Competitor Spy

Competitor Spy

Analyze competitor affiliate sites, YouTube channels, and social profiles to surface which programs they promote, what content drives their traffic, and which strategies are worth replicating. Outputs an actionable reverse-engineering report so you can skip years of trial and error.

Stage

This skill belongs to Stage S1: Research

When to Use

• User wants to know what programs are working in a specific niche
• User has a competitor site/channel in mind and wants to understand their strategy
• User is entering a new niche and wants a shortcut to what works
• User wants to find underserved content gaps a competitor hasn't covered
• User asks "how do top affiliates in [niche] make money?"

Input Schema

{
  competitor_url: string      # (optional) Direct URL to competitor site, channel, or profile
  niche: string               # (optional) Niche to analyze if no specific competitor given
  platform: string            # (optional) "blog" | "youtube" | "tiktok" | "twitter" | "newsletter"
  depth: string               # (optional, default: "standard") "quick" | "standard" | "deep"
  focus: string               # (optional) "programs" | "content" | "traffic" | "all"
}

Workflow

Step 1: Identify Competitors to Analyze

If competitor_url is provided, skip to Step 2.

If only niche is provided, find 3-5 top competitors:

1. web_search "best [niche] affiliate sites" — look for review/comparison sites
2. web_search "[niche] review site affiliate" — find review-first monetization models
3. web_search "[niche] blog affiliate income report" — income reports reveal programs
4. Note: YouTube — web_search "youtube [niche] affiliate site:youtube.com" to find channels

Pick 3 competitors that are clearly affiliate-driven (review pages, comparison tables, "best X" content, Amazon links, affiliate disclaimers visible).

Step 2: Identify Affiliate Programs They Promote

For each competitor site/channel:

Method A — Link analysis:

• web_fetch [competitor_url] and scan for outbound links
• Look for: ?ref=, ?via=, /go/, aff_id=, ?affiliate=, shareasale.com, impact.com, partnerstack.com, awin.com, cj.com, linktr.ee
• These patterns indicate affiliate links

Method B — Content analysis:

• Look at their top content: "Best X", "X vs Y", "X Review", "X Alternatives"
• Every product featured prominently = likely affiliate relationship
• Products mentioned with a CTA button ("Try X Free", "Get X") = strong affiliate signal

Method C — Disclosure scan:

• Search page for "affiliate", "commission", "sponsored", "partner" disclosures
• These legally required disclosures often appear at top/bottom and reveal programs

Method D — Income reports (if available):

• web_search "[site name] income report affiliate" — some affiliates publish earnings
• web_search "[creator name] how I make money affiliate" — creator transparency posts

Extract for each program found: name, estimated prominence (primary/secondary/mentioned), content type promoting it, and whether it appears on openaffiliate.dev.

Step 2.5: Analyze Competitor Content Engagement (data-driven)

For each competitor, scan their recent content performance across social platforms. This reveals not just WHAT they create, but HOW WELL it performs.

With API (optional — see shared/references/social-data-providers.md):

• Search YouTube/TikTok for competitor brand name or channel
• Get views, likes, comments, shares for their top 10-20 content pieces
• Calculate engagement_score for each: (likes × 2 + comments × 3 + shares × 5) / max(views, 1) × 1000
• Identify which content format gets them the highest engagement
• Compare their engagement against trending-content-scout benchmark (if available)

Without API (default):

• web_search "[competitor name] youtube channel" → find their channel
• web_fetch channel page → extract view counts from visible videos
• web_search "[competitor name] tiktok" → find top videos with view counts
• web_search "[competitor name] best video" → find their highest-performing content
• Note: approximate data, but reveals relative performance patterns

Extract for each competitor:

• Avg engagement score — how well does their content perform overall?
• Strongest platform — where do they get the most traction?
• Weakest platform — which platforms are they ignoring? (gap to exploit)
• Top performing content — their 3-5 best pieces by engagement
• Format that works for them — which content format gets them the most engagement?

Add these to the competitor assessment table in Step 5:

Step 3: Analyze Their Content Strategy

For each competitor, extract:

Content patterns:

• Most common formats: listicles ("10 best X"), comparisons ("X vs Y"), tutorials, reviews, roundups, case studies
• Average content depth: shallow (<1000 words), standard (1000-3000), deep (3000+)
• Publishing frequency: estimate from visible dates or web_search "site:[domain] 2024"
• Content freshness: are articles updated? When?

Traffic indicators (from web search signals):

• web_search "site:[domain]" — rough page count
• Search for their brand name — how much branded traffic/discussion?
• Look for "X review" queries in their content — review content = high buyer intent

SEO and social signals:

• Do they rank for "[product] review" terms? (indicates SEO strategy)
• Active social profiles linked from site? Which platforms?
• Do they have a newsletter/email list? (footer signup forms)

Step 4: Find Content Gaps

Compare competitor content to what's NOT covered:

1. Products they promote but haven't done deep comparison posts for
2. Common user questions (from YouTube comments, Reddit threads, forums) they haven't answered
3. New product launches in the niche that competitors haven't covered yet
4. Angles competitors avoid (negative reviews, honest cons, "X is not for everyone")

Use web_search "reddit [niche] [product] problems" to find pain points no affiliate has addressed honestly — these make high-converting, low-competition content.

Step 5: Score Competitor Strategies

For each competitor, assess:

Higher replicability score = easier to beat them.