Key Responsibilities and Required Skills for Digital Marketing Analyst

🎯 Role Definition

The Digital Marketing Analyst is a data-driven marketing professional responsible for measuring, optimizing and reporting on digital campaigns and customer journeys to maximize ROI, conversion rate and lifetime value. This role combines web analytics (Google Analytics 4), paid media performance analysis (Google Ads, Meta Ads Manager), SEO measurement, A/B testing, and dashboarding (Looker, Tableau, Power BI) to provide actionable insights and prioritization recommendations for marketing and product stakeholders. The ideal candidate translates complex data into clear marketing recommendations, automates recurring reporting, and partners with cross-functional teams to implement tracking and optimization strategies.

📈 Career Progression

Typical Career Path

Entry Point From:

Marketing Coordinator with campaign reporting responsibilities
Junior Data Analyst or Marketing Data Specialist
SEO Specialist or Paid Media Associate

Advancement To:

Senior Digital Marketing Analyst
Marketing Analytics Manager / Manager, Paid Media Analytics
Head of Marketing Operations or Director of Marketing Analytics

Lateral Moves:

SEO Manager / Organic Growth Manager
PPC / Paid Media Specialist
Growth Marketing Manager

Core Responsibilities

Primary Functions

Analyze multi-channel digital marketing performance (paid search, paid social, display, email, organic search) and produce weekly, monthly and quarterly reports that quantify ROI, CPA, ROAS and LTV to inform budget and channel allocation decisions.
Develop, maintain and automate campaign performance dashboards using Looker, Tableau or Power BI to provide stakeholders with real-time KPIs and ad hoc insight capabilities.
Configure and manage analytics tracking including Google Analytics 4, Google Tag Manager, server-side tagging and ensure data quality, event consistency and accurate conversion measurement across web and mobile.
Design and execute A/B and multivariate tests (using Optimizely, VWO or similar) to improve conversion rates across landing pages, registration flows and checkout experiences, and report statistically significant results and recommended rollouts.
Build and maintain attribution models (last-click, position-based, data-driven) and run incrementality lift and holdout experiments to determine channel contribution and optimize media spend.
Translate campaign performance into actionable optimization recommendations for paid search and paid social (keyword bidding, negative keywords, audience targeting, creative testing) and collaborate with media buyers to implement changes.
Run search engine optimization analysis (technical audits, on-page, backlink evaluation) using tools like Ahrefs, SEMrush or Screaming Frog and work with content and engineering teams to prioritize fixes that increase organic visibility.
Perform in-depth customer and cohort analysis to identify high-value segments, churn patterns and opportunities for retention and re-engagement campaigns that increase customer lifetime value.
Use SQL and Python (or R) to extract, transform and analyze raw clickstream, CRM and customer transaction data to answer complex business questions and support predictive modeling initiatives.
Measure and optimize email marketing performance by analyzing deliverability, open and click-through behavior, and segmenting audiences to improve conversion and retention metrics in platforms such as HubSpot, Marketo or Braze.
Create and maintain media tracking templates, UTM standards and naming conventions to ensure consistent campaign measurement across teams and external agencies.
Collaborate with product management and engineering to define measurement plans for new features, implement event tracking and validate instrumentation to ensure reliable experimentation and analytics.
Lead media and creative post-mortems by synthesizing performance data, creative effectiveness metrics and audience insights to define learnings and best practices for future campaigns.
Conduct competitor and market analysis to surface trends, benchmarks and opportunistic channels or tactics that can drive incremental audience acquisition and growth.
Drive revenue forecasting and budget pacing analysis for marketing channels; provide scenario modeling to guide spend reallocation decisions in response to performance fluctuations.
Implement and improve marketing automation workflows and lifecycle campaigns that leverage scored lead data, behavioral triggers and personalization to nurture prospects and reduce time-to-purchase.
Provide clear, stakeholder-ready executive summaries and presentations that translate technical metrics into business impact and prioritized action items for senior leadership.
Establish and maintain data governance standards for marketing data, including naming conventions, data lineage and validation checks to minimize measurement drift and inconsistencies.
Monitor and report on emerging privacy and regulatory changes (e.g., cookie deprecation, consent frameworks) and adjust measurement and attribution approaches to ensure compliance and business continuity.
Train marketing, product and agency partners on analytics best practices, dashboard interpretation and campaign tagging to elevate cross-functional measurement literacy.
Audit paid media account structures, conversion tracking and bidding strategies to ensure scalable campaign architecture, clear performance signals and accurate budget allocation.
Support ad-hoc, high-impact analysis such as pricing experiments, funnel leakage diagnostics and new market entry modeling to provide rapid, data-backed recommendations.
Partner with BI and data engineering to optimize data pipelines, reduce latency in marketing data, and ensure integration between advertising platforms, CRM and analytics layers.

Secondary Functions

Provide support for ad-hoc data requests, exploratory analysis and marketing attribution troubleshooting when campaign anomalies arise.
Maintain and contribute to the marketing analytics roadmap by identifying opportunities to automate reporting, instrument new events, and consolidate data sources.
Assist in stakeholder prioritization of analytics and tagging tickets by translating business needs into clear product or engineering requirements.
Participate in sprint planning and agile ceremonies related to marketing analytics, tracking, and A/B testing workstreams.
Support vendor evaluations for analytics, attribution and testing tools by developing requirements, running pilots and summarizing vendor performance vs. business goals.
Help manage relationships with external agencies and partners by validating their reporting, auditing performance claims and aligning on shared measurement standards.
Document standard operating procedures for campaign tagging, dashboard updates and funnel analyses to ensure continuity and reproducibility.
Monitor ongoing campaign health and flag potential fraud, click anomalies, or data integrity issues that could skew optimization decisions.
Support cross-functional marketing initiatives such as product launches, seasonal campaigns and retention drives with analytics input and measurement plans.
Contribute insights to creative briefs and audience personas based on behavioral and performance data to improve campaign targeting and messaging alignment.

Required Skills & Competencies

Hard Skills (Technical)

Google Analytics 4 (GA4) — implementation, event modeling, funnel analysis, audiences and custom reporting.
Google Tag Manager and server-side tagging — setup, debugging and governance to ensure tracking accuracy.
Paid media platforms — Google Ads (Search, Display, Shopping), Microsoft Ads and Meta/Instagram Ads Manager with experience in campaign structure and bid strategies.
SQL for data extraction, cohort analysis and building marketing datasets from warehouses (BigQuery, Redshift, Snowflake).
Data visualization and dashboarding — Looker, Tableau, Power BI or equivalent to build automated, stakeholder-friendly dashboards.
A/B testing and experimentation platforms — Optimizely, VWO, Google Optimize (or equivalent) with experience in test design and statistical significance.
SEO tools and techniques — Ahrefs, SEMrush, Screaming Frog, technical SEO audits and on-page optimization best practices.
Marketing automation and email platforms — HubSpot, Marketo, Braze, Iterable or comparable systems with journey design and segmentation.
Attribution and analytics modeling — familiarity with multi-touch attribution, data-driven models, and incrementality testing methods.
Excel/Google Sheets advanced skills — pivot tables, VLOOKUP/XLOOKUP, array formulas and automation with macros or App Script.
Basic scripting/data science — Python or R for advanced analysis, automation and predictive modeling (preferred).
Familiarity with CRM systems and data flows — Salesforce or HubSpot integrations and lead lifecycle measurement.
Tagging, UTM standards and campaign naming governance to ensure clean, usable datasets.

Soft Skills

Strong analytical and problem-solving mindset with the ability to translate data into clear business recommendations.
Excellent written and verbal communication; capable of creating executive summaries and presenting complex analyses to non-technical stakeholders.
Attention to detail and high standards for data quality, reproducibility and documentation.
Stakeholder management and cross-functional collaboration skills; able to influence product, creative and paid media teams.
Prioritization and project management to balance recurring reporting with strategic analysis and experiments.
Curiosity and continuous learning orientation to keep pace with digital advertising and analytics innovations.
Storytelling with data — crafting narratives from metrics that drive action and align teams around clear next steps.
Adaptability and resilience in fast-moving marketing environments and seasonal campaign cycles.
Ethical judgment around customer data privacy, consent and compliant measurement practices.
Initiative and ownership — comfortable leading analytics projects from scoping to delivery.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Marketing, Statistics, Economics, Business, Data Science, Computer Science, or a related field.

Preferred Education:

Master's degree in Analytics, Marketing Science, Business Analytics or an MBA with strong quantitative coursework.
Relevant professional certifications such as Google Analytics Individual Qualification (GAIQ), Google Ads Certification, HubSpot Inbound Certification, or courses in SQL/Python for analytics.

Relevant Fields of Study:

Marketing or Digital Marketing
Statistics, Mathematics or Data Science
Business, Economics or Finance
Computer Science or Information Systems
Communication with quantitative coursework

Experience Requirements

Typical Experience Range:

2–5 years of hands-on experience in digital marketing analytics, marketing operations or paid media analysis.

Preferred:

3–7 years of progressive experience managing analytics for multi-channel digital campaigns, building dashboards and running experimentation programs.
Demonstrated experience with GA4 implementation, SQL querying against a data warehouse (BigQuery/Redshift/Snowflake), and direct collaboration with product and engineering teams to implement tracking.
Proven track record of improving ROI/ROAS, lowering CPA, or materially improving conversion rates through data-backed optimizations.
Experience working with agencies, cross-functional marketing teams, and senior leadership in a fast-paced or high-growth environment.