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Job Description
Reports to: Director Media & Consumer Marketing (M&CM)
About the Role: The Marketing Effectiveness Lead will be responsible for building and implementing a robust, data-driven marketing measurement framework. A Modern Marketing Measurement Toolkit where each tool shows up with a different cadence of delivery. Identify consistent and scalable measurement capabilities that allow for planning and reporting outcomes. This role will be instrumental in driving data-driven decision-making, optimizing marketing performance, and maximizing ROI.
Key Responsibilities:
Measurement Framework: - Develop and implement a comprehensive marketing measurement framework, including KPIs, metrics, and attribution models. - Oversee the implementation of advanced analytics tools and techniques to measure marketing performance. - Establish a robust data governance framework to ensure data quality and accessibility.
Data Analysis and Insights: - Analyse marketing performance data to identify trends, opportunities, and areas for improvement. - Develop insightful reports and dashboards to track key metrics and monitor campaign performance. - Testing and Experimentation: Co-Design A/B testing road-maps to optimize marketing campaigns. Analyse test results to identify winning strategies and make data-driven decisions.
Cross-Functional Collaboration: - Work closely with marketing and finance teams to provide actionable insights that answer business objectives. - Collaborate with external partners and vendors to leverage their expertise and technology.
Team Leadership: - Mentor and guide the marketing team on data-driven decision making and best practices. - Foster a data-driven culture within the organization.
Qualifications
Experience in a senior Data Science, Data Strategy or Technology Solutions role and leading projects.
Strong analytical skills, deep understanding of marketing metrics and analytics.
Proven Experience in data strategy & measurement framework capabilities.
Strong understanding of hypothesis testing and measurement methodologies such as frequentist and bayesian approaches, or a strong statistical knowledge and data analysis skills.