We are looking for an Amazon CRO Data & Experimentation Analyst to help improve the performance of our Amazon product listings through data-driven analysis, structured experimentation, and clear optimisation recommendations.
In this role, you will be responsible for measuring listing performance, managing the A/B testing process, analysing conversion funnels, and transforming Amazon performance data into actionable business decisions.
The goal of this position is to ensure that Conversion Rate Optimisation (CRO) decisions are based on reliable evidence rather than assumptions. You will analyse experiments, identify conversion opportunities, investigate performance changes, and clearly communicate what changed, why it changed, and what actions should be taken next.
Works closely with: Category Performance Manager, SEO Specialists, Creative Designers, Video Editor, and Advertising Team
Key Responsibilities1. A/B Testing & Experimentation
- Manage the complete Amazon experimentation pipeline across:
- Main product images
- Product titles
- Bullet points
- Image galleries
- A+ Content
- Ensure every experiment begins with a clearly defined problem, baseline, hypothesis, variation, and success metric.
- Coordinate experiment launch dates and testing periods.
- Monitor active tests and ensure sufficient data is collected before making decisions.
- Analyse completed experiments and recommend whether variations should be implemented, rejected, refined, or retested.
- Maintain consistency and discipline across the experimentation process.
2. Test Result Analysis
- Analyse the impact of experiments on key performance indicators, including:
- Click-Through Rate (CTR)
- Conversion Rate (CVR)
- Sessions
- Units Ordered
- Revenue
- Gross Profit
- Distinguish meaningful performance improvements from normal fluctuations.
- Identify possible reasons why a variation succeeded or failed.
- Evaluate both conversion impact and commercial value before recommending implementation.
- Present experiment findings in clear, concise business language for the CRO team and leadership.
3. Performance & Funnel Analysis
Monitor listing performance across the complete Amazon conversion funnel:
Impressions → Clicks → Sessions → Conversion → Revenue
Key responsibilities include:
- Detect performance gaps across priority ASINs and product categories.
- Investigate sudden changes in traffic, ranking, CTR, CVR, revenue, and sales.
- Analyse potential causes behind performance changes.
- Connect listing performance with factors such as:
- Pricing
- Inventory and stock availability
- Advertising activity
- Customer reviews and ratings
- Organic ranking
- Competitor activity
- Promotional campaigns
4. Dashboard & Reporting Management
- Build and maintain CRO dashboards for priority ASINs and active experiments.
- Track before-and-after performance for optimised listings.
- Maintain accurate weekly and monthly performance reporting.
- Monitor key metrics including:
- Organic visibility
- Sessions
- CTR
- CVR
- Revenue
- Gross profit
- ACoS
- TACoS
- Active experiments
- Experiment win rate
- Ensure dashboards and reports are accurate, consistent, easy to understand, and suitable for management decision-making.
- Identify important trends, anomalies, risks, and optimisation opportunities.
5. Experiment Prioritisation
- Work closely with the CRO Team Lead and Category Performance Manager to identify high-impact testing opportunities.
- Estimate the potential value of experiments based on:
- Traffic volume
- Conversion gaps
- Revenue opportunity
- Commercial importance
- Potential scalability
- Prioritise experiments that can generate valuable learnings across multiple related ASINs or categories.
- Help prevent low-value, unclear, or poorly structured experiments from consuming creative and technical resources.
6. Experiment Documentation & Knowledge Management
- Maintain a central record of all CRO experiments.
- Document:
- Problem statements
- Baselines
- Hypotheses
- Test variations
- Results
- Conclusions
- Final decisions
- Document both successful and unsuccessful experiments to support continuous learning.
- Convert winning experiments into reusable CRO guidelines and playbooks.
- Identify patterns and learnings that can be scaled across categories, ASINs, and marketplaces.
7. AI, Claude Skills & Agent Workflows
- Use Claude Skills, AI agents, and similar AI-assisted tools to support:
- Data summarisation
- Performance comparison
- Anomaly detection
- Experiment documentation
- Dashboard reporting
- Root-cause investigation
- Develop repeatable AI-assisted workflows that reduce manual reporting and analysis effort.
- Use AI to identify possible explanations for changes between different performance periods.
- Validate all AI-generated insights against the original source data before presenting conclusions or recommendations.
- Continuously explore opportunities to improve CRO analysis and reporting efficiency through automation.
8. Cross-Functional Collaboration
- Translate analytical findings into clear and practical actions for SEO, Creative, Video, Advertising, and Category teams.
- Help designers and SEO specialists understand the objective and hypothesis behind each experiment.
- Coordinate listing implementation dates, testing periods, and result-review timelines.
- Clearly communicate findings, recommendations, risks, and next steps.
- Escalate data-quality issues, tracking gaps, or experiment risks to the CRO Team Lead.
A/B Testing Workflow
The analyst will manage and continuously improve the following experimentation process:
Insight → Hypothesis → Baseline → Variation → Launch → Measure → Decide → Document → Scale
Depending on traffic volume, test stability, sample size, and Amazon experiment data, a typical experiment may require approximately 1–2 weeks of data collection before a final decision is made.
Testing duration should always be determined by data quality and reliability rather than speed alone.
Required Experience
- Experience in data analysis, digital analytics, CRO, e-commerce analytics, or experimentation.
- Practical experience analysing A/B tests and conversion funnels.
- Strong understanding of performance metrics such as CTR, CVR, sessions, revenue, sales, and profitability.
- Ability to interpret changes in performance and investigate potential root causes.
- Experience creating dashboards, reports, and analytical summaries.
- Strong spreadsheet and data-analysis skills.
- Ability to translate complex data into clear commercial recommendations.
- Experience using Claude, AI agents, ChatGPT, or similar AI-assisted analytical tools.
- Strong attention to detail and commitment to data accuracy.
Preferred Experience
The following experience would be an advantage:
- Amazon Seller Central
- Amazon Brand Analytics
- Search Query Performance
- Manage Your Experiments
- Amazon listing-performance analysis
- Amazon advertising analytics
- Organic-performance analysis
- ACoS and TACoS analysis
- Organic ranking and keyword-performance analysis
- Understanding of paid-to-organic relationships
- Experience working with large ASIN portfolios
- Familiarity with basic statistical concepts, including:
- Sample size
- Confidence levels
- Test duration
- Statistical significance
- Performance variance
Core Skills
- A/B Testing & Experiment Analysis
- Conversion Rate Optimisation (CRO)
- Amazon Funnel Analysis
- Dashboard Creation
- Performance Reporting
- Root-Cause Investigation
- Data Validation & Accuracy
- Commercial Data Interpretation
- Experiment Prioritisation
- Revenue & Profitability Analysis
- AI-Assisted Data Analysis
- Analytical Storytelling
- Cross-Functional Communication
- Problem Solving
- Attention to Detail
Experience- 4+ Years
Mail: [email protected]
Contact: +91 9952560396
Location: Chennai, Tamil Nadu
Pay: ₹60,000.00 - ₹70,000.00 per month
Work Location: In person
