Expertise · 02 / 06 · User Acquisition

Paid programs tuned to CAC payback

I run multi-channel acquisition across Google, Meta, LinkedIn and programmatic for B2B and fintech funnels, measured on cost per lead, cost per registration and a channel-level CAC audit.

See it at work → All workstreams →

Senior Marketing ManagerThinkingAI · 10 yrs in growth, 5 in B2B fintech

CAC-auditedfinance signs the definitions

LinkedIn CPL $300+ → ~$160PingPong, 2021–2023

Acquisition efficiencyaudited per channel 02

LinkedInenterprise segmentCPL ~$160

Googleregistration~$35

Metaretargetingscaled

ProgrammaticABM liststested

CAC, audited every dollar has a denominator

{ "workstream": "acquisition",
"channels": 4, "kpi": "payback" }

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+. At PingPong, as Marketing Manager for Ads & Lifecycle from 2021 to 2023, I ran the LinkedIn and Google ad accounts, bringing LinkedIn CPL to ~$160 and Google registration cost to ~$35, with 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

What goes into a paid program I run?

⚡

Channel strategy

✓ Multi-market paid media

✓ CAC · LTV/CAC · ROAS

✓ Bidding tightened, volume held

◎

Audience architecture

✓ Intent-signal segmentation

✓ A targeting brief per channel and region

✓ Keyword optimization

▲

Funnel & landing

✓ Ad-to-onboarding friction

✓ Landing pages matched to ad groups

✓ Qualification & routing

⚗

Testing & AI

✓ ICE/PXL test roadmaps

✓ AI creative analysis

✓ A readout closes every test

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.

I research keywords and intent for Google Ads, tear down competitor ads, and build LinkedIn audiences from my own segments. I write a targeting brief per channel and region, then build the campaign 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

I design messaging, landing paths, qualification logic and routing 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.

I match landing pages to LinkedIn and Google ad groups, agree qualification rules with sales, and wire routing into the CRM. Everyone signs one funnel spec: 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

I put creative, audiences, keywords, bidding and landing pages on one roadmap and score them with ICE and PXL before anything runs.

That loop cut LinkedIn CPL from $300+ to ~$160: I restructured campaigns, tightened audiences, optimized keywords, improved landing pages. I close each test with a readout on what moved and 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, with volume held. I keep a channel-level CAC audit running: every dollar has a denominator finance will sign.

Efficiency and volume have to hold together

CreativeOS: what I would build for that loop now (2025 demo) Acquisition efficiency, Google $90 → $35