Social Media Marketing Simulation — Content Mix & Posting Cadence

Content Type

Campaign Settings

Posting frequency 7 / week

Audience size 260 users

Campaign Status

Day 0 — campaign launched.

Reach

0.0%

Engagement rate

0.0%

Brand awareness

Est. sales

Unaware Aware Engaged Fatigued

How it works

Followers sit on a small-world graph in 3D (a few nearest-neighbour links plus a handful of long-range "shares" — the same topology real information cascades travel on). Each user is in one of four states:

Unaware → Aware → Engaged
              Aware/Engaged → Fatigued → (slow recovery) → Unaware

Every simulated day, if a post fires, a direct-follower slice is exposed with probability p = openRate · Q, where Q is the content-type's quality multiplier (Video 0.90, Image 0.70, Story 0.60, Text 0.45). Awareness then spreads edge-by-edge:

P(U → A) = β · Q · (1 − fatigue_j)   for each aware/engaged neighbour
P(A → E) = γ · Q · (1 − fatigue_i)
P(A/E → F) = k_f · fatigue_i          (oversaturation)
fatigue(t+1) = fatigue(t) · decay + exposureGain

Posting too rarely leaves reach flat; posting too often pushes fatigue up faster than engagement, so a chunk of the audience burns out into the fatigued state before it converts — the classic marketing trade-off between cadence and audience fatigue. Estimated sales accumulate a fraction of every Aware→Engaged conversion, scaled by content quality.

Content type — sets the quality multiplier Q used in every transition above.
Posting frequency — posts per simulated week; higher values speed up reach but also fatigue.
Audience size — rebuilds the follower network at a new size.

Day 0

Your brand account Follower network

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