Ad Targeting & Channel Fit Simulator

Targeting & Message

Targeting precision 50%

Message–audience fit 60%

Channel budget mix

Social40%

Search35%

TV25%

Total budget $30,000

Adjust the controls, then launch.

Results

Reach

Conversion rate

Conversions

ROAS

0.0x

How it works

900 audience agents sit in a 2D preference space: horizontal position is channel affinity (which of the three channels reaches them) and vertical position is need level for the product, centred on the core segment at 0.

reach(agent)   = channelShare(chan) × (1 − e^(−budget / 40000))
relevance(y)   = fit × exp( −y² / (2σ²) ),  σ = 0.9 − 0.75 × precision
exposed        = random() < reach(agent)
converts       = exposed && random() < relevance(y)
ROAS           = (conversions × $80) / budget

Targeting precision shrinks σ, the width of the interest window the message is tuned for — high precision means only agents close to the core need level convert well, but those who do convert at a much higher rate.
Message–audience fit is a flat multiplier on conversion probability — a better-written, better-designed ad converts more of whoever it reaches, regardless of targeting.
Channel budget mix sets what share of each channel's audience actually sees the ad (channelShare = that channel's slider ÷ sum of all three).
Total budget drives reach through diminishing returns: doubling spend does not double reach once a channel is close to saturated.

The gap between broad-and-shallow (low precision, wide reach, low conversion rate) and narrow-and-deep (high precision, small reach, high conversion rate) campaigns is the real trade-off every media planner navigates.

SocialSearchTV

Unreached Exposed Converted

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