01
Baseline
Paid lead share, non-brand traffic, CAC, conversion, AI mentions and technical position before work begins.
PROOF, NOT THEATRE
Case studies should prove. Not decorate.
This page publishes only verifiable outcomes: baseline, work completed, period, metrics and limitations. No invented numbers to fill a layout.
PROOF POLICY
From paid dependency to measurable owned demand.
Every case is documented with context, what changed, what did not change and how each metric was calculated. If a source, period or definition is missing, the number does not become marketing.
02
Interventions
SEO, content, citations, digital PR, CRO, CRM and automation described without arbitrary attribution.
03
Period
Declared measurement window, seasonality and relevant external changes needed to interpret the result.
04
Outcome
Pipeline, blended CAC, revenue contribution and reduced dependency with an explicit measurement method.
If a number cannot be traced to a source, a period and a definition, it does not become a claim.
BaselineA documented starting point.
MethodClear interventions and measurement logic.
EvidenceVerifiable outcomes rather than isolated vanity metrics.
FAQ
How we publish evidence
Credibility matters more than a spectacular number without context.
Why not publish demonstration figures?
Because an invented case study destroys the credibility it is meant to create. Data is published only when evidence exists and disclosure is permitted.
How do you attribute a result?
We separate correlation from attribution. Where attribution is imperfect, we say so and use multiple signals rather than assigning everything to one channel.
Which metrics matter most?
Pipeline, CAC, non-brand demand, conversion and paid dependency. Rankings and traffic are useful, but do not describe economic impact on their own.
Build a system that keeps working when ad spend stops.
We start with demand, current visibility and the bottlenecks limiting organic growth and conversion.