Why start with tracking instead of campaigns?

Because every decision after it inherits the error. Bad data doesn’t make you a little wrong, it makes you consistently wrong in a direction you can’t see.

Is a lower cost-per-lead always better?

No. Our own data across $11M+ in revenue found no relationship between cost-per-lead and profit. Optimizing for cheap leads can cancel the campaigns that were making money.

What budget do you work with?

We work best where there’s enough spend for real signal. If your tracking is broken, fixing it usually returns more than adding budget would.

Do you need access to our revenue data?

Yes, ideally. Optimizing to platform-reported conversions alone is how brands scale unprofitably. We tie spend to actual closed revenue.

Jump sections

Services / Paid Acquisition

Paid media is only as good as the data underneath it.

Every scaling decision you make is downstream of your tracking. If conversions are double-counted, misattributed, or lost to browser restrictions, you are optimizing toward a fiction — confidently, and at increasing cost. We fix the measurement layer first, then scale.

Let's build something

Fix the signal, then spend.

Browser pixels lose a meaningful share of conversions to ad blockers, privacy defaults, and cookie limits. The fix is server-side event tracking (CAPI) running alongside the pixel — and, critically, deduplication so the same purchase reported by both isn't counted twice.

Get this wrong and the platform learns from noise. We've audited accounts where tag containers fired duplicate conversions across multiple properties, inflating reported performance while real profitability quietly slid. On a recent retail build, server-side implementation reached 84% event coverage with deduplication verified — meaning the optimization signal going back to the platform was clean.

Raw events

Server-side events (CAPI)

Capture what the browser pixel loses.

Deduplicate

One purchase counted once, not twice.

Clean signal

The platform learns from truth, not noise.

Scale on cost per buyer

Spend against closed revenue and margin.

84% event coverage

Then optimize on the right number

Cost-per-click and cost-per-lead are convenient, not predictive.

Across 150+ campaigns and $11M+ in tracked revenue, we found cost-per-lead had effectively zero correlation with profitability. We optimize toward cost per buyer and contribution margin, which means connecting ad spend to closed revenue — not just to form fills.

84%

Server-side event coverage on a recent retail build, deduplication verified — clean signal to the platform.

$11M+

Tracked revenue across 150+ campaigns where cost-per-lead showed zero correlation with profit.

What we build and operate

Measurement first, then the channels on top of it.

Measurement infrastructure

Server-side events, clean GTM, deduplication, and offline conversion imports where the sale closes off-site.

Measurement infrastructure

Server-side events, clean GTM, deduplication, and offline conversion imports where the sale closes off-site.

Google

Search, shopping, feed optimization, and performance campaigns.

Google

Search, shopping, feed optimization, and performance campaigns.

Creative iteration

The variable that moves performance most once targeting is commoditized.

Creative iteration

The variable that moves performance most once targeting is commoditized.

Geographic and segment analysis

Finding the markets where the same spend converts better.

Geographic and segment analysis

Finding the markets where the same spend converts better.

Questionsbuyersask

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I've worked with Lightdrop on multiple projects over the last 5 years and am always amazed with the level of strategy, guidance and execution they bring to the table. Lior and his team are masters in digital and brand marketing.