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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
Framework-Driven Optimization
Measure with Clean Data
Experiment for Impact
Improving website engagement through optimization directly impacts funnel velocity and lifetime value. Engagement metrics (time on site, pages per session, scroll depth, and interaction rate) are leading indicators of whether users will convert. For US-based eCommerce and B2B sites, optimizing engagement is a systems problem: content relevance, load performance, clean tracking, and experiment-driven design all combine to increase qualified conversions and reduce wasted ad spend.
Treat engagement optimization as a repeatable process: Discover → Prioritise → Implement → Measure → Iterate. That process keeps teams focused on revenue impact (not vanity metrics) and aligns front-end changes with server-side attribution and analytics accuracy.
Prioritise a mix of behavioural and technical signals so optimization actions have clear causality to revenue. Key signals include:
| Client Event | Client-Side Signal | Server-Side / Attribution |
|---|---|---|
| Pageview | GA4 page_view | Server logs + enhanced measurement |
| CTA Click | Custom event: cta_click | Event forwarded via GTM Server container |
| Add to Cart | ecommerce.add_to_cart | Order intents reconciled with backend |
| Purchase | purchase event (client + server) | Final revenue event (source attribution applied) |
Implementing server-side tracking reduces attribution leakage common in US ad platforms (Google Ads, Meta). For implementation patterns, see Prebo Digital's services overview here and review team structure on the homepage here.
Design experiments that map engagement improvements to revenue. A typical AB test should include a primary engagement metric (e.g., scroll depth or CTA click rate) and a secondary revenue metric (e.g., add-to-cart rate or $ checkout rate). Use server-side reconciliation to ensure purchase credit is accurate for US ad spend analysis.
Score ideas by ease, impact (estimated $), and measurement confidence. Example estimate for a mid-market Shopify store: improving product page engagement by 15-25% can yield a 5-12% lift in conversions, translating to an estimated $5,000-$20,000 monthly revenue increase depending on traffic and AOV (estimates only).
When you improve website engagement through optimization, account for US privacy rules (CCPA) and cookie consent patterns that can affect client-side signals. Implement consent-aware measurement and server-side fallbacks so engagement attribution remains reliable even when third-party cookies are blocked.
Pro tip: Pair qualitative signals (session recordings, surveys) with quantitative events. Session replays explain the why; events tell you the how much. This combined approach reduces false positives in optimization and focuses teams on profitability, not just engagement spikes.
Turn winning experiments into templates: standardized copy variants, image treatments, and component-level tests. Document variant performance and attribution adjustments in a central playbook. For guidance on building a performance-driven growth system, see Prebo Digital’s about page here. If your team needs a process to operationalize these steps, Prebo Digital outlines service areas on the contact page here.
A US DTC brand reduced mobile LCP by 30% and increased product page interaction by 18% through image optimizations and a simplified PDP layout; after server-side event reconciliation, observed a 7% net increase in attributed revenue (example figures are estimates and vary by store). For a deeper framework or a growth audit, review Prebo Digital’s services here.
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