Marketing Analytics Manager

Roles and responsibilities

• Lead the growth engineering team, a group of data analysts, performance marketers, lifecycle marketers and marketing automation specialists responsible for driving the best commercial results for Canonical through data and technology.
• Design, implement and operate Canonical marketing technology stack, a dozens of martech applications, from commercial applications (Marketo, Google Analytics, Leandata) to open source solutions (Superset, Kubeflow, WordPress).
• Own reporting and analytics throughout the customer lifecycle from ABM, Multi-Touch Attribution, funnel performance, acquisition costs and customer retention.
• Develop and track OKRs and conversion rates across the marketing and revenue funnels.
• Optimise lead scoring, lead flow and cadences to increase conversion rates across marketing and sales.
• Develop web analytics and SEO practices to sustain high levels of organic user and customer acquisition.
• Drive Return On Ad Spend optimisation through attribution methodologies, advanced targeting and channel exploration.
• Ensure marketing data cleanliness and completeness through data governance policies and management practices.
• Champion an experimentation culture by supporting the business with processes, tooling (A/B tests, MAB) and expertise.
• Collaborate with teams across marketing and throughout Canonical (Product, IS, Engineering, RevOps, Finance) to build data solutions to Go To Market problems.
• Support execution excellence in the marketing team through training, tools and documentation.
  
  

What we are looking for in you

• An undergraduate or postgraduate degree in data science, statistics, mathematics, computer science, or engineering , or a compelling narrative about your alternative chosen path, together with an exceptional academic track record throughout your education years.
• A strong analytical mindset with solid evidence of managing projects that drive commercial success.
• Knowledge in advanced marketing analytics (media mix modelling, cohort analysis, attribution models ), coding/scripting languages (Python, JS, etc), and databases (SQL, etc)
• Exceptional management experience, leading analytical, creative professionals to excellence.
• Experience in selecting, implementing and managing a leading edge martech stack preferably built on open source software.
• A track record of building a culture of experimentation across the organisation.
• Advanced web analytics and SEO practices across website and SAAS products.
• Proven ability of collaborating with senior stakeholders across functions (sales, revenue operations, product, IS…) to turn strategic business and product questions into impactful analytic projects.
• Willingness to travel up to 2-4 times a year for internal events.
  
  

Additional Skills Of Interest

• Experience implementing ML generated predictive models for lead generation or customer retention purposes.

Desired candidate profile

Leadership & Team Management

• Team Management: Lead and mentor a team of marketing analysts, data scientists, and data engineers to ensure high-quality, actionable insights.
• Resource Allocation: Assign tasks, set priorities, and allocate resources to meet business objectives and marketing goals.
• Talent Development: Foster continuous learning and career growth for team members, providing guidance, training, and performance reviews.
• Cross-functional Collaboration: Work closely with other departments, including marketing, sales, finance, and product teams, to align analytics efforts with broader business objectives.

2. Strategic Marketing Insights

• Campaign Performance Analysis: Analyze the performance of marketing campaigns across various channels (digital, traditional, email, etc.), including paid search, social media, SEO, and display ads.
• Customer Segmentation: Develop customer segments and personas based on data analysis to ensure targeted marketing strategies.
• Behavioral Analytics: Use data to understand customer behaviors and trends (e.g., purchase patterns, website engagement, and conversion rates) to inform marketing tactics.
• Revenue Attribution: Develop and manage models to attribute revenue accurately to marketing efforts, identifying which channels or tactics are most effective.
• Market Research: Conduct competitive analysis and market research to assess industry trends, customer needs, and competitive positioning.

3. Data-Driven Decision Making

• KPI Definition: Establish key performance indicators (KPIs) and metrics to evaluate the success of marketing strategies and ensure alignment with business goals.
• Predictive Analytics: Implement predictive modeling and forecasting techniques to anticipate customer behavior, forecast trends, and make proactive marketing decisions.
• Optimization: Use A/B testing, multivariate testing, and optimization algorithms to test marketing hypotheses and continuously improve campaigns.
• Reporting & Dashboards: Oversee the development of comprehensive reports and interactive dashboards that provide key marketing performance data to executives and stakeholders.

4. Marketing Technology & Tools

• Analytics Tools: Proficiency with analytics platforms like Google Analytics, Adobe Analytics, Mixpanel, and Kissmetrics to measure and analyze user behavior and digital marketing performance.
• Customer Relationship Management (CRM): Experience with CRM platforms such as Salesforce, HubSpot, or Marketo to analyze customer journeys and sales funnels.
• Data Visualization: Use data visualization tools like Tableau, Power BI, or Google Data Studio to present complex data in an easy-to-understand, actionable format.
• Marketing Automation: Work with tools like Eloqua, Pardot, or HubSpot to implement and optimize marketing automation workflows and campaigns.
• Data Warehousing & Databases: Familiarity with databases, SQL, and data warehousing solutions to manage large sets of marketing data.

5. Business and Marketing Strategy Alignment

• ROI Analysis: Measure the ROI of various marketing initiatives and campaigns, ensuring marketing spend is optimized and aligned with overall business goals.
• Budget Management: Collaborate with finance and marketing leadership to allocate marketing budget effectively, ensuring maximum return from marketing activities.
• Stakeholder Communication: Present findings and recommendations to senior leadership and key stakeholders, helping them make data-informed decisions about future marketing strategies.