Case 01 · Ripple · FinTech

An $18M+ pipeline engine for an enterprise FinTech.

Rebuilt LinkedIn and programmatic demand-gen from attribution up. Cut cost-per-lead by 58% while compressing average sales-cycle length.

Influenced pipeline
$18M+
Across 14 months, multi-touch attribution
CPL reduction
−58%
Inherited baseline vs. Q4 exit
Enterprise SQLs
312
Validated by sales, not marketing
Sales-cycle Δ
−22%
Cohort compression through content gating

The challenge

When I came in, Ripple's enterprise marketing team was generating leads, but the commercial team didn't trust them. Pipeline attribution was a hall of mirrors. LinkedIn reported one number, Salesforce another, and the finance team ignored both. Content was being gated aggressively, but ungated accounts were closing faster. The operator question was simple: what is the math actually doing?

What we built

We threw out the reporting cadence and rebuilt from the warehouse up. Segment into BigQuery into Looker, server-side events on every form, UTM-consistency enforced through a proxy layer. Once we could see true multi-touch on Salesforce opps, we could kill what wasn't working without second-guessing ourselves.

  • Rebuilt the LinkedIn account list with a 6sense intent overlay, focused 80% of spend on in-market 6QA accounts
  • Restructured content gating: top-of-funnel ungated, mid-funnel email-gated, bottom-funnel sales-gated
  • Shipped a budget-pacing script that redistributed weekly based on opp velocity, not click weight
  • Built a weekly commercial readout that went to the CFO, not the CMO
"We stopped marketing to leads and started marketing to accounts that close."

What happened

By month six, the sales team was voluntarily pulling our LinkedIn list into their outbound cadence. By month nine, finance was citing marketing-influenced pipeline in the board deck. By month fourteen, blended CPL was down 58% with a 3.2x lift in SQL to Closed-Won rate. The engine wasn't generating more. It was generating the right ones.

What stuck

The real deliverable wasn't the pipeline. It was the operating system. Two years later the same measurement architecture, pacing discipline, and commercial cadence are still running. The team hires against the system, not the campaigns.

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Have a similar problem?

If your pipeline-attribution picture looks fuzzy and your finance team doesn't trust the marketing numbers, let's talk.

↑↓ · ↵ · escBlake Burnett