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Discover what makes us different
Our average client sees a 35% lift in conversion rate across 150+ CRO projects.
500+ tests run across landing pages, checkouts and lead capture forms.
Every change is backed by analytics, heatmaps and real session data.
Certified VWO partners running enterprise-grade experimentation programmes.
Here's what sets us apart from the competition
Find answers to common questions
Prebo integrates CRO work with GA4, Google Tag Manager, server-side tracking, and common ecommerce platforms like Shopify and WordPress to ensure accurate event capture and attribution. We also set up ETL or data-layer solutions where needed so test results feed into a single source of truth for decision making.
Common experiments include A/B tests, multivariate tests, funnel experiments, UX and checkout performance optimizations, and technical fixes that reduce friction. Test duration depends on traffic volume and required statistical power but typically ranges from several weeks to a few months per experiment cycle.
We prioritise revenue-per-visitor, conversion rate, average order value, customer acquisition cost (CAC), lifetime value (LTV), and marketing efficiency ratio (MER), alongside statistical significance for experiments. Clean attribution and centralized data pipelines ensure those metrics reflect true business impact rather than platform-reported figures.
CRO is designed to improve conversion efficiency and attribution accuracy, which can increase revenue and profitability when combined with product-market fit and adequate traffic. Outcomes vary by business and depend on test quality, funnel issues identified, and downstream economics, so results are not assured and are measured against revenue-focused KPIs rather than vanity metrics.
CRO is the systematic process of improving a website or funnel to increase revenue per visitor. Prebo Digital uses a technical-first, analytics-driven approach with hypothesis-driven experiments, server-side tracking, and funnel-level optimization focused on measurable revenue outcomes.
In This Article
Revenue-focused KPIs
Clean tracking stack
Funnel-aligned experiments
Landing pages are where ad spend, content, and product positioning meet a user decision. Measuring the success of landing page conversion efforts means moving beyond surface metrics (pageviews) to revenue-focused KPIs that affect CAC, LTV, and profitability. This guide walks through the key metrics, funnel breakouts (TOF → MOF → BOF), and practical tracking architecture suitable for Shopify, WooCommerce, and B2B landing pages targeting US customers.
Map each landing page to its funnel stage to set realistic targets: top-of-funnel (TOF) pages prioritize CTR and email capture; middle-of-funnel (MOF) pages focus on product interest and trials; bottom-of-funnel (BOF) pages drive purchase or demo requests. Use this simple funnel breakdown to align experiments and attribution windows.
User → Click/Impression → Landing Page → Client-Side Tagging → Server-Side Tagging → GA4/Ad Platforms → Data Warehouse
A server-side layer reduces attribution loss from ad-blockers and browser restrictions. For a practical implementation path, review the approaches used in our services overview and the agency's technical approach on the homepage.
| Cadence | Metrics | Why it matters |
|---|---|---|
| Weekly | Visits, LP CR, micro-conversions, revenue per visit | Detect early drops, validate experiments quickly |
| Monthly | CAC, LTV cohort updates, attribution-adjusted ROAS | Assess long-term profitability and media efficiency |
Measurement focus should shift from traffic volume to revenue impact: prioritize metrics that affect customer economics and funnel velocity, not just clicks.
Start with a clear measurement plan: define primary conversion (purchase, demo booked, lead), secondary conversions, attribution windows, and data owners. Use GA4 combined with a server-side tagging layer and conversion events pushed to a data warehouse for reliable attribution and long-term reporting. If you want a practical implementation overview, see how our technical-first approach aligns with agency processes on the About page.
Design experiments with primary metric aligned to business outcome (e.g., $ revenue per visit). Run tests with adequate sample size and expected effect size calculated for US traffic volumes. Track both statistical significance and business significance-small percentage lifts can be meaningful when CAC is high.
Imagine a Shopify store with 50,000 landing visits/month, $80 average order value (AOV), and a current LP CR of 2.0% (1,000 orders). A targeted CRO program increases LP CR to 2.4% (1,200 orders), a 20% relative lift. Incremental revenue = 200 orders × $80 = $16,000/month. If incremental media cost is $6,000, the net contribution is approximately $10,000/month (figures are illustrative estimates for US stores).
For teams looking to operationalize these steps quickly, our structured framework covers strategy, build, test, and scale phases. To discuss specific technical constraints on your platform, you can reference our contact page for engagement details.
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