Publish Everywhere. Measure Everything. Improve Automatically.
Smart scheduling posts to 8 platforms with optimal timing. Analytics collect performance at 1h, 24h, and 7d intervals. The feedback loop recalculates content bucket weights automatically.
Multi-Channel Publishing
One content brief becomes platform-optimized posts published across every channel your clients care about.
TikTok
X / Twitter
YouTube
Blog
Resilient Publishing Pipeline
A managed job queue handles the entire publishing workflow. Content is enqueued with platform-specific timing, retried on failure, and rate-limited to protect your accounts.
Each job carries the full context: content variant, target platform, UTM parameters, and scheduling metadata. The system processes thousands of publishing jobs per hour across all accounts.
Platform-Specific Timing
Each platform has different peak engagement windows. The scheduler optimizes independently for each one.
Queue Priority
Trending content gets priority scheduling. Evergreen fills remaining slots. Seasonal locks to calendar dates.
Rate Limiting
Respects platform API rate limits and posting frequency guidelines to avoid shadowbanning.
Retry Logic
Smart retry with exponential backoff. Failed posts are automatically retried up to 3 times.
Editorial Calendar
90-Day View
Full quarter planning with weekly and daily drill-down
80% Planned
Evergreen and seasonal content scheduled weeks in advance
20% Reactive
Reserved slots for trending topics detected by Discovery
Drag & Drop
Reorder and reschedule content with a visual calendar interface
90-Day View with Reactive Slots
Plan a full quarter of content while keeping 20% of slots open for trending topics that the Discovery Engine identifies in real time.
Evergreen and seasonal content fills the planned 80%. When a trending topic scores high, it claims a reactive slot and gets fast-tracked through production and distribution.
Full UTM Attribution
Every link published through Max Socials is automatically tagged with UTM parameters. No manual setup. No missed tracking. Complete attribution from impression to conversion.
utm_sourcePlatform (TikTok, Instagram, etc.)utm_mediumContent type (video, image, text)utm_campaignContent bucket nameutm_contentVariant ID for A/B trackingutm_termTopic keyword from DiscoveryExample Tagged URL
Performance at Three Intervals
Each published piece is monitored at three checkpoints, capturing progressively deeper insights.
1 Hour
Initial engagement metrics: early likes, comments, shares, and save rate
24 Hours
Full-day performance: reach, impressions, engagement rate, click-throughs
7 Days
Sustained performance: follower growth impact, conversion attribution, bucket scoring
Key Performance Metrics
Four core metrics tracked per content bucket, per platform, and per account.
Engagement Rate
Likes + comments + shares divided by impressions, segmented by platform and content type
Reach Efficiency
Impressions generated per dollar of production cost, measuring content ROI
Conversion Rate
UTM-tracked clicks that result in desired actions per content bucket
Bucket Score
Composite performance score for each content bucket, updated after every analytics cycle
The Feedback Loop That Never Stops Learning
Analytics do not just sit in a dashboard. They feed directly back into the Discovery Engine to continuously improve content strategy.
Publish
Content is distributed to target platforms with UTM tracking
Collect
Analytics are gathered at 1h, 24h, and 7d intervals
Score
Each content bucket's performance score is recalculated
Adjust
Discovery Engine re-weights topic scoring based on results
Improve
Next cycle's content briefs reflect what actually works
Connect Content to Revenue
Full UTM tracking connects every piece of content to downstream revenue events. Know exactly which content bucket, variant, and platform drives the most value.
- Track content production cost per asset
- Attribute conversions to specific content buckets
- Calculate return on AI-generated vs human content
- Report ROI per client with exportable dashboards
3.2X
Average ROI on AI content vs traditional
142%
Average engagement increase
$0.05
Average production cost per automated task
Distribution & Analytics FAQ
How does smart scheduling determine the best posting time?
The scheduler analyzes historical engagement data for each Account's audience on each platform. It identifies peak engagement windows and distributes content to maximize reach. The timing model updates weekly as new performance data arrives.
Can I manually override the AI's scheduling decisions?
Yes. The editorial calendar supports manual overrides for any scheduled post. You can drag and drop to reschedule, pause the queue for a specific channel, or force-publish content at a specific time. Manual overrides are tracked so the AI learns from your preferences.
How does the feedback loop actually improve content?
After each analytics collection cycle, bucket performance scores are recalculated. If a content bucket consistently outperforms expectations, its weight in the Discovery Engine increases, leading to more content briefs in that category. Underperforming buckets get deprioritized automatically.
What UTM parameters are tracked automatically?
Every published link includes utm_source (platform), utm_medium (content type), utm_campaign (bucket name), utm_content (variant ID), and utm_term (topic keyword). This provides full attribution from social impression through to conversion event.
Ready to Close the Content Loop?
See how automated distribution and analytics turn every post into a data point that improves the next one.
Close the Loop