Experiment Design & A/B Testing
Prove What Works Before You Scale
Your marketing team has strong opinions about what will drive growth: “Video ads will outperform image ads,” “Longer landing pages convert better,” “Email subject lines with emojis get higher open rates.” But opinions without data lead to expensive mistakes.
Experiment design and A/B testing turn opinions into facts. Instead of betting your marketing budget on assumptions, you test small, measure results, and scale only what proves to work.
The Testing Advantage: Companies that run systematic experiments grow 7x faster than those that rely on intuition. But 73% of businesses don’t have proper testing frameworks in place.
Why Most A/B Tests Fail
You’ve probably tried A/B testing before: changed a button color, ran it for a week, saw a small difference, and weren’t sure if it was meaningful. Most A/B tests fail because they lack:
- Statistical significance (not enough traffic or time)
- Clear hypothesis and success metrics
- Proper test isolation (multiple changes running simultaneously)
- Business impact measurement (testing clicks instead of revenue)
Our Experiment Design Framework
Hypothesis-Driven Testing
Problem Identification: Data analysis to find conversion bottlenecks and growth opportunities
Hypothesis Formation: Clear predictions about what changes will improve specific metrics
Success Metrics Definition: Primary and secondary KPIs that matter for business growth
Test Implementation
Proper Test Setup: Single-variable changes with controlled conditions
Audience Segmentation: Ensuring test groups are statistically equivalent
External Factor Control: Accounting for seasonality, marketing campaigns, and other variables
Related Services
Experiment design works best with Analytics & Attribution for proper measurement and CRO & Landing Pages for implementation of winning tests.
E-commerce Store Increases Revenue 34%
StyleShop was making website changes based on best practices and competitor analysis, but revenue growth remained flat despite increased traffic.
Experiment Design Implementation:
- Established testing framework with proper statistical requirements
- Created hypothesis backlog prioritized by potential business impact
- Implemented testing calendar to avoid experiment conflicts
Key Winning Tests:
- Product page layout change: +23% add-to-cart rate
- Checkout process simplification: +18% completion rate
- Email subject line optimization: +41% open rates
Results After 6 Months:
- Revenue per visitor: +34% improvement
- Conversion rate: 2.8% to 4.1%
- Average order value: +22% increase
Testing Timeline
What Progress Actually Looks Like
Experiment Setup
1-2 Weeks
Individual Tests Run
2-6 Weeks
Meaningful business impact
3-4 months
Growth Strategy Pricing
| Service | Description | Price |
|---|---|---|
| Testing Setup & Management | Framework setup and test execution | $1,400/mo |
| Advanced Experimentation | Multivariate testing and statistical analysis | $2,000/mo |
| Complete Testing Program | Strategy, execution, and growth recommendations | $2,600/mo |
What We Test — and Why It Matters
Growth Road-Map Creation
Growth strategy development takes 4–6 weeks for comprehensive analysis and road-map creation. Initial implementation shows results within 60–90 days, with significant improvements within 6 months.
- Impact vs. effort analysis for all potential initiatives
- Resource requirement assessment and allocation
- Timeline development with realistic milestones
- Risk assessment and mitigation planning
- Phase 1: Quick wins (30 days)
- Phase 2: Medium-impact setup (60–90 days)
- Phase 3: High-impact, long-term (6–12 months)
- Phase 4: Innovation & expansion (12+ months)