AH

How I work

See how I work

I work best where the problem is messy, the evidence is scattered, and the obvious answer is probably wrong.

My work sits somewhere between UX research, strategic diagnosis, content clarity, interface critique, and commercial common sense. I help teams understand why something is not working, what evidence supports that, and what to do next without turning the whole thing into a 90-slide fog machine.

I am useful when you need someone to look across the page, the journey, the offer, the data, the customer expectation, and the business reality — then tell you plainly where the thing is breaking.

I do not start with assumptions

I start by looking at what is actually happening.

That might mean reviewing analytics, heatmaps, recordings, user feedback, search behaviour, customer journeys, page structure, content, product information, policies, checkout flows, or the broader decision environment around a brand.

The question is rarely just:

Is this page good?

The better question is usually:

What did the user already believe before they got here, and does this experience confirm it or quietly ruin everything?

I separate symptoms from causes

A drop-off is not a diagnosis.

A low conversion rate is not a diagnosis.

A confusing page is not always the root problem.

Sometimes the interface is weak. Sometimes the offer is unclear. Sometimes the proof is missing. Sometimes the policy contradicts the promise. Sometimes the user arrived with expectations shaped by reviews, search results, AI summaries, social chatter, or something your business has forgotten it ever said.

My job is to work out which layer is actually causing the damage.

I look for contradiction

Contradiction is where trust goes to die.

I look for places where the story changes across:

  • ads
  • landing pages
  • product pages
  • pricing
  • policies
  • FAQs
  • checkout
  • reviews
  • search results
  • social proof
  • support information
  • AI/search summaries

If a customer has to reconcile too much, they hesitate.

If a machine has to reconcile too much, it guesses.

Neither outcome is good.

I use evidence, but I do not worship dashboards

Data is useful. It is not divine.

I use quantitative data to find patterns, behavioural data to see what people actually do, and qualitative evidence to understand why the numbers might be happening.

That can include:

  • GA4
  • Microsoft Clarity
  • Hotjar
  • Mixpanel
  • user interviews
  • survey responses
  • support themes
  • content and UX audits
  • heuristic reviews
  • accessibility checks
  • competitor and category context

The aim is not to collect evidence for decoration.

The aim is to reduce uncertainty.

I say the useful thing, not the convenient thing

I am not very good at pretending a button colour test will fix a proposition problem.

If the issue is wording, I’ll say that.

If the issue is hierarchy, I’ll say that.

If the issue is that the business is making a promise it cannot operationally support, I will definitely say that.

Politely, where possible.

With a scalpel, where necessary.

What you usually get

Depending on the work, outputs may include:

  • UX and UI audits
  • journey reviews
  • content and offer clarity reviews
  • prioritised findings
  • evidence-backed recommendations
  • wireframe concepts
  • page or flow restructuring
  • research synthesis
  • stakeholder-ready summaries
  • practical next-step plans
  • strategic diagnosis across trust, proof, expectation, and interface

I do not produce vague “improve UX” recommendations.

That is not a recommendation. That is a decorative shrug.

How projects usually run

Most work follows a simple pattern.

1. Frame the problem

We clarify what you think is happening, what you already know, what you suspect, and what decisions the work needs to support.

2. Gather the evidence

I review the relevant data, journeys, pages, feedback, recordings, research, content, and surrounding signals.

3. Diagnose the issue

I separate surface problems from deeper causes, looking for friction, ambiguity, contradiction, missing proof, weak hierarchy, expectation mismatch, and trust failure.

4. Prioritise what matters

Not everything deserves equal attention. I focus on what is most likely to affect user confidence, decision-making, comprehension, and commercial outcomes.

5. Recommend practical fixes

You get clear recommendations, not theatre. Where useful, I include example copy, wireframes, structural changes, or validation ideas.

6. Help the team move

The goal is not to admire the problem. The goal is to give teams enough clarity to act without making everything worse in a different font.

What I am like to work with

Clear.

Direct.

Curious.

Evidence-led.

Occasionally funny.

Very allergic to bullshit.

I will challenge assumptions, but I am not interested in point-scoring. The aim is better work, better decisions, and fewer expensive acts of collective self-deception.

Best fit projects

I am a good fit when:

  • something important is underperforming and nobody fully knows why
  • the interface feels wrong but the cause is unclear
  • users are confused, hesitant, or dropping out
  • the offer is hard to explain
  • internal teams disagree about what matters
  • research, analytics, and business reality need joining up
  • trust is fragile
  • AI/search/reputation signals are starting to matter
  • you need a senior outside brain without hiring a whole agency circus

Probably not a fit if

You want someone to rubber-stamp a decision already made.

You want decorative UX theatre.

You want a 60-page report nobody reads.

You believe “make it pop” is a strategy.

You are looking for someone to hide a broken promise behind better copy.

The short version

I help teams understand what is really going on, where trust or clarity is breaking, and what needs to change.

Sometimes that is the page.

Sometimes it is the journey.

Sometimes it is the offer.

Sometimes it is the business quietly contradicting itself in public.

That is usually where the interesting work starts.