Conversion Optimisation & Analytics

Conversion Rate Optimisation & Analytics

Turn more existing traffic into enquiries, sales and revenue.

Discuss conversion optimisation & analytics

When it matters

When traffic does not convert

Conversion optimisation is useful when traffic is available but important pages, forms, offers or journeys are losing too many potential conversions.

The analysis can also reveal where Google Ads and paid acquisition or SEO and organic growth need a stronger landing journey.

You may need this when

Traffic is growing but conversion is not
You cannot see where or why visitors drop out
Pricing, forms or key pages are creating friction
Tests are being run without a clear hypothesis or reliable measurement

What the work can include

What conversion rate optimisation can include

Funnel and conversion diagnostics
Analytics and measurement design
UX, landing-page and form optimisation
Pricing and merchandising review where relevant
Experiment planning and commercial interpretation

The scope stays tied to a defined conversion problem, whether it sits on one page or across a wider funnel.

How we work

How we find and fix conversion problems

Establish where the loss is material

We validate the data and identify the points in the journey where improving conversion would have meaningful commercial impact.

Form a testable explanation

We combine behavioural evidence, customer context and offer analysis to define why performance may be weak and what would need to change.

Prioritise the intervention

We compare likely impact, effort, confidence and implementation risk to decide which changes or experiments should happen first.

Learn from the result

We measure the outcome, keep what is supported by evidence and use the result to determine the next priority.

Measurement

How CRO performance is measured

Measures may include qualified conversion rate, funnel progression, revenue per visitor, acquisition efficiency and average selling price. Selected senior experience includes an approximately 15-20% improvement in average selling price through pricing, UX and conversion work; this is not attributed to a FolkWeb client case.

Leading signals include trustworthy data, clear hypotheses and improvement in the specific journey being tested. Funnel progression, qualified conversion and revenue per visitor provide the commercial interpretation.

Small movement in a surface metric is not enough without understanding its effect on buyer quality and the wider funnel.