The gist
Lift is live: LinkedIn’s conversion lift is now generally available and easy to spin up.
B2B lift works: It is a data question, not a category question, when your audience density is high.
Think marathon: MMM, testing, and attribution each play a role across different time horizons.
Eyes on revenue: Today: conversion lift. Tomorrow: pipeline and revenue lift are on the roadmap.
How conversion lift works on LinkedIn
Conversion lift runs at the account level to answer one thing: did your LinkedIn ads cause more of the outcomes you care about? If your conversions flow through CAPI, you get richer reads. Budget guardrails keep the randomized split clean and statistically sound.
Setup is intentionally light; the more conversion types you send, the more nuance you get back. Early customers saw outsized gains, including thousands of incremental conversions and an 841% relative conversion lift.
Incrementality across a long B2B cycle
You will not pause go-to-market for nine months to “wait for science,” and you do not have to.
Test earlier outcomes now (qualified visits, high-intent content downloads, sales-accepted leads) and instrument how they move through pipeline, so you have a defensible bridge from early signal to closed-won.
Treat the toolkit like marathon training: reporting for daily direction, attribution for in-flight tweaks, randomized tests for causal proof, MMM for the long view.
The B2B myth that “lift tests do not work here” falls apart where professional density is high.
On LinkedIn, you can target by company, role, and seniority with adequate volume and clean design, randomized tests read.
Keep a ROAS mindset even for brand: whatever your leading metric, know how it ladders to revenue. Compete on share of voice with the exact accounts you must win so upstream gains foreshadow pipeline velocity and deal size, not just vanity awareness. Strong inputs matter: healthy CAPI, clean conversion taxonomy, clear test windows and exclusions.
Today’s read centers on conversion lift. The next horizon is mapping lift to pipeline contribution, sales velocity, and deal size.
What Jae Oh said (and why it matters)
General availability and timing
Jae underscored the moment: “More excitingly, conversion lift testing is actually now fully available.” That matters because causal reads are no longer a niche pilot. You can instrument them in your day-to-day.
The product’s core mission
He tied it back to business outcomes: “And if LinkedIn is a place where business happens, let’s make it easy for you to measure that.” Measurement is not an add-on, but ultimately how you defend budget and guide allocation.
Why incrementality belongs in the toolkit
“When it comes to: ‘Does marketing make an impact on my sales or outcome?’ Everything is incremental.” You may not test every move, but your spend should ladder to incremental impact.
On keeping perspective
Jae balanced the hype cycle: “It is not the single tool. Absolutely not.” Use testing alongside attribution and MMM so each method does the job it is built for.
Long-term brand effects
He reminded us why some impact shows up over years, not weeks: “You can’t associate Santa Claus and not red from Coca-Cola.” Plan for near-term reads without ignoring compounding brand equity.
From lift to revenue: Your next move
We covered how LinkedIn’s conversion lift works in a professional context and how to pair it with attribution and MMM to build a causal, long-range view of impact. Jae points to what is next: tying lift directly to pipeline contribution, sales velocity, and deal size.
Prioritize proof of impact with the audience you can actually reach on LinkedIn.
Prove it, then scale it.
