// What I do
Your metrics show what happened.
They rarely show why.
Your list looks healthy. Open rates hold. Yet the people behind the numbers keep drifting — engaged buyers quietly going quiet, fresh sign-ups already half-disengaged, segments rotting under a stable headline figure. The dashboard can't see it. I work with established senders to find the audience drift and list-quality erosion underneath the reporting, and to turn that into decisions. Start with the Audit, or pick the one problem that's biting.
The Email Intelligence Audit
This is blind flight: the reports show what happened, rarely why. The Audit is a fixed-scope, tool-supported diagnosis that reads across the layers most reporting keeps separate — list health, engagement behaviour, deliverability, content, and the AI-readiness of the data underneath. It optimises for audience state change, not campaign metrics. The output isn't a prettier dashboard. It's a decision you can defend, with the evidence attached and the next moves ranked.
What's Included
- ✓A five-layer read — list, engagement, deliverability, content, data foundation — connected, not siloed
- ✓Audience-drift and list-quality diagnosis: who is quietly disengaging beneath a stable headline number
- ✓Deliverability checked as a cause, never assumed away
- ✓AI-readiness of the data foundation — because AI won't fix shallow email data, it will only scale shallow decisions
- ✓A prioritised roadmap you own and can act on without me
- ✓Format: fixed-scope engagement, tool-supported
Who It's For
Established, data-rich senders whose numbers have moved and whose dashboards can't say why. If you suspect the problem sits underneath the reporting, this is the place to start.
Growth Experimentation
A test that isn't sized proves nothing, however clean the chart looks. I help teams prove causation rather than narrate coincidence: size the test on the right denominator, read significance honestly instead of stopping the moment the line tips, and build a testing rhythm that compounds rather than restarting from zero each quarter. The point isn't more tests. It's tests that change what you do next.
What's Included
- ✓Experiment design sized on the correct denominator, not guesswork
- ✓Honest significance reading — no peeking, no stopping early because the line looks good
- ✓A testing rhythm where each result feeds the next
- ✓Hypotheses tied to audience behaviour, not surface metrics
- ✓Format: project or ongoing — sorted in the call
Who It's For
Teams who already run tests but end up arguing about the results. If your last experiment ended in a meeting rather than a decision, that's the gap to close.
Data That Drives Decisions
Most organisations don't lack data. They lack the layer between the raw event stream and the decision a human has to make on Monday. I build that layer: KPI frameworks that map to choices rather than to charts, analytics people trust enough to act on without an analyst in the loop, and pipelines that hold up when the volume grows and the schema shifts. The measure of success is simple — fewer decisions waiting on someone to pull a number.
What's Included
- ✓KPI frameworks tied to decisions, not vanity charts
- ✓Analytics people trust without an analyst-in-the-loop
- ✓Pipelines that hold up as volume and schema change
- ✓The translation layer from raw event data to the call being made
- ✓Format: scoped to the problem — agreed in the call
Who It's For
Organisations rich in data and poor in intelligence. You have the reports; what you're missing is the confidence to decide from them.
// Ready to start?
Stop optimising subject lines when the real problem is audience drift.
Tell me where the numbers moved and which way. A click rate that slid two quarters running. A re-engagement flow that used to work. A segment you can't explain. We'll start there, on a call, and work out which of these is actually worth your money first.