analytics-checker | analytics-checker

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analytics-checker | analytics-checker

Analytics Checker

Interprets platform analytics data and turns numbers into clear, actionable recommendations.

Step 1: Identify What Data You Have

Ask the user to share their analytics in one of these forms:

Screenshot or image of their analytics dashboard
CSV/export file from their platform
Pasted numbers directly in chat
Verbal description ("my views dropped 40% last month")

Also confirm:

Which platform the data is from
What time period it covers
What their goal is (growth, engagement, monetization, sales)

Step 2: Platform-Specific Metrics Guide

YouTube

Metric	What it means	Healthy benchmark
CTR (Click-Through Rate)	% who click after seeing thumbnail	4–10% is good; 2–4% is average
Average View Duration	How long people watch	Aim for 40–60%+ of video length
Impressions	How often YouTube shows your video	Higher = algorithm is pushing it
Watch Time (hours)	Total hours watched	Key for monetization and ranking
Subscribers gained	Net new subs from video	Positive = video resonates with new audience
Revenue / RPM	Revenue per 1,000 views	Varies by niche: $2–$50 RPM

Key YouTube diagnostic questions:

Is CTR high but AVD low? → Hook is working, but content isn't delivering on the promise
Is CTR low but AVD high? → Great content, weak thumbnail/title
Are impressions low? → Algorithm isn't distributing the video — check SEO and watch time on recent uploads

TikTok

Metric	Benchmark	Notes
Views	N/A — highly variable	Don't compare to other creators
Watch time %	70–100% = great	TikTok rewards completion rate
Shares	>1% of views = strong	Shares are the #1 growth signal
Profile visits	Indicates interest beyond the video
Follower conversion	Views → Followers

Key TikTok diagnostic questions:

Low completion rate? → Hook isn't holding. Restructure opening 3 seconds.
High views but low follows? → Content is entertaining but not niche-clear
Video stuck at ~300 views? → Initial engagement was too low — try posting at a different time

Instagram

Metric	Notes
Reach	Unique accounts who saw the post
Impressions	Total views (including repeat)
Engagement rate	(Likes+Comments+Saves+Shares) / Reach — aim for 3–6%+
Saves	High saves = high-value content (algorithm loves this)
Shares	Virality signal
Story views / exits	Where people drop off in stories
Reel plays	Treated like TikTok — completion rate matters

LinkedIn

Metric	Notes
Impressions	How many times shown
Reactions + Comments + Shares	Engagement indicators
Follower demographics	Are you reaching the right people?
CTR on links	If you post external links (usually lower reach)

Twitter/X

Metric	What it means	Healthy benchmark
CTR (Click-Through Rate)	% who click after seeing thumbnail	4–10% is good; 2–4% is average
Average View Duration	How long people watch	Aim for 40–60%+ of video length
Impressions	How often YouTube shows your video	Higher = algorithm is pushing it
Watch Time (hours)	Total hours watched	Key for monetization and ranking
Subscribers gained	Net new subs from video	Positive = video resonates with new audience
Revenue / RPM	Revenue per 1,000 views	Varies by niche: $2–$50 RPM

Step 3: Diagnose the Data

For any analytics input, run through this diagnostic framework:

The 3-Layer Diagnosis

Discovery — Is the platform showing your content to enough people?
- Low impressions/reach? → Posting frequency, SEO, hashtags, posting time
Click-through / Hook — Are people choosing to engage with it?
- Low CTR or low swipe-ups? → Thumbnail, title, hook text
Retention / Completion — Are people staying once they start?
- High drop-off? → Content pacing, length, value delivery

Step 4: Output Format

📊 ANALYTICS REPORT: [Platform] — [Period]

🔍 OVERVIEW
[2–3 sentence summary of overall performance]

📈 WHAT'S WORKING
- [Metric]: [Value] → [Why this is good and what it signals]
- ...

⚠️ AREAS TO IMPROVE
- [Metric]: [Value] → [What it indicates and why it matters]
- ...

🎯 TOP 3 RECOMMENDATIONS
1. [Specific action] — [Why it will help based on the data]
2. ...
3. ...

📅 WHAT TO TEST NEXT
[Suggest 1–2 experiments based on the data]

Step 5: Trend Analysis

If the user has data over multiple periods:

Identify trends (growing, declining, plateauing)
Flag anomalies (sudden spikes or drops — what caused them?)
Suggest comparisons ("your best-performing video did X — how does this differ?")

Tips

No data yet: If the user is just starting out, explain which metrics to watch first and how to read their platform's native dashboard.
CSV files: Parse them, identify key columns, and summarize the top insights.
Screenshots: Describe what you see and analyze it against benchmarks.
Overwhelmed users: Focus on 2–3 actionable metrics, not everything at once.
Monetization questions: Know CPM/RPM differences, YouTube Partner Program thresholds (1,000 subs + 4,000 watch hours or 10M Shorts views).