Real traffic & ad estimator

1. Definitions

Let’s define the numbers you already have:

Variable	Meaning
CF_uv	Cloudflare unique visitors (all IPs, bots + humans)
CF_req	Cloudflare total requests
Mat_uv	Matomo unique visitors (JS-enabled humans)
Mat_pv	Matomo pageviews
bot_factor	Estimated % of Cloudflare traffic that is bots (0–1)
JS_factor	Fraction of real humans that trigger Matomo/JS (0–1)

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2. Step 1: Estimate human visitors from Cloudflare

$$Humans_{CF} = CF\_uv \times (1 – bot\_factor)$$

HumansCF​=CF_uv×(1−bot_factor)

• Example: bot_factor = 0.98 (98% bots)

$$Humans_{CF} = 2{,}580{,}000 \times (1 – 0.98) = 51{,}600$$

HumansCF​=2,580,000×(1−0.98)=51,600

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3. Step 2: Adjust Matomo for JS undercounting

$$Humans_{real} = Mat\_uv / JS\_factor$$

Humansreal​=Mat_uv/JS_factor

• Example: JS_factor = 0.05 (only 5% of humans trigger JS)

$$Humans_{real} = 2{,}509 / 0.05 \approx 50{,}180$$

Humansreal​=2,509/0.05≈50,180

✅ Notice this roughly matches the Cloudflare-estimated human count.

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4. Step 3: Estimate real ad impressions

If your ad triggers on each pageview:

$$AdImpressions_{real} = Humans_{real} \times AvgPagesPerHuman \times AdEngagementFactor$$

AdImpressionsreal​=Humansreal​×AvgPagesPerHuman×AdEngagementFactor

• AvgPagesPerHuman ≈ Mat_pv / Mat_uv = 5,769 / 2,509 ≈ 2.3
• AdEngagementFactor = fraction of pages where ad is actually viewed (0–1), e.g., 0.5

$$AdImpressions_{real} = 50{,}180 \times 2.3 \times 0.5 \approx 57{,}700$$

AdImpressionsreal​=50,180×2.3×0.5≈57,700

• Compare to Cloudflare requests (8.3M) — huge difference because most requests are bots or non-engaged humans.

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5. Step 4: Optional shortcut formula

$$AdImpressions_{real} \approx Mat\_uv \times \frac{1}{JS\_factor} \times \frac{Mat\_pv}{Mat\_uv} \times AdEngagementFactor$$

AdImpressionsreal​≈Mat_uv×JS_factor1​×Mat_uvMat_pv​×AdEngagementFactor

• Only requires Matomo numbers + your estimate of JS coverage + ad view factor.
• No need to deal directly with raw Cloudflare numbers unless you want bot analysis.