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Marketing Performance Metrics

Marketing Performance

Platform, Activities, Artifacts and Performance Outcomes.

What We Measure

The berley framework changes what matters:

Traditional MetricFishing EquivalentWhat It Really Measures
CACCost per fishIs the berley efficient?
Conversion RateBite rateIs the hook emotional?
CLTVFish sizeAre we in the right waters?
TrafficFish in the areaIs the berley attracting?
RetentionFish returningIs the ecosystem healthy?

The insight: 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.

MetricBenchmark
Return on Investment (ROI)A positive ROI is generally considered good. Higher ROI means marketing efforts are more effective in generating income relative to cost.
Customer Acquisition Cost (CAC)Varies by industry. For SaaS, CAC should be recovered in less than 12 months of revenue from a new customer.
Customer Lifetime Value (CLTV)CLTV should be at least 3x your CAC for a viable business model.
Conversion RateAverage landing page conversion rate is around 2.35%, top 25% convert at 5.31% or higher.
Traffic-to-Lead Ratio2-5% is often seen as average.
Lead-to-Customer Ratio~20% is often seen as average, varies by industry.

Diagrams | Matrices | Thinkers

Common metrics used to judge the success of executing marketing strategy.

Content Strategy

  • Publications
  • Impressions
  • Conversions

AEO Signals

Traditional metrics measure catches. These measure whether the berley trail is compounding.

MetricWhat It MeasuresTargetWhy It Matters
AI citation ratePages cited in ChatGPT / Perplexity / AI Overviews per monthGrowing MoMAwareness before intent forms — the zero-click layer
Content opportunity conversionScored opportunities acted on vs total opportunities identified60%+Discipline: high-value gaps get created, not filed
Opportunity $ realisedRevenue attributable to content created from scored opportunitiesTrending up QoQCloses the loop between content investment and business outcome
Signal-to-calendar lagDays from signal identified to content published7 days or fewerSpeed of loop — slow loops lose kairos windows
Attribution depth% of content pieces with measurable downstream action (click, sign-up, reply)50%+Confirms berley is attracting, not just broadcasting

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.

Variation

Benchmark targets vary depending on:

Context

Questions

Which marketing performance metric — cost per qualified lead, berley trail conversion rate, or content compounding — best predicts whether a content marketing strategy will sustain growth at scale?

  • At what content volume does the berley trail produce enough inbound pull that outbound becomes unnecessary?
  • How do you measure the compounding value of a meta article versus a social post — and which investment returns more over 12 months?
  • Which marketing channel produces the highest quality leads for a crypto venture — community-led content, prediction-based thought leadership, or direct partnership?