A practical marketing cohort analysis framework for comparing customers by acquisition period and channel, then using retention, revenue, payback and lifetime value to make better budget decisions.
A practical framework for turning revenue and growth objectives into a marketing KPI tree with measurable outcomes, leading indicators, channel actions, owners and decision thresholds.
A practical framework for turning technical SEO findings into revenue ranges, implementation requirements, opportunity cost and engineering tickets that earn credible stakeholder support.
A practical model for measuring whether digital PR creates SEO value: assess link quality and relevance, track rankings and branded search, isolate qualified traffic, and connect earned coverage to pipeline without overstating attribution.
A practical framework for making content, images, video, product data and structured information easier to discover across traditional search, visual search, voice interfaces and AI assistants.
A practical operating framework for turning scattered AI prompts into a governed marketing asset: organised by workflow, documented with clear inputs and outputs, tested through version control, measured for quality and connected safely to automation.
A practical operating framework for requesting, monitoring, responding to and learning from customer reviews across one or many locations—without turning the process into a generic automation exercise.
A practical framework for creating an SEO service-level agreement that defines scope, response times, client responsibilities, approvals, escalation and reporting—without making ranking promises.
A repeatable SEO website QA checklist for pre-release and post-release checks, with clear owners, severity levels, validation evidence and rollback triggers.
A practical framework for AI search referral tracking that connects identifiable AI traffic, ambiguous attribution, assisted conversions, CRM outcomes and revenue quality.