RUTHH / SERVICES
Conversion work starts with understanding where decisions become difficult, not adding urgency badges everywhere. We review the quality of your measurement and the shopping journey, then turn observed friction into changes and experiments your team can evaluate.
DISCUSS YOUR PROJECTWe review the available event setup, consent effects, channel attribution and reporting definitions before interpreting funnel drop-off. Duplicate purchases, missing events or inconsistent denominators can distort the picture. Findings distinguish observed behavior from gaps in measurement.
We inspect how people find products, compare options and understand availability, pricing and delivery information. Collection filters, mobile layouts, variant selection and product detail pages are evaluated against the catalog and customer questions rather than a generic checklist of visual trends.
We review cart interactions, discount handling, shipping expectations and error states, using available analytics and direct testing. Checkout recommendations stay within the store’s supported capabilities. The aim is to clarify decisions and remove avoidable obstacles, not introduce misleading pressure.
Recommendations become a backlog with evidence, a hypothesis, effort, dependencies and a success definition. Where traffic and tooling support experimentation, we plan the audience, primary metric, guardrails and decision rules before launch. Implementation and ongoing experiment operation are scoped explicitly.
Checking measurement first helps distinguish a real shopping problem from a broken event or a change in traffic mix. That context matters before committing design or development time.
A stated hypothesis and a consistent measurement window make results easier to discuss. The team can retain, revise or stop work based on evidence rather than treating every release as a success.
Conversion rates are affected by product fit, price, availability, traffic and trading conditions as well as interface design. Low traffic or incomplete data may make a controlled test impractical. We agree proportionate methods and report uncertainty; no audit or experiment guarantees a conversion or revenue increase.
Agree the commercial question, relevant audience and available data. Review event quality, consent setup, seasonality and recent merchandising or campaign changes.
Walk through representative collection, product and cart flows on relevant devices. Combine observed usability issues with reliable funnel evidence and customer feedback where available.
Rank opportunities by evidence, potential relevance, effort and dependencies. Define the proposed change, acceptance checks, measurement plan and any experiment limitations.
Validate implementation and events, then observe the agreed window or run the scoped test. Review the result alongside guardrails and external changes before deciding the next step.
Not necessarily. A conversion audit may identify a narrow issue in product selection, delivery information or cart feedback. A broader design project is considered only when the evidence and business priorities justify it.
There is no useful universal threshold. Feasibility depends on the baseline rate, effect size worth detecting, audience split and acceptable test duration. If a reliable test is not practical, we propose a more suitable evaluation method and explain its limits.
We document what can and cannot be inferred, then identify measurement fixes where needed. Qualitative review and direct testing can still reveal issues, but they should not be presented as proof of a quantified conversion impact.
We can audit those journeys and scope changes to information hierarchy, filtering, variants and interaction feedback. Recommendations are tied to your products, customer questions and available evidence rather than assumed to work for every store.
We agree the primary metric, guardrails, audience and observation window before release. Results are reviewed for data quality and relevant trading changes; a small or inconclusive result is reported as such, without inventing an uplift.
Share your store URL, the shopping step you want to improve and the analytics you currently use. Let us know about recent campaigns, catalog changes or reporting problems that could affect the baseline.
DISCUSS YOUR PROJECT