Documentation Index
Fetch the complete documentation index at: https://mintlify.com/subratomandal/dyeink/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Dyeink includes built-in analytics to help you understand how your blog is performing. Track views, shares, and published posts without needing external analytics tools.All analytics are privacy-focused and don’t track individual users or use cookies. Only aggregate statistics are collected.
Accessing Analytics
You can view your analytics in two places:- Dashboard - Quick overview of key metrics with a visual graph
- Stats - Detailed breakdown by metric type (Traffic, Sharing)
Dashboard Analytics
The Dashboard provides an at-a-glance view of your blog’s performance:Key Metrics
Total Views
Cumulative page views across all your published posts
Total Shares
Number of times your posts have been shared
Published Posts
Count of live, published posts on your blog
Analytics Graph
The dashboard includes a 7-day trend graph showing:- Views (blue line) - Daily page views
- Published (purple line) - Posts published each day
- Spot trends in traffic
- Correlate publishing activity with views
- Identify your best-performing days
The graph shows data for the last 7 days. Historical data beyond 7 days is aggregated into total metrics.
Stats Page
For more detailed analytics, visit the Stats page from your admin sidebar.Traffic Tab
The Traffic tab shows view-related metrics:- Total Views - All-time page views
- Published - Number of published posts
Sharing Tab
The Sharing tab tracks social engagement:- Total Shares - Number of times posts were shared
Understanding Your Metrics
Views
What counts as a view:- Each page load of a published post
- Multiple views from the same visitor
- Views from any source (direct, search, social, etc.)
- Previews in the editor
- Admin panel visits
- Unpublished draft views
Shares
What counts as a share:- Clicks on social share buttons
- Shares via Twitter, Facebook, LinkedIn, etc.
- Share buttons on your blog increment the counter
- Each share button click is counted
- Shares are attributed to the specific post
Published Posts
What counts:- Posts with
published: truestatus - Live posts accessible on your blog
- Drafts
- Deleted posts
Analytics Best Practices
Check analytics regularly
Check analytics regularly
Review your dashboard weekly to:
- Track growth trends
- Identify popular content
- Understand publishing patterns
Correlate views with publishing
Correlate views with publishing
Use the graph to see:
- Which publishing schedule works best
- How new posts drive traffic
- When your audience is most active
Monitor shares for engagement
Monitor shares for engagement
Track growth over time
Track growth over time
Compare metrics week-over-week:
- Are views trending up?
- Is publishing frequency consistent?
- Are shares increasing?
Reading the Analytics Graph
Graph Elements
The analytics graph uses:- X-axis: Date (last 7 days)
- Y-axis: Count (views, published posts)
- Blue area: Views per day
- Purple area: Posts published per day
Interpreting Patterns
Spike in views after publishing
Spike in views after publishing
Normal pattern. New posts drive traffic:
- Initial spike when you publish
- Gradual decline over following days
- SEO traffic may build over time
Consistent daily views
Consistent daily views
Indicates:
- Steady audience
- Good SEO performance
- Evergreen content
Declining views
Declining views
May suggest:
- Need for new content
- Seasonal trends
- Changes in audience interest
Views without new posts
Views without new posts
Great sign! This means:
- Organic search traffic
- Social referrals
- Returning visitors
Privacy and Data Collection
Dyeink analytics are designed with privacy in mind:No Personal Data
We don’t collect names, emails, or IP addresses
No Cookies
Analytics work without tracking cookies
Aggregate Only
Only totals and counts are stored, no individual sessions
GDPR Compliant
Privacy-first approach meets data protection requirements
Comparing Metrics
Views per Post
To calculate average views per post:- 1,000 total views
- 10 published posts
- Average: 100 views per post
Share Rate
To calculate share rate:- 1,000 views
- 50 shares
- Share rate: 5%
A share rate above 2-3% is considered excellent. Most content has a share rate under 1%.
Common Analytics Questions
Why are my views lower than expected?
Why are my views lower than expected?
Possible reasons:
- New blog (SEO takes time)
- Not sharing on social media
- Infrequent publishing
- Niche topic with small audience
- Publish consistently (weekly or bi-weekly)
- Share posts on social media
- Optimize titles for search
- Write about topics people search for
Are bots counted in views?
Are bots counted in views?
Legitimate crawlers (Google, Bing) are filtered out. Only real page loads from browsers count as views.
Can I export analytics data?
Can I export analytics data?
Currently, analytics are view-only in the dashboard. Export functionality may be added in future updates.
How far back does historical data go?
How far back does historical data go?
- Graph: Last 7 days
- Totals: All-time since your blog was created
Why did my views drop suddenly?
Why did my views drop suddenly?
Common causes:
- Haven’t published recently
- Seasonal interest (holidays, events)
- Social media post no longer trending
- Search ranking changes
Tracking External Analytics
While Dyeink provides built-in analytics, you can also use external tools:Google Analytics
To add Google Analytics:- Create a Google Analytics account
- Get your tracking ID (e.g.,
G-XXXXXXXXXX) - Add it to your blog’s custom code section (if available)
External analytics integration may vary. Check with Dyeink support for current implementation options.
Other Tools
- Plausible - Privacy-focused alternative to GA
- Fathom - Simple, GDPR-compliant analytics
- Cloudflare Analytics - If using Cloudflare for DNS
Improving Your Metrics
Growing Views
Increasing Shares
Next Steps
Create Posts
Write content to drive analytics
Subscribers
Build an audience beyond page views
Custom Domains
Professional domains can improve click-through rates

