Marketing teams are choking on attribution models. But the real problem is simpler: you and leadership can't agree on what "proof" even looks like.

62% of organizations have different definitions of qualified leads. MIT found a 95% failure rate for AI projects not showing measurable returns within six months. 70% of B2B marketers are under pressure to prove ROI right now.

The pressure isn't coming from bad data. It's coming from misaligned expectations.

I got my hands on internal docs from teams that just secured 20-40% budget increases. Here's what separated them: they stopped arguing about attribution and asked one question.

"What would good enough proof look like to you?"

Not perfect proof. Good enough proof.

Your CEO doesn't want a 47-slide deck on multi-touch attribution. They want to know: is this worth the money?

If you can't agree upfront on what would convince them, you'll never convince them.

2026 is the year of the ROI reckoning. Marketing budgets are flat at 7.7% of revenue. 59% of CMOs don't have enough budget to execute their strategy. Board pressure is up 21%, CFO pressure up 52%.

53% of investors now expect positive ROI from AI in six months or less.

But AI ROI is harder to prove. You can't point to a direct conversion from an AI-written email. AI amplifies everything, making attribution murkier.

Marketing shows data. Leadership wants more. Marketing shows better data. Leadership still isn't convinced. Budgets get cut.

The teams winning stopped playing this game. They defined the rules first.

Tier 1: Weak Proof

Time saved, process improvements, team sentiment, usage metrics.

Your baseline. But if you ONLY show this, you're vulnerable. "We're using it" doesn't mean "it's worth the cost."

Tier 2: OK Proof

Cost comparison, quality scores, error reduction, output volume increase.

Where most teams stop. Enough to renew a contract, not enough to increase budget. You're proving efficiency, not impact.

Tier 3: Strong Proof

Direct revenue attribution, pipeline velocity, CAC reduction, LTV increase, market share gains.

This gets you promoted. It connects spend to business outcomes.

The critical move: Don't start by gathering Tier 3 proof. Ask leadership which tier they need to see first.

Team A (SaaS, $8M): Spent three months building multi-touch attribution. CEO said: "Can you just show me if AI leads close at the same rate?"

Tier 3 data, Tier 2 proof needed. Three months wasted.

Team B (Ecommerce, $22M): Asked CFO: "What would we need to show you?"

CFO: "Better ROAS over 90 days."

Ran the test. AI: 4.2:1 ROAS. Traditional: 3.1:1. Approval in one meeting. Budget up 35%.

Team C (B2B, $12M): Asked CEO: "What proof do you need for a 20% budget increase?"

CEO: "Deals close 15% faster, CAC doesn't go up."

Built measurement around those two metrics. Six months: deals 18% faster, CAC down 8%. Got 20% plus an additional 15%.

The pattern is clear. The teams that secure budget increases don't start by building measurement systems. They start by defining what proof their decision-makers actually need.

Perfect attribution doesn't exist. Multi-touch models are guesses. AI ROI is hard to isolate.

None of that matters if you can't agree on proof standards upfront.

The fastest ROI improvement isn't better tracking. It's better alignment.

You're about to get the complete implementation:

This is where proof theory becomes budget approval.