RESOURCES · Overview · White Paper · Evidence Methodology · Case Studies · Test Deployments · Current Thinking · FAQ
Case Study · 60 days
DTC e-commerce: +42% checkout completion
Measured over 60 days in a live client deployment: +42% checkout completion, +33% repeat buyers, 35% less reporting time and 28% 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
DTC fashion and lifestyle e-commerce · 35 employees · North America · direct-to-consumer model.
Challenge
The client had high cart abandonment, rising acquisition cost, creative fatigue and fragmented ROI reporting.
Applied work
Purchase-intent scoring, AI-assisted content, cart-recovery workflows, ad-spend optimization and a unified Shopify/Klaviyo/GA4/Meta view.
Measured outcomes
+42% checkout completion · +33% repeat buyers · 35% reduction in reporting time · 28% lower CAC.
Evidence boundary
Results were measured over a 60-day window in one client deployment. They have not been independently audited and do not include enough attribution detail to generalize beyond this deployment.
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.
STRATEGIC DILIGENCE · Technology → Architecture → Evidence → Deployment → Leadership
