ELI RESEARCH

AI search to revenue benchmark: separate visibility from business evidence

Recommendation, referral, demo and closed revenue are distinct evidence stages.

Five-rung evidence ladder — no percentages
Research in progress

No public AI-to-revenue benchmark yet. No conversion averages are invented.

RELEASE STANDARD

Methodology is publishable before findings are.

Eli can publish the question universe, schema, definitions and quality controls before a benchmark release. It will only publish an aggregate when the underlying observations are complete, reviewable and described with their coverage and limitations. Until then, this page makes no performance, ranking or customer-outcome claim.

Evidence layers

AI answer proves visibility; referral supports direct attribution; website action proves conversion; CRM needs identity/join logic; revenue requires confirmed business system evidence.

Future design

If data exists, publish AI referral to qualified action/opportunity, AI-influenced opportunity, time to conversion and stage differences with denominators/attribution rules.

Why separate

Dark funnel and multi-touch make perfect attribution impossible. Evidence tiers prevent one score from claiming too much.

FAQ

Questions about the research design and release boundary.

How much converts?

No universal number without dataset.

Revenue measured?

Partially through referral, website and CRM evidence.

Buyer-reported valid?

Supportive, not perfect.

Prompt to revenue?

Only instrumented cases.

Why layers?

Each proves different thing.

CONNECT YOUR WEBSITE

Connect AI visibility to revenue evidence

The Eli AI Search to Revenue Benchmark separates AI-answer visibility, referral evidence, website action, CRM opportunity and revenue. Results publish only with sufficient real permissioned downstream data.

Connect AI visibility to revenue evidence