Your LinkedIn Ads ROI is better than it looks

Why standard ROAS fails for LinkedIn Ads

The standard ROAS formula assumes revenue appears within thirty days of spend. In B2B SaaS that almost never happens. The form fill lands in week one, the SQL in month two, the opportunity in month four, and the revenue in months six to twelve. Industry data puts the average time from first LinkedIn impression to closed revenue at roughly two hundred and eighty days. Measured on a thirty-day window, even a program that ultimately returns five to ten times its spend will look like it is losing money. The calculation is not wrong; the timeframe is.

The cohort-based ROAS framework

The fix is to group leads by the month they were generated and measure the revenue that cohort produces at ninety, one hundred and eighty, and three hundred and sixty-five days. At thirty days you see form fills only and ROAS looks terrible, which is normal. By ninety days early SQLs appear and the trend becomes visible. One hundred and eighty days is the real indicator of program health, where a healthy program shows two to five times return. By three hundred and sixty-five days a strong program reaches five to ten times. Reading any single early window in isolation is how teams talk themselves out of a channel that works.

The formulas that matter

Three metrics tell the real story. Cost per pipeline dollar is ad spend divided by pipeline value attributed to LinkedIn, with a healthy target around ten to twenty cents on the dollar. Pipeline-to-spend ratio inverts that and should reach five to ten times by one hundred and eighty days. True cost per SQL is spend divided by SQLs, and what counts as good depends on deal size, since a fifty-thousand-dollar contract can comfortably absorb a far higher cost per SQL than a small one.

Why LinkedIn looks worse than Google, and usually isn't

LinkedIn carries a higher cost per lead than Google, often double, but the leads tend to carry three to five times the contract value. When you compare the two channels on cost per pipeline dollar rather than cost per lead, LinkedIn frequently matches or beats Google. The mistake that drives underinvestment is the metric mismatch: judging a high-intent, high-value channel by a top-of-funnel cost metric instead of by the pipeline and revenue it eventually produces.

Measuring it properly requires connected data

None of this works without infrastructure. You need conversion data flowing back to LinkedIn, a CRM tracking deal stages and revenue, and a way to connect ad spend to pipeline outcomes without rebuilding a spreadsheet every month. Puetto configures the tools, builds the automations, and runs the reporting that ties LinkedIn spend to closed revenue on a cohort basis, faster than a hire and more accountable than an agency.