Agency Benchmarking

Compare AI-generated campaign output with real agency work, then use blind scoring to decide what can safely move in-house.

Decision frame

When does routine campaign work move in-house?

Use blind scoring to decide which campaign types are ready for AI production, while the agency stays focused on higher-value creative and strategy.

Evidence
Generate a challenger
Rule
AI >= agency ship-rate
Scale path
Archive wins into Knowledge Repo
Agency baseline

Real agency deliverable to benchmark against

Choose the agency baseline before generating the AI parallel version.

Performance projection

Projected performance — AI vs Agency

Hypothetical email performance as more historical campaign content is loaded into the Knowledge Repository. The agency is a fixed baseline; the AI improves as it learns from your archive.

Illustrative projection for the narrative, not measured data.

Learning agent output

Performance Learning Agent

Converts benchmark scores and campaign metrics into reusable recommendations for the next brief.

Concrete outcome subjects beat feature-led subjects

Rank subject lines that name cost, downtime, or risk reduction above generic product claims.

CTA should follow persona intent

Default to Book a demo for IT buyers, but offer Get printer details for procurement variants.

Compliance-safe proof improves launch speed

Attach proof/disclaimer language during generation, not at final review.

Historical email campaigns loaded into Knowledge Repository: 7 · today
0 (cold start)60+ (mature archive)
Open rate
Agency22.00%
AI19.96%
Agency ahead (-2.04 pts)
Click-through rate
Agency2.80%
AI2.37%
Agency ahead (-0.43 pts)
Conversion rate
Agency1.00%
AI0.89%
Agency ahead (-0.11 pts)
Unsubscribe rate
Lower is better
Agency0.40%
AI0.84%
Agency ahead (+0.44 pts)

All metrics shown as %. For unsubscribe rate, lower is better — a shorter AI bar is the win.

AI overtakes the agency on conversion at ~11 historical campaigns — and keeps unsubscribe lower from there on. Every campaign you archive into the Knowledge Repository moves the in-house line further past the agency, which is how routine work shifts from agency to AI over time.