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Case Study · 90 days
Sustainable manufacturing: +32% qualified leads
Measured over 90 days in a live client deployment: +32% qualified leads, +21% opportunity-to-win ratio, 40% faster reporting and 18% lower CAC. The client’s name is withheld at their request. Results are specific to this deployment and are not a benchmark, forecast or guarantee.
Context
B2B sustainable-film manufacturer serving packaging and agriculture · company size withheld · Canada · manufacturing business model.
Challenge
The client faced unqualified distributor inquiries, rising CAC as traditional outreach lost efficiency, limited purchase-intent visibility and multi-week reporting delays.
Applied work
Digital-funnel and SEO audits, predictive lead scoring, Google and LinkedIn optimization, technical content, KPI guardrails and unified analytics/reporting across identified campaign data sources.
Measured outcomes
+32% qualified leads · +21% opportunity-to-win ratio · 40% faster reporting · 18% lower CAC.
Evidence boundary
Results were measured over a 90-day window in one client deployment. They have not been independently audited and do not include enough attribution detail to establish a general causal benchmark. Statements about predictive intent, shorter sales cycles, dynamic budget shifts or real-time operation should therefore be read as deployment-specific implementation descriptions, not universal performance claims.
HOW TO READ THIS CASE
Measured results through the mAI operating model
This case reports results from one live client deployment. The stated context and measured outcomes remain the evidence boundary; the mAI operating model below provides a consistent way to inspect how the work maps to marketing operations without extending those results.
PLAN
Define the operating problem, business context, constraints, baseline and KPI contract.
EXECUTE
Apply the deployment’s workflows, channels, content, scoring or integrations under human oversight.
MEASURE
Read the measured metrics against the stated window and the stated limitations.
OPTIMIZE
Use measured signals to refine approved actions without treating deployment-specific results as universal benchmarks.
P² EVIDENCE VIEW
Productivity + Precision
Productivity signals include operating effort, reporting time, workflow speed or automation coverage when the deployment measured them. Precision signals use the business KPI measured in this case. Neither dimension should be generalized beyond the evidence provided.
HUMAN COMMAND
Governed interpretation
Strategy, audiences, budgets, brand-critical content, privacy, compliance and material policy decisions remain subject to defined human approval. Evidence classification and claim boundaries are part of that governance layer.
EVIDENCE STATUS
This page is a case study from a live client deployment. Its outcomes were measured in that deployment, and the client’s name is withheld at their request. Read the results with the stated context and boundaries, not as a forecast or guarantee.
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