Merchandise Content Analyst

Massmart; Johannesburg; On-site; ZAR 300 000 - 450 000; Full time

Job summary

A leading company in the retail sector seeks an Analyst to enhance product content quality through data analysis and reporting. The role involves data collection, trend analysis, and stakeholder collaboration to drive improvements in digital merchandising. Ideal candidates will have experience in data management and strong analytical skills.

Qualifications

• 2–4 years’ experience in data analysis or eCommerce content management.
• Strong knowledge of data extraction and validation for reporting.

Responsibilities

• Gather and validate product content data from multiple sources.
• Analyze product content data to identify trends and insights.
• Develop interactive dashboards to visualize key performance metrics.

Skills

Data Analysis & Interpretation

Attention to Detail

Process Optimisation

Problem-Solving

Communication & Presentation Skills

Education

Matric (Grade 12)

Relevant degree in a related field

Tools

SQL

Python

Excel

Power BI

Tableau

Looker

Job description

“We encourage people with disabilities to apply.”

Summary:

The Analyst is responsible for collecting, analyzing, and reporting on merchandise content data to support decision-making, improve SKU activation, and enhance product content quality. The role ensures that data is structured, validated, and presented in a meaningful way to drive continuous improvements in digital merchandising.

Functions / Responsibilities:

Data Collection & Management

• Gather product content data from multiple internal and external sources to ensure a comprehensive and holistic understanding of merchandise content across all platforms.
• Validate collected data for accuracy, completeness, and consistency before analysis to prevent misleading insights that could result in poor business decisions.
• Organize raw data into structured formats such as databases, spreadsheets, or BI dashboards to facilitate easier analysis and reporting.
• Standardize naming conventions, taxonomies, and categorization rules for merchandise content to improve searchability and maintain uniformity across digital platforms.
• Maintain a centralized repository of SKU activation, content engagement, and compliance metrics to enable quick reference and historical trend analysis.
• Support the Specialist in data extraction and manipulation by creating queries, data models, and automation scripts to improve efficiency and reduce manual work.

Trend & Impact Analysis

• Analyze historical and real-time product content data to identify trends, correlations, and anomalies that could impact SKU activation, engagement, and sales performance.
• Compare content performance across different product categories to determine which descriptions, images, or features contribute to higher conversion rates and customer retention.
• Benchmark our product content against competitor listings to understand market positioning, identify gaps, and recommend improvements that enhance our competitive advantage.
• Investigate fluctuations in customer engagement with merchandise content to determine whether they are influenced by seasonality, price changes, content updates, or other external factors.
• Generate insights on how different product attributes (e.g., image resolution, bullet points, long-form descriptions) impact customer decision-making, ensuring continuous optimization of digital merchandising.
• Track customer search behaviors and filter usage patterns to refine keyword tagging, metadata structuring, and overall product discoverability on the website and shopping app.

Reporting & Dashboards

• Develop interactive dashboards that visualize key performance metrics such as SKU activation rates, content completeness, and engagement scores to provide leadership with real-time insights.
• Generate weekly and monthly reports that summarize merchandise content trends, compliance levels, and areas for improvement, ensuring data-driven decision-making.
• Summarize large volumes of content data into executive-friendly reports and presentations that highlight key findings, challenges, and actionable recommendations.
• Automate data reporting processes by developing scripts, macros, or BI integrations that reduce manual effort and improve reporting accuracy.
• Enhance data visualization techniques using charts, heatmaps, and comparative analytics to make complex data more accessible and understandable for non-technical stakeholders.
• Distribute reports to relevant internal teams, ensuring that Buying, Marketing, and Content teams receive accurate and timely information to adjust their merchandising strategies accordingly.

Process Improvement & Automation

• Identify inefficiencies in current merchandise content workflows by analyzing process bottlenecks and proposing data driven solutions that improve speed and accuracy.
• Develop automation scripts to streamline data extraction, validation, and reporting, reducing human error and increasing efficiency in merchandise content management.
• Improve data integration processes by working with IT and development teams to enhance system capabilities, ensuring smoother synchronization of product data across platforms.
• Integrate AI and machine learning models into merchandise content workflows to enhance product categorization, auto tagging, and image recognition capabilities.
• Streamline the onboarding and updating of SKU data by implementing standard operating procedures (SOPs) that reduce redundancy and improve accuracy.
• Support the testing and implementation of new technologies in the content management space, ensuring the business stays ahead in digital merchandising innovations.

Stakeholder Support

• Provide actionable insights to the Merchandise Content Standards team to enhance product descriptions, ensuring they align with customer preferences and search behaviors.
• Support the Marketing team with data-driven recommendations on content performance, helping them optimize campaign messaging and product storytelling.
• Engage with the Buying team to share insights on vendor-provided content quality, ensuring that suppliers comply with merchandise content standards.
• Assist IT teams in integrating analytics tools into the eCommerce platform, enabling seamless tracking of content performance across different channels.
• Advise vendors and third-party sellers on best practices for structuring their product data, helping them improve their listings and increase activation success rates.
• Collaborate with internal teams, including UX designers and category managers, to align content strategies with broader eCommerce and business objectives.

Data Compliance & Quality Control

• Monitor adherence to internal and external data compliance regulations to ensure that product information is accurate, non-misleading, and aligned with industry standards.
• Identify inconsistencies in product data and proactively correct discrepancies before they impact the customer experience or lead to regulatory issues.
• Implement validation rules and automated quality control measures that flag incomplete or incorrect product information, ensuring only high-quality content goes live.
• Audit content datasets regularly to detect potential risks, ensuring that all SKU descriptions, images, and attributes meet established quality benchmarks.
• Train internal stakeholders on merchandise content compliance best practices, equipping them with the knowledge needed to maintain high-quality listings.
• Ensure that all reporting, analysis, and data-sharing processes align with data privacy and security protocols, reducing the risk of unauthorized access and information leaks.

Requirements:

Minimum Academic, Professional Qualifications and Experience required for this position

Qualifications:

• Matric (Grade 12) or equivalent – Required.
• Relevant degree a related field preferred

Experience:

• 2–4 years’ experience in data analysis, business intelligence, or eCommerce content management.
• Strong knowledge of data extraction, validation, and structuring for reporting.
• Experience with dashboard creation, automation, and data-driven storytelling.
• Proficiency in SQL, Python, or Excel for data manipulation and reporting.
• Familiarity with eCommerce platforms, PIM systems, and digital merchandising.
• Exposure to AI-driven analytics, automation, and data governance compliance

Competencies and Skills

Core Competencies:

• Data Analysis & Interpretation
• Attention to Detail
• Process Optimisation
• Problem-Solving
• Business Intelligence & Reporting
• Stakeholder Collaboration
• Technical Proficiency in Data Tools
• Decision-Making Under Pressure
• Compliance & Data Governance
• Communication & Presentation Skills

Skills

• Data Extraction & Structuring
• Trend Analysis & Impact Evaluation
• BI Dashboard Development (Power BI, Tableau, Looker, etc.)
• Process Automation (SQL, Python, VBA, or RPA Tools)
• Data Validation & Quality Control
• eCommerce Content Optimisation
• Competitor & Benchmark Analysis
• Data-Driven Decision-Making
• AI & Machine Learning Integration
• Data Compliance & Risk Management

“Employment Equity Policy Requirements may be applicable"