AI in marketing.

Evaluate content and campaign agents through quality, qualified interest, and downstream outcomes.

Example workflow

Where agents work.

Campaign planner: Drafts campaign briefs, defines target audiences, and suggests channel mix from historical performance.
Audience builder: Generates segments from CRM and product-usage data and flags segment drift for rebuilds.
Attribution agent: Reads campaign and pipeline data and attributes revenue across touches by channel.
Creative drafter: Writes ad copy, landing-page variants, and email sequences tied to a campaign brief and target audience.
Lead-quality watchdog: Monitors MQL to SQL conversion by source and flags sources where lead quality degrades.

Pipeline-influenced revenue: Revenue from cycles the agent's campaigns or audiences touched.
Campaign cycle time: Median time from brief to live versus team baseline.
MQL → SQL conversion: Lead quality on agent-built versus human-built segments.
Override rate: Frequency of marketer rewrites of agent output.
Spend efficiency: CAC delta on agent-allocated channels versus baseline.

Measurement depends on your source records and mapping. These are signals to evaluate, not automatically collected metrics.

Source coverage and outcome attribution depend on the records you provide.

We’ll review your source data and agree what to measure.