Key Responsibilities and Required Skills for Web Marketing Analyst

🎯 Role Definition

The Web Marketing Analyst is responsible for translating web and digital marketing data into actionable insights that drive customer acquisition, engagement, retention, and revenue. This role combines technical web analytics, marketing channel analysis (SEO/SEM/PPC/email/social), testing and optimization (A/B and multivariate), and cross-functional collaboration with product, engineering, content and performance marketing teams. The ideal candidate will be fluent in analytics platforms (GA4, Adobe Analytics), tag management (GTM), data querying (SQL/BigQuery), visualization (Looker/Tableau/Power BI), and conversion optimization methodologies.

📈 Career Progression

Typical Career Path

Entry Point From:

Digital Marketing Coordinator or Assistant
Junior Web Analyst / Analytics Intern
SEO Specialist or PPC Coordinator

Advancement To:

Senior Web Marketing Analyst / Senior Digital Analyst
Web Analytics Manager or Insights Lead
Digital Marketing Manager / Growth Marketing Manager

Lateral Moves:

SEO Manager / Organic Growth Specialist
Paid Media / PPC Manager
Product Analyst or Customer Intelligence Analyst

Core Responsibilities

Primary Functions

Develop, maintain, and own web analytics reporting and dashboards that track acquisition, behavior, conversion and revenue KPIs across organic, paid, email, referral and social channels; automate key reports for weekly and monthly stakeholder review.
Implement and validate tracking for websites and single-page applications using Google Tag Manager (GTM), ensuring accurate event, conversion and pageview measurement for GA4, Adobe Analytics or similar platforms.
Lead GA4 migration planning and execution including tagging strategy, event mapping, custom dimensions/metrics, and validation against legacy Universal Analytics data to ensure continuity of measurement.
Translate business questions into measurement strategies, design tagging schemas and event taxonomies, and document data dictionaries to maintain a single source of truth for digital metrics.
Perform detailed channel and campaign performance analysis (SEO, SEM, display, social, affiliates, email), identifying optimization opportunities and recommending budget reallocations to improve ROI and CPA.
Conduct landing page and funnel analysis to identify bottlenecks, friction points, and drop-off stages; provide prioritized recommendations to product and UX teams to improve conversion rates.
Design, implement and analyze A/B tests and multivariate experiments using platforms such as Optimizely, VWO, Google Optimize or internal experimentation frameworks; interpret results and produce action plans for rollouts.
Build advanced queries in SQL and BigQuery (or similar data warehouses) to join web event data with CRM, product and media datasets to perform cohort, retention and LTV analyses.
Create and present executive-level summaries and deep-dive analyses for marketing leadership and cross-functional stakeholders, translating complex data into clear business recommendations and next steps.
Audit and troubleshoot tracking issues, data discrepancies and sampling problems across analytics platforms; implement QA processes and monitoring alerts to ensure data accuracy and reliability.
Perform keyword research, SERP analysis and on-page technical SEO audits in collaboration with content teams to increase organic visibility and conversions.
Manage UTM strategy, campaign tagging governance and marketing attribution models, working with media buyers and analytics engineers to improve multi-touch attribution accuracy.
Analyze paid search and social campaigns at granular keyword/ad set levels to optimize bids, creatives, and landing page experiences for improved CTR, CVR and ROAS.
Leverage user behavior tools (Hotjar, FullStory, session replay, heatmaps) to validate hypotheses about user experience and support qualitative insights that complement quantitative analytics.
Create predictive models and forecasting dashboards (e.g., revenue, churn, CAC payback) using statistical methods or basic machine learning approaches to inform budgeting and growth planning.
Collaborate with engineering and product teams to prioritize analytics requirements, embed instrumentation in sprints, and ensure timely release of measurement features.
Maintain and enforce data governance and privacy-compliant measurement practices (GDPR/CCPA), anonymization and consent management for tracking across regions.
Conduct segmentation and cohort analyses to uncover high-value customer behaviors, inform personalization strategies, and guide lifecycle marketing programs.
Optimize site performance and technical SEO elements (page speed, schema markup, sitemaps, robots.txt) with developers and DevOps to improve organic ranking and user experience.
Support creative and content teams by testing messaging variants, CTA placements and content layouts to maximize conversion and engagement metrics.
Monitor competitor digital performance and industry trends, synthesizing insights into recommendations for channel and content strategy adjustments.
Configure and maintain marketing automation connectors and data flows between analytics, CRM, email platforms (e.g., Salesforce, HubSpot, Braze) and advertising platforms for seamless measurement and activation.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis for campaign managers and business stakeholders, delivering clear, actionable outputs under tight timelines.
Contribute to the organization's data strategy and roadmap by identifying gaps in instrumentation, proposing tagging improvements and prioritizing analytics investments.
Collaborate with business units to translate data needs into engineering requirements, acceptance criteria and test plans.
Participate in sprint planning and agile ceremonies within the data engineering and marketing technology teams to ensure analytics work is scoped and delivered.
Train marketing and product teams on analytics tools, dashboard usage, and common analysis techniques to democratize data-driven decision making.
Maintain documentation of tracking implementations, event naming conventions and analytics playbooks to reduce churn and onboarding time for new hires.

Required Skills & Competencies

Hard Skills (Technical)

Google Analytics (GA4) — configuration, event modeling, custom reports and advanced analysis.
Google Tag Manager (GTM) — container design, custom events, data layer implementation and debugging.
SQL — writing complex joins, aggregations, window functions and working in BigQuery, Redshift or Snowflake.
Data visualization — building reports and dashboards in Looker, Tableau, Power BI, or Data Studio with best-practice design.
A/B testing & experimentation platforms — Optimizely, VWO, Google Optimize or internal frameworks, plus statistical test interpretation.
SEO tooling — experience with SEMrush, Ahrefs, Screaming Frog, Google Search Console and on-page/technical SEO best practices.
Paid media analytics — familiarity with Google Ads, Microsoft Ads, Facebook Ads Manager and campaign optimization metrics.
Web performance and technical skills — understanding of page speed optimization, Chrome DevTools, Lighthouse and basic HTML/CSS knowledge.
Marketing automation & CRM integration — HubSpot, Salesforce, Braze, or similar for lifecycle and attribution analysis.
Backend analytics/data stack experience — BigQuery, Snowflake, ETL/ELT concepts, and basic scripting in Python/R for analysis automation.
Tagging QA and data governance — monitoring, alerts, and privacy-compliant instrumentation (GDPR/CCPA).
Familiarity with user behavior tools — Hotjar, FullStory, Crazy Egg for session replay and heatmap analysis.
Excel/Google Sheets — advanced formulas, pivot tables and modeling for ad-hoc analysis.

Soft Skills

Analytical thinking — ability to frame business problems, hypothesize, test and synthesize insights into recommendations.
Communication — strong written and verbal storytelling skills for presenting complex data to non-technical stakeholders.
Cross-functional collaboration — experience working closely with product, engineering, creative and paid performance teams.
Prioritization & project management — manage competing analytics requests, deliverables and deadlines in an agile environment.
Attention to detail — meticulous approach to tagging, QA and data validation to ensure accuracy and trust in reporting.
Curiosity and continuous learning — keeps current with analytics, SEO/SEM, experimentation and martech trends.
Business acumen — understands marketing funnels, unit economics and how analytics translates to revenue and growth metrics.
Problem-solving and troubleshooting — resolves measurement discrepancies and technical issues quickly and effectively.
Stakeholder management — ability to drive alignment and influence strategy through data-driven insights.
Initiative — proactive ownership of measurement gaps, automation opportunities and process improvements.

Education & Experience

Educational Background

Minimum Education:

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

Preferred Education:

Bachelor’s or Master’s degree in Analytics, Data Science, Digital Marketing, or equivalent professional certifications (Google Analytics Individual Qualification, Google Ads certification, SQL/BigQuery certificates).

Relevant Fields of Study:

Marketing Analytics
Data Science / Statistics
Business / Economics
Computer Science / Information Systems

Experience Requirements

Typical Experience Range:

2–5 years of hands-on experience in web analytics, digital marketing analysis, or growth analytics for mid-market or enterprise environments.

Preferred:

3–6+ years with demonstrable experience owning web measurement for marketing channels, implementing GTM and GA4, running A/B tests, and building SQL-driven dashboards. Experience in e-commerce, SaaS, or large consumer web properties is highly desirable.