?"
options:
  - label: "Product or feature launch", description: "Timing, messaging, audience for a launch"
  - label: "Content strategy", description: "Which topics, formats, platforms are relevant now"
  - label: "Competitive positioning", description: "How competitors position themselves and where the gap is"
  - label: "Campaign timing", description: "When a theme or topic has momentum"
multiSelect: false

Then ask for free-text input: product/concept + target audience + optional time window.

Scope extraction (two-step):

Extract 5-10 structured research angles from the free-text input. Categorize them:

  • Audience: who are they, what do they say, what language do they use?
  • Trending topics: what has momentum in this domain right now?
  • Competitors: how do they position themselves, what is their messaging?
  • Channels: where is the audience active?
  • Timing signals: when is the conversation most active?

Present as a mandatory output block — this is the contract between PHASE 0 and the rest of the skill, and the input for /marketing-content:

SCOPE ANCHORS

Topic: {topic in one sentence}
Audience: {who + 2-3 characteristics}
Trending topics: [{topic 1}, {topic 2}, ...]
Competitors: [{name 1}, {name 2}]
Active channels: [{platform 1}, {platform 2}]
Timing window: {active now / seasonal: {when} / open}
Research type: {launch / content / positioning / campaign timing}

Confirm via AskUserQuestion (Yes / Adjust).

PHASE 1: Multi-Source Research

Run WebSearch queries in parallel, derived from the scope angles. Cover at minimum:

  • Trend signals per platform (Twitter/X, Reddit, LinkedIn, HN, news sources)
  • Competitor messaging and positioning
  • Audience language and pain points (forums, reviews, comments)

Present findings per source with platform label:

PLATFORM — {platform name}

Query: "{search query}"

Findings:
- {key finding 1}
- {key finding 2}

Sources: {URLs}

PHASE 2: Signal Analysis

Analyze the collected data on three axes:

Platform temperature differences:

PlatformCharacter
Twitter/XEarly adoption, emotional, fast cycles
RedditCritical, detailed, niche communities
LinkedInProfessional, lagging indicator, B2B sentiment
Hacker NewsTech/startup, skeptical, anti-hype
Product HuntLaunch-moment buzz, early adopters

Temperature difference = actively interpret: "trending on X but not on LinkedIn" is a signal, not a gap.

Trajectory per topic — label each relevant topic:

  • acute_rise: appears and rises quickly → time-sensitive window
  • plateau: high but stable → mainstream, commodity risk
  • zombie: lingers without growth → exhausted momentum
  • comeback: was gone, returns → new trigger, investigate cause

Sentiment conflict:

Look for where consensus breaks — not "positive or negative?" but "where does sentiment fracture?" That breaking point is the most relevant moment for campaign timing.

Present:

SIGNAL ANALYSIS

Platform temperatures:
- {platform}: {trajectory label} — {character of the conversation}
- {platform}: {trajectory label} — {character of the conversation}

Temperature difference: {interpretation of the difference between platforms}

Weak signals: {what is in niche sources but not in mainstream?}

Sentiment conflict: {where does consensus fracture? what is the actual conflict?}

PHASE 3: Actor-Specific Recommendations

Ask via AskUserQuestion which actor type is relevant:

header: "Actor type"
question: "Who are the recommendations for?"
options:
  - label: "Brand / company (Recommended)", description: "Marketing team, content strategy, campaigns"
  - label: "Solo creator / personal brand", description: "Content creator, thought leader, freelancer"
  - label: "Agency / consultant", description: "Advice for clients, positioning"
multiSelect: false

Generate a concrete recommendation per relevant scope angle:

  • Action: what specifically to do (not "consider X" but "publish Y on Z")
  • Timing window: when — based on trajectory label
  • Reasoning: which signal justifies this
  • Platform: where to activate

No "keep monitoring" advice allowed. Every recommendation ends with a concrete action or decision. If the moment is not yet right: say that explicitly with the condition under which it becomes right.

Present as table:

RECOMMENDATIONS — {actor type}

| # | Action | Timing | Platform | Reasoning |
|---|--------|--------|----------|-----------|
| 1 | {concrete action} | {now / in N weeks / wait for X} | {platform} | {signal} |
| 2 | ... | ... | ... | ... |

PHASE 4: Report + Save

Generate a markdown report:

# Marketing Research: {topic}

## Summary

{2-3 sentences: what is the core opportunity and the core risk?}

## Signal Analysis

### Platform Temperatures

{temperature differences + trajectories}

### Sentiment Conflict

{where does consensus fracture?}

### Weak Signals

{what mainstream doesn't cover}

## Audience Language

{exact words, frames, and pain points the audience uses}

## Competitive Positioning

{how do competitors position themselves and where is the gap?}

## Recommendations

| #   | Action | Timing | Platform | Reasoning |
| --- | ------ | ------ | -------- | --------- |

{table from PHASE 3}

## Sources

- [{source title}]({url})

Save to .project/thinking/{topic}-marketing-research.md.

Show next steps:

Next steps:
- /marketing-content  — write text variants based on these signals
- /marketing-screenshots — marketing screenshots for launch
- /project-plan       — feature backlog based on market insights

Guidelines

Formatting:

  • NEVER blockquote syntax (>) — unreadable background in dark terminals
  • NEVER backticks for emphasis on regular words — use bold
  • Backticks only for code, file paths, and command references

Language: Follow the Language Policy in CLAUDE.md.

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