Marketing & Content Topics
Marketing strategy, content marketing, campaign management, and digital marketing. Covers content strategy, campaign execution, and marketing analytics.
Google Analytics and Web Metrics
Comprehensive knowledge of Google Analytics 4 and broader web analytics practices for measuring, analyzing, and translating website and application behavior into business decisions. Candidates should be able to navigate the Google Analytics 4 interface and configure properties and data streams, explain how data is collected through tracking snippets and event instrumentation, and distinguish user based metrics such as users from session based metrics such as sessions. Core metric fluency includes sessions, users, engagement rate, bounce rate, average session duration, pages per session, and conversion rate and when to use each. The scope includes designing and implementing conversion tracking and conversion events, defining goals and funnels, analyzing user behavior flows and identifying funnel drop off points, creating segments and performing cohort analysis, and using campaign tagging parameters for marketing attribution. Candidates should also understand attribution models including first click, last click, and multi touch, be able to diagnose data quality and tracking issues such as missing events, duplicate hits, cross domain problems, and consent related gaps, interpret campaign and product performance, and recommend measurement improvements and controlled experiments to validate hypotheses.
Buyer Journey and Content Strategy
Understand and map the buyer decision journey across stages such as awareness, consideration, decision, retention, and advocacy, and develop stage specific content strategies that address buyer questions, concerns, and motivations at each stage. Skills assessed include identifying stage definitions and objectives, mapping content types and formats to stages, crafting stage-appropriate messaging and positioning, aligning distribution channels to where buyers are in the funnel, and orchestrating content flows to guide prospects toward conversion and retention. Candidates should be able to discuss segment and persona differences in journey needs, optimize content mix and formats for top, middle, and bottom funnel, use examples of successful journey based strategies, measure effectiveness with relevant metrics, and iterate using testing and analytics. This topic covers content mapping, alignment, positioning, and stage specific content planning for marketing and growth contexts.
Marketing Automation Platforms and Workflows
Comprehensive domain knowledge and hands on skills for selecting, configuring, operating, and troubleshooting marketing automation platforms and the automated programs they run. Encompasses platform selection and configuration, workspace and user role management, integration with customer relationship management systems, validating data mappings, and operational best practices. Covers workflow and campaign design using triggers, conditions, actions, and workflow components to build trigger based, drip, lifecycle, and lead nurturing campaigns, as well as lead scoring models, segmentation strategies, dynamic content, progressive profiling, and personalization at scale. Includes email marketing strategy and campaign design such as deliverability and list hygiene practices, subject line and content testing, A B testing methodologies, send time optimization, template management, landing pages and form integration, and compliance with regulations such as CAN SPAM and General Data Protection Regulation. Addresses metrics, analytics, and attribution including open rate, click through rate, conversion rate, bounce rate, unsubscribe rate, and campaign level reporting. Details platform operations and troubleshooting such as diagnosing synchronization errors, duplicate records and data conflicts, testing workflows in staging environments, escalation to vendor support, and resolving integration issues, plus scaling and complexity management and orchestration across channels including email, mobile messaging, web, push notifications, and paid advertising. Familiarity with major systems such as Marketo, HubSpot, Salesforce Marketing Cloud, Klaviyo, and ActiveCampaign is relevant, but emphasis is on reliable workflow design, operational excellence, and performance optimization.
Marketing Technology Evaluation and Selection
Covers understanding the marketing technology ecosystem and applying a repeatable framework to evaluate, compare, and select tools and vendors. Candidates should be familiar with common categories such as customer relationship management systems, marketing automation platforms, customer data platforms, web and product analytics, testing and experimentation tools, email and advertising systems, content and social management platforms, attribution and measurement solutions, and integration middleware. They should be able to explain the role each category plays in a stack, typical data flows and integration patterns, identity resolution and customer matching considerations, and how components interact to support measurement and personalization goals. The evaluation framework should include defining the business problem and success metrics, mapping required capabilities to vendor features, conducting gap analysis and weighted scorecards, and planning pilots or proofs of concept. Selection and trade off criteria should address total cost of ownership including licensing, implementation, integration, data migration, training, and ongoing maintenance; expected return on investment and measurable benefits; opportunity cost of not adopting; scalability and performance; security, privacy, and regulatory compliance; vendor reliability and commercial terms including service level agreements and data portability; user experience and adoption challenges; operational support and maintainability; and risks such as vendor lock in and technical debt. Candidates should also be able to discuss build versus buy trade offs, migration and exit planning, pilot success criteria and rollout sequencing, data governance and quality implications, and how priorities and selection trade offs shift with company stage, team capabilities, and budget.