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Marketing Performance

Platform, Activities, Artifacts and Performance Outcomes.

Measurement framework
Three tiers, each KPI tied to the process that moves it
Most marketing metrics measure individual catches. The real multiplier is the fish-ball effect — network effects that compound. Small fish attract big fish. Ecosystem health beats individual campaign performance.
Tier 1
Loop viability — can the loop sustain itself?
Tier 2
Loop efficiency — is it compounding faster than it costs?
Tier 3
Ecosystem health — is the fish-ball forming?

Tier 1 — Loop Viability​

These metrics answer one question: can the loop sustain itself? If any of these is missing or unmeasurable, fix that before optimising anything downstream.

Allowlist Inclusion Rate​

Allowlist Inclusion Rate ← allowlist-getting campaign + VI merchant profile completeness.

Of all active agent workflows operating in the target category, what percentage include this service on their Verifiable Intent L2 merchant-allowlist. This is the direct measure of the agentic-commerce thesis: being pre-authorized before the purchase cycle starts.

Harder to instrument than AI Citation Rate — no standardised tooling exists yet heuristic. Proxy signals while direct measurement matures: UCP registry inclusion status, inbound agent transaction volume through machine-readable endpoints, and principal-segment citation rate on AI surfaces that delegating consumers use to research services.

Define the measurement methodology before setting targets. The Onchain Analytics Lead is responsible for closing this gap.

Onchain CAC​

Onchain CAC ← AEO/AIO cycle + wallet onboarding flow.

The cost to acquire a verified wallet that completes a first transaction. This is a new metric — no industry benchmark exists yet. The process that moves it is AI citation rate driving discovery, followed by a frictionless wallet onboarding path.

See Customer Acquisition Cost for the traditional CAC model. Onchain CAC extends it with verified transaction proof rather than lead-form attribution.

AI Citation Rate​

AI Citation Rate ← AEO/AIO weekly cycle.

Pages cited in AI answer surfaces (ChatGPT, Perplexity, Gemini, AI Overviews) per month, growing month-on-month. This is a zero-click awareness metric: the buyer's question was shaped by AI before they ever typed a keyword. The process that moves it is the weekly SCAN→SCORE→CREATE loop run by the AEO/AIO Strategist.

Target: growing month-on-month heuristic. Absolute number depends on market size and topic coverage.

Agent Discovery Rate​

Agent Discovery Rate ← MCP / .well-known / UCP registration completeness.

The proportion of capable AI agents that can discover your service through machine-readable protocols. An agent that cannot find you through a protocol endpoint does not exist to agentic commerce buyers. The process that moves it is protocol registration hygiene: MCP server manifests, .well-known/agent.json endpoints, and UCP capability declarations.

This metric has no established benchmark. It is a binary precondition: either discoverable or not heuristic.

Tier 2 — Loop Efficiency​

These metrics answer: is the loop compounding faster than it costs to run?

CLTV:CAC Ratio​

CLTV:CAC (≥3:1 heuristic) ← loyalty programme design.

Customer lifetime value divided by acquisition cost. The 3:1 floor is a widely cited SaaS viability threshold [source: SaaS Capital benchmarks]. In agentic commerce, loyalty tokens change the numerator: a holder has economic skin in the network, compounding retention without incremental campaign spend.

See Customer Lifetime Value for the full calculation model.

Magic Number​

Magic Number (above 0.75 signals efficient growth heuristic) ← protocol integrations + enterprise sales velocity.

New ARR added per dollar of sales and marketing spend in the prior period. A Magic Number below 0.5 heuristic signals the loop is leaking. In agentic commerce, protocol integrations function as a distribution lever that reduces CAC for the next buyer cohort — a multiplier the traditional Magic Number does not capture.

See Magic Number for the calculation method.

Organic Growth Rate​

Organic Growth ← berley depth pages compounding over time.

Inbound traffic and leads generated without paid distribution. The process that moves it is content compounding: AEO-optimised depth pages cited across AI surfaces, linked from protocol documentation, and indexed by search engines. Organic growth is a lagging indicator — the signal that the berley trail is working.

See Organic Growth for measurement methodology.

Tier 3 — Ecosystem Health​

These metrics answer: is the fish-ball forming? Network effects are the hardest to build and the most durable once established.

Protocol Integration Count​

Protocol Integration Count ← partnership and ecosystem activity.

The number of live protocol integrations (x402, AP2, ACP, UCP, MCP, A2A) that route commerce through or to your service. Each integration functions as a distribution channel that requires no incremental marketing spend to activate. The process that moves it is the Partnership / Ecosystem Lead's activation cadence against ecosystem programs.

x402 as attribution rail — x402's primary marketing value is not as a payment channel but as an attribution rail: every on-chain x402 transaction is a verified conversion event, closing the attribution gap that plagues web2 marketing. 165M+ cumulative transactions processed as of April 2026 [source: Coinbase Developer Platform, April 2026]. Caveat: daily volume dropped 92% from the December 2025 peak of 731k/day to ~57k/day by February 2026, reflecting early bot-driven volume transitioning to organic demand [source: CoinDesk, March 2026]. Current adoption is strongest in API monetization and developer tooling, not consumer checkout.

Loyalty Token Volume and TVL​

Token Volume and TVL ← token economics design + loyalty programme execution.

Total value locked and transaction volume through the loyalty token programme. These are onchain, auditable, and compound: more holders means more liquidity means more utility means more holders. The process that moves it starts with the Token Economics and Loyalty Designer's incentive model.

Community Activation Rate​

Community Activation Rate ← DAO architect and community building.

The proportion of token holders or registered community members who take at least one governance or product action in a rolling 30-day window heuristic. A healthy activation rate sustains itself; a declining one signals the fish-ball is dispersing. The process that moves it is the Community / DAO Architect's weekly health loop.

New Instruments to Define​

Four KPIs in Tier 1 are measurement gaps in agent-native marketing. They do not yet have established benchmarks or standardised tooling:

Allowlist Inclusion Rate — the most strategically important gap. No direct tooling exists. Proxy through UCP registry status, inbound agent transaction volume, and principal-segment citation rate while the ecosystem builds direct measurement capability.

Onchain CAC — extends traditional CAC with verified transaction proof. Requires wallet attribution infrastructure live on day one. No industry benchmark exists.

AI Citation Rate — requires active AI surface monitoring across ChatGPT, Perplexity, Gemini, and AI Overviews. Tooling is nascent; most teams track this manually or with custom scripts. No standardised measurement tool exists.

Agent Discovery Rate — requires a complete audit of machine-readable protocol endpoints. The question of what "fully discoverable" means across all active protocols is still being defined by the ecosystem.

These are the highest-priority instrumentation gaps for any team entering agentic commerce. Define the measurement methodology before setting targets. The Onchain Analytics Lead role is responsible for closing these gaps.

Loop Gate​

Before any weekly reporting cycle closes, answer:

  1. What did the best piece this week teach us about the audience?
  2. What scored opportunity did we act on — and did the estimate hold?
  3. What signal did we miss that a competitor capitalised on?
  4. What goes into next week's SCAN as a result?

If these four questions have no answers, the measurement cycle was vanity, not learning.

Metric Depth​

Each KPI listed here has a dedicated page with calculation methodology and historical benchmarks:

Variation​

Benchmark targets vary by:

Context​

Questions​

If allowlist inclusion rate is the direct measure of the agentic-commerce thesis, what is the first proxy signal you could instrument this week before dedicated tooling exists?

  • Which of your Tier 1 metrics would change most if the majority of buyers in your category shifted from immediate mode (human confirms each transaction) to autonomous mode (agent acts within pre-set scope)?
  • At what point does allowlist placement compound faster than AI citation rate — and what would you measure to detect that crossover?
  • When onchain attribution is live from day one, which traditional marketing metrics become redundant?