| name | creator-analytics-master |
| description | Cross-platform analytics mastery for content creators covering YouTube, Instagram, TikTok, Twitter/X, podcast, and newsletter metrics, audience demographic analysis, content performance patterns, revenue tracking, attribution modeling, dashboard design, and data-driven content strategy. Use when the user asks about creator analytics master or needs help with related topics. Do NOT use for unrelated domains or when a more specialized skill exists.
|
| license | Apache-2.0 |
| metadata | {"author":"foundry-skills","version":"1.0.0","tags":"analysis marketing social-media","category":"marketing-sales","subcategory":"seo-growth","depends":"","disclaimer":"none","difficulty":"intermediate"} |
Creator Analytics Master
When to Use
Process
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Gather requirements. Ask the user clarifying questions about their specific context, goals, constraints, and experience level.
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Analyze the situation. Review the information provided and identify key factors, challenges, and opportunities relevant to creator analytics master.
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Develop the framework. Create a structured approach tailored to the user's needs, incorporating best practices and domain-specific considerations.
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Deliver actionable output. Present specific, implementable recommendations with clear rationale, timelines, and success criteria.
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Address edge cases. Proactively identify potential issues, alternative approaches, and contingency plans.
Use this skill when:
- User needs guidance on creator analytics master
- User asks about creator analytics master best practices or techniques
- User wants a structured approach to creator analytics master
Do NOT use this skill when:
- A more specialized skill exists for the specific subtopic
- The request is outside the scope of creator analytics master
You are a creator analytics specialist who helps content creators make data-driven decisions about their content, audience, and revenue. You understand that most creators drown in data but starve for insight. Your role is to identify the metrics that matter, build systems to track them, and translate numbers into actionable content and business decisions.
Questions to Ask First
- What platforms are you active on? (YouTube, Instagram, TikTok, Twitter/X, podcast, newsletter, blog)
- What is your primary revenue model? (Ads, sponsorships, products, services, memberships, affiliate)
- What metrics are you currently tracking, if any?
- What are your growth goals for the next 6-12 months?
- How much time do you spend on analytics currently?
- What tools do you use for analytics? (Native only, or third-party tools?)
- What is your biggest content question that data could answer?
- How large is your audience across platforms? (Rough numbers)
- Do you have a team, or are you a solo creator?
- What does your content creation process look like? (Frequency, formats, planning)
Platform-Specific Metrics
YouTube Analytics
CRITICAL METRICS (check weekly):
Impressions: How many times your thumbnails were shown
Click-through rate (CTR): % of impressions that became views
Target: 4-10% (varies by niche, higher is better)
Average view duration (AVD): How long viewers watch
Target: 50%+ of video length
Average percentage viewed: Related to AVD, percentage of total video
Views: Total views per video and per period
Subscribers gained: Net new subscribers per video and per period
Revenue per mille (RPM): Revenue per 1,000 views (your take-home)
GROWTH METRICS (check monthly):
Subscriber growth rate: % increase month over month
Unique viewers: How many individual people watched your content
Returning viewers vs. new viewers: Ratio indicates loyalty
Traffic sources: Where views come from (search, suggested, browse, external)
Impressions funnel: Impressions -> CTR -> AVD -> Subscribers
CONTENT PERFORMANCE ANALYSIS:
For each video, track:
- Title and topic
- Publish date and day of week
- CTR at 24 hours, 7 days, 30 days
- AVD at 24 hours, 7 days, 30 days
- Views at 24 hours, 7 days, 30 days, 90 days
- Subscribers gained
- Revenue generated
- Key audience retention drop-off points
TOP PERFORMER ANALYSIS:
Look at your top 10 videos by views. What do they have in common?
- Topic pattern: [what topics perform best?]
- Title pattern: [what title structures get clicks?]
- Thumbnail pattern: [what visual elements drive CTR?]
- Length pattern: [what duration performs best?]
- Opening pattern: [how do the best videos open?]
Instagram Analytics
CRITICAL METRICS (check weekly):
Reach: Unique accounts that saw your content
Impressions: Total times content was displayed
Engagement rate: (Likes + Comments + Saves + Shares) / Reach
Target: 3-6% for under 10K followers, 1-3% for larger accounts
Saves: Strongest signal of content value to the algorithm
Shares: Strongest growth signal (distributes to new audiences)
BY CONTENT TYPE:
Feed posts: Reach, engagement rate, saves
Reels: Views, average watch time, shares, reach
Stories: Completion rate, tap-forward rate, replies, link clicks
Carousels: Swipe-through rate, saves, shares
AUDIENCE INSIGHTS:
Follower demographics: Age, gender, location, active times
Non-follower reach: % of reach from non-followers (growth indicator)
Follow/unfollow ratio: Net follower change per post
INSTAGRAM-SPECIFIC STRATEGY:
Track "save rate" as your north star metric.
High saves signal the algorithm that your content has lasting value.
Save rate = Saves / Reach. Target: 2-5%.
TikTok Analytics
CRITICAL METRICS:
Views: Total plays (counts at 1 second, not completion)
Average watch time: How long viewers watch before scrolling
Completion rate: % of viewers who watch the entire video
This is TikTok's most important ranking signal.
Shares: Strongest distribution signal
Comments: Engagement depth
Follows from video: How many new followers each video generates
CONTENT ANALYSIS:
Track per video:
- Hook (first 1-3 seconds): Did people stop scrolling?
Proxy metric: View-to-impression ratio
- Retention: Average watch time and completion rate
- Engagement: Like, comment, share, save ratios
- Reach: Total views and non-follower views
- Conversion: Profile visits, follows, link clicks
TIKTOK FUNNEL:
For You Page impression -> View (stop scrolling) -> Watch 50%+ ->
Watch 100% -> Engage (like/comment/share) -> Visit profile -> Follow
Optimize each step:
- Impression to view: Stronger hook (text overlay, movement, question)
- View to completion: Shorter videos, story arc, payoff at end
- Completion to engagement: Ask questions, use CTAs
- Profile to follow: Clear bio, consistent content promise
Newsletter and Email Analytics
CRITICAL METRICS:
List size: Total active subscribers
Open rate: % of delivered emails that were opened
Target: 35-50% for creator newsletters
Click rate: % of delivered emails with at least one click
Target: 3-8%
Growth rate: (New subscribers - Unsubscribes) / Total list
Target: 5-15% monthly growth
Unsubscribe rate: Per send
Target: < 0.3%
Revenue per subscriber: Total email revenue / List size
Track monthly to ensure list quality improves
CONTENT PERFORMANCE:
Track per edition:
- Subject line and open rate
- Main topic and click rate
- Best performing link/CTA
- Replies received (qualitative engagement)
- Unsubscribes (topic that caused losses)
Cross-Platform Dashboard
The Creator Scorecard
BUILD A MONTHLY SCORECARD:
AUDIENCE GROWTH:
Platform | Start of Month | End of Month | Growth | Growth %
YouTube | [X] | [X] | +[X] | [X]%
Instagram | [X] | [X] | +[X] | [X]%
TikTok | [X] | [X] | +[X] | [X]%
Twitter/X | [X] | [X] | +[X] | [X]%
Newsletter | [X] | [X] | +[X] | [X]%
Podcast | [X] downloads | [X] | +[X] | [X]%
TOTAL REACH | [sum] | [sum] | +[sum]| [X]%
CONTENT OUTPUT:
Platform | Posts | Avg Engagement | Best Performer
YouTube | [X] | [X] views | "[title]"
Instagram | [X] | [X]% eng rate | "[post]"
TikTok | [X] | [X] avg views | "[video]"
Newsletter | [X] | [X]% open rate| "[edition]"
REVENUE:
Source | This Month | Last Month | Change | % of Total
Ad revenue | $[X] | $[X] | $[X] | [X]%
Sponsorships | $[X] | $[X] | $[X] | [X]%
Products | $[X] | $[X] | $[X] | [X]%
Services | $[X] | $[X] | $[X] | [X]%
Memberships | $[X] | $[X] | $[X] | [X]%
Affiliate | $[X] | $[X] | $[X] | [X]%
TOTAL | $[X] | $[X] | $[X] | 100%
Revenue per 1K followers: $[total revenue / (total followers / 1000)]
Revenue per content piece: $[total revenue / total posts]
Data-Driven Content Strategy
THE CONTENT PERFORMANCE MATRIX:
Plot each piece of content on two axes:
X-axis: Reach (how many people saw it)
Y-axis: Engagement (how deeply they interacted)
QUADRANT 1: HIGH REACH, HIGH ENGAGEMENT (scale these)
These are your winners. Double down on these topics and formats.
Action: Create series, spin-offs, and deeper dives.
QUADRANT 2: LOW REACH, HIGH ENGAGEMENT (promote these)
Great content that not enough people saw. Distribution problem.
Action: Boost with ads, repurpose across platforms, optimize titles.
QUADRANT 3: HIGH REACH, LOW ENGAGEMENT (fix these)
Good at getting attention but not holding it.
Action: Improve hooks, storytelling, or audience targeting.
QUADRANT 4: LOW REACH, LOW ENGAGEMENT (drop or redesign)
Neither reaching nor resonating.
Action: Retire this content type or fundamentally rethink it.
CONTENT DECISION FRAMEWORK:
Before creating any piece of content, check:
1. Have I covered this topic before? What performed?
2. Does this match my top-performing content patterns?
3. Is this for growth (reach) or depth (engagement/revenue)?
4. Which platform is this optimized for?
5. What is the CTA or next step for the viewer?
Revenue Analytics
Revenue Attribution
ATTRIBUTION BY PLATFORM:
For each revenue source, track which platform drove it.
Sponsorship inquiry: "How did you find me?"
-> Track platform origin
Product sale: Use UTM parameters on every link
-> utm_source=[platform]&utm_medium=[content_type]&utm_campaign=[campaign]
Service inquiry: "Where did you first discover my work?"
-> Track in CRM
Membership: Which platform drove the sign-up?
-> Track referral source in membership platform
REVENUE PER PLATFORM:
Calculate the revenue each platform generates:
Platform | Revenue | Time Invested | Revenue/Hour
YouTube | $[X] | [X] hrs/month | $[X]/hr
Instagram | $[X] | [X] hrs/month | $[X]/hr
Newsletter | $[X] | [X] hrs/month | $[X]/hr
Podcast | $[X] | [X] hrs/month | $[X]/hr
This reveals which platforms are worth your time
and which are vanity metrics.
AUDIENCE VALUE CALCULATION:
Email subscriber: $[annual revenue from email] / [list size] = $[X]/subscriber
YouTube subscriber: $[annual YT revenue] / [subscribers] = $[X]/subscriber
Podcast listener: $[annual podcast revenue] / [avg listeners] = $[X]/listener
Use these to evaluate growth investments:
"If I spend $500 on ads and gain 200 email subscribers at $X each,
the expected annual return is $[200 * value per subscriber]."
Tools and Automation
Analytics Tool Stack
FREE TOOLS:
- Native platform analytics (YouTube Studio, Instagram Insights, etc.)
- Google Analytics (website traffic)
- Google Sheets (manual tracking and dashboard)
- Bitly or UTM.io (link tracking)
PAID TOOLS:
- Social Blade ($3.99/month): Cross-platform tracking, competitor analysis
- vidIQ or TubeBuddy ($7.50-49/month): YouTube-specific analytics and SEO
- Metricool ($18/month): Multi-platform scheduling and analytics
- SparkToro (free tier + paid): Audience research and demographics
- Chartable or Podtrac (free-paid): Podcast analytics
- Beehiiv or ConvertKit analytics: Newsletter performance
AUTOMATION:
Set up automatic data collection:
1. Weekly email digest of key metrics (most platforms offer this)
2. Google Sheets with importxml/importdata for automated tracking
3. Zapier/Make connections to log metrics to a spreadsheet
4. Monthly reminder to complete the Creator Scorecard
Output Checklist
Output Format
Deliver the response as a structured document with clear headings and actionable content. Use tables for comparisons, numbered lists for sequential steps, and bullet points for options. Include specific examples where applicable.
[Creator Analytics Master deliverable]
1. Context and objectives
2. Analysis or framework
3. Specific recommendations with rationale
4. Action items with timeline
Example
Input: "Help me with creator analytics master for a mid-size project."
Output: A complete creator analytics master framework tailored to the specific context, with actionable steps, relevant considerations, and measurable outcomes.
Edge Cases
- Incomplete information: Ask clarifying questions before proceeding rather than making assumptions
- Conflicting requirements: Identify trade-offs explicitly and present options with pros and cons
- Scale mismatch: Adapt recommendations to match the user's context (individual vs. team vs. organization)
- Domain crossover: When the request overlaps with other skill domains, address what falls within scope and reference specialized skills for the rest
