User Acquisition: Tuned to CAC Payback

The framework

Demand first,
then efficiency

01 · Map demand & intent

I start with the demand map: what people actually search, how competitors position, how the ICP behaves in each region. Spend waits until that picture exists.

Concretely, that's keyword and intent research for Google Ads, competitor ad teardowns, and segment definitions that become LinkedIn audience architecture instead of platform defaults. The output is a targeting brief per channel and region, and the campaign gets built from it.

The targeting brief exists before the campaign does

AdRadar: competitor ad intelligence Keyword research for fintech, intent mapping in practice

02 · Architect the funnel

Messaging, landing paths, qualification logic and routing get designed as one system, because CAC quality is decided after the click as much as before it. I walk the whole path from ad to onboarding and fix friction before spend scales.

In practice: landing pages matched to LinkedIn and Google ad groups, qualification rules agreed with sales, routing wired into the CRM. The artifact is a funnel spec everyone signs: what a qualified lead is, where it goes, how fast.

CAC quality is decided after the click too

Global web & tracking, landing paths and lead flow Marketing ops: routing and qualification logic

03 · Run structured experiments

Creative, audiences, keywords, bidding and landing pages all go on one roadmap, prioritized with ICE/PXL. Tests get judged on downstream activation and revenue.

This is the loop that cut LinkedIn CPL from $300+ to ~$160: campaign restructuring, audience refinement, keyword optimization, landing improvements. Each test ships with a readout: what moved, what didn't, what runs next.

Judge tests on revenue

Acquisition efficiency: CPL $300 → $160 case Landing page testing, how I prioritize

04 · Optimize efficiency at scale

Once winners are clear, I tighten bidding logic, feed quality signals back to the platforms, and cut spend that isn't earning its keep. AI speeds up creative analysis and segmentation so the loop runs weekly.

Google registration cost went from $90+ to ~$35 this way, with volume held. The standing artifact is a channel-level CAC audit, where every dollar has a denominator that finance will sign.

Efficiency has to hold while volume does

CreativeOS: AI in the creative loop Acquisition efficiency, Google $90 → $35

Paid programs I have run across four channels:

⚡

Channel strategy

✓ Multi-market paid media

✓ CAC · LTV/CAC · ROAS

✓ Budget & bidding logic

◎

Audience architecture

✓ Intent-signal segmentation

✓ ICP & regional variants

✓ Keyword optimization

▲

Funnel & landing

✓ Ad-to-onboarding friction

✓ Landing improvements

✓ Qualification & routing

⚗

Testing & AI

✓ ICE/PXL test roadmaps

✓ AI creative analysis

✓ Cohort-level readouts

What I buy and measure with:
channels, bidding and attribution

Ad
platforms

Google Ads

Meta Ads

LinkedIn Ads ⇄Programmatic / Display

Measurement

GA4

Looker Studio

Amplitude ∑LTV / CAC / ROAS models

Tracking &
attribution

⌁UTM governance ☲Cohort analysis ▤Channel-level CAC audit

AI in
the loop

✦Creative analysis ✧Segmentation enrichment ◆Efficiency optimization

Proof

Cost per lead nearly halved, with the channels still full

Paid channels were scaling spend faster than pipeline: LinkedIn leads cost $300+, Google registrations $90+. Campaign restructuring, audience refinement, keyword optimization and landing improvements brought LinkedIn CPL to ~$160 and Google registration cost to ~$35, with volume held, and every dollar of CAC auditable by channel.

Read the full case ›

LinkedIn Ads · Google Ads Instrumented per channel

~$160 LinkedIn cost per lead, down from $300+. Google registrations $90+ → ~$35