Free tool

Google vs Meta vs LinkedIn Budget Split Calculator

Decide where a first paid-media budget should go. Enter your monthly budget, conversion value, margin, and platform assumptions to get a clean starting split across Google, Meta, and LinkedIn.

Inputs

$

Total spend you want to divide across Google, Meta, and LinkedIn.

$

Revenue per lead, order, signup, or booked call.

%

Used to estimate real profit, not just revenue.

Platform assumptions

Google Ads
$
%
Meta Ads
$
%
LinkedIn Ads
$
%

Recommended split

Best first channel
Meta Ads

Meta Ads has the strongest expected gross profit per dollar. The split still keeps budget across all viable channels so you can collect comparative signal.

Projected revenue
$2,699
Projected net profit
$215
Blended ROAS
2.70×
Blended CPA
$66.69

Google Ads

$436 allocation, 43.6% of budget

$1.30 gross profit per $1
Clicks
175
Conversions
7.0
CPA
$62.50
ROAS
2.88×

Meta Ads

$455 allocation, 45.5% of budget

$1.35 gross profit per $1
Clicks
379
Conversions
7.6
CPA
$60.00
ROAS
3.00×

LinkedIn Ads

$109 allocation, 10.9% of budget

$0.32 gross profit per $1
Clicks
15
Conversions
0.4
CPA
$250.00
ROAS
0.72×

How the split is calculated

The math rewards platforms with the strongest expected gross profit per dollar, then turns that into a practical testing mix.

Intent, interest, and identity

Google is strongest when search intent already exists. Meta is strongest when creative can create interest or retarget visitors. LinkedIn is strongest when job title, company size, or industry matters more than cheap clicks.

Profit per dollar

The calculator converts CPC, conversion rate, order value, and margin into expected gross profit per ad dollar. That is usually more useful than allocating by gut feel or last-click platform preference.

Blended testing

Even when one platform looks best, a first budget should usually keep some spend across the other viable channels. You need comparable signal before you crown a winner.

Break-even discipline

If every platform is below break-even, the answer is not to force a bigger launch. Tighten the offer, landing page, audience, or creative before scaling the budget.

A better first-budget rule

Most teams split budget by confidence: 60% to the platform they know, 30% to the platform they are curious about, and 10% to the one someone mentioned in a meeting. That can work by accident, but it ignores the only question that matters: how much gross profit should each dollar create?

Use Google when people are already searching for the problem. Use Meta when the offer is visual, broad, or strong for retargeting. Use LinkedIn when the buyer is defined by company, role, or industry and the conversion value can absorb a higher click cost.

For a deeper strategy view, read our guide to Google Ads vs Meta Ads vs LinkedIn Ads.

How AdFlint uses this idea

AdFlint launches campaigns across Google, Meta, and LinkedIn from one dashboard, then watches the actual platform data. The starting allocation is only the beginning: spend can move toward the channel that is producing better clicks, conversions, and pacing.

Questions

How should I split budget between Google, Meta, and LinkedIn?

Start with your economics, not a fixed rule of thumb. Google usually captures active demand, Meta creates or retargets demand, and LinkedIn is best for higher-value B2B audiences. This calculator weighs each platform by estimated gross profit per dollar using CPC, conversion rate, value, and margin assumptions.

Should Google Ads always get the biggest budget?

No. Google often deserves the first test when people are already searching for what you sell, but it can be expensive or too small if demand is limited. Meta may win for ecommerce and broad consumer categories, while LinkedIn can win when a single B2B lead is worth enough to justify a higher CPC.

What numbers should I enter if I have no campaign history?

Use conservative assumptions, then treat the output as a testing plan. Estimate CPC from keyword tools or platform benchmarks, use a low conversion rate, and enter the real value and gross margin of the outcome. After the first week, replace assumptions with actual CPC and conversion data.

Does this replace ad platform optimization?

No. It gives you a rational starting split and a way to sanity-check channel economics. Live campaign optimization still needs actual performance data, creative testing, targeting changes, and pacing controls.

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