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Analytics

Analytics in Influgen are organized around operator decisions, not vanity charts. The goal is to help you decide what to generate more of, where to publish it, and which characters deserve more credits.

Available analytics views​

The current analytics surface includes:

  • overview
  • engagement
  • content performance
  • audience
  • platform breakdown

These endpoints share a common date-range system and can be scoped to a specific character.

Date filtering​

Analytics queries accept:

  • characterId or character_id
  • dateFrom or date_from
  • dateTo or date_to

If you do not pass a range, Influgen defaults to the last 30 days.

[screenshot: Analytics dashboard with overview cards, engagement trend chart, platform breakdown bars, and credit usage strip]

What to watch first​

For most teams, these metrics matter most:

  • engagement rate
  • content type performance
  • platform contribution
  • follower growth
  • credit efficiency by character

Do not optimize for output volume alone. A character that burns credits fast but produces weak engagement is not actually efficient.

How to use analytics operationally​

  • Increase content volume only after the strongest content types are clear.
  • Compare Instagram and TikTok performance separately instead of averaging them together.
  • Use audience view to check whether the character is attracting the intended niche.
  • Use content-performance view to identify repeatable prompt patterns.

Cache behavior​

Analytics responses are cached briefly on the private edge for faster dashboard loads, so you get responsive charts without sacrificing per-workspace isolation.