A/B testing for Shopify
Validate improvements with A/B testing
Opinions about what will improve conversion are plentiful. Data about what actually works is scarce. Starcodia runs A/B testing programs that validate hypotheses with real traffic so you know what works before committing to permanent changes.
How A/B testing works
A/B testing is the scientific method applied to ecommerce optimization:
Split traffic. A portion of your traffic sees the control (current experience) while another portion sees a variant (proposed change). Traffic is randomly assigned to ensure fair comparison.
Measure results. Both versions are measured against the same success metrics—typically conversion rate, revenue per visitor, or add-to-cart rate.
Statistical analysis. Statistical tests determine whether the variant performs better with enough confidence to rule out chance. We require 95% confidence before declaring winners.
Implement winners. Changes that prove to improve metrics are implemented permanently. Changes that do not are discarded without permanent implementation.
This approach removes guesswork from optimization decisions. Instead of implementing changes based on opinion or intuition, you implement changes proven to improve metrics.
Common A/B test areas
Product pages. Layouts, image galleries, description formatting, add-to-cart button styling, trust signals, reviews display, cross-sells and upsells.
Collection pages. Grid layouts, filtering options, sorting defaults, product card design, load-more vs pagination.
Cart and checkout. Cart layout, upsell positioning, shipping messaging, payment option display, express checkout buttons.
Homepage. Hero messaging, value propositions, featured collections, social proof, navigation prominence.
Navigation. Menu structure, category naming, search prominence, mobile navigation patterns.
Promotions. Discount display, urgency messaging, free shipping thresholds, bundle offers.
A/B testing programs
A single test provides a single data point. An ongoing testing program creates compounding improvements over time. Starcodia testing programs include:
Hypothesis development. We identify test opportunities based on data analysis, UX audits, industry best practices and competitive analysis.
Test prioritization. Not all tests are equal. We prioritize tests by potential impact, confidence level and implementation effort.
Test implementation. We build test variants and configure testing tools. No developer time required from your team.
Result analysis. We monitor tests, ensure statistical validity, and analyze results to understand why tests won or lost.
Winner implementation. Winning variations are implemented permanently in your theme.
Learning documentation. Insights from tests inform future hypotheses and build institutional knowledge.
Start an A/B testing program
If you have sufficient traffic and want to optimize based on data rather than opinion, Starcodia can design a testing program for your store.
Discuss A/B testing