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Key Responsibilities and Required Skills for Advertising Analyst

💰 $ - $

AdvertisingAnalyticsMarketing

🎯 Role Definition

The Advertising Analyst is a data-driven marketing professional responsible for measuring, analyzing, optimizing, and reporting on digital advertising campaigns across programmatic, paid search, paid social, and display channels. This role blends ad operations, analytics, and strategic insights to maximize campaign performance, ROI/ROAS, and marketing impact. The Advertising Analyst partners closely with media buyers, marketing managers, creative teams, and engineering to implement tracking, troubleshoot delivery issues, and translate campaign data into actionable recommendations.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Digital Marketing Coordinator with exposure to paid media reporting.
  • Junior Data/Marketing Analyst supporting campaign measurement.
  • Ad Operations Assistant or Media Trafficking Coordinator.

Advancement To:

  • Senior Advertising Analyst / Senior Media Analyst
  • Programmatic Lead or Paid Media Manager
  • Marketing Analytics Manager or Media Strategy Manager
  • Measurement & Attribution Lead or Head of Ad Operations

Lateral Moves:

  • Paid Search Specialist / SEM Manager
  • Paid Social Manager / Social Advertising Lead
  • Analytics Engineer or Data Analyst focused on marketing data

Core Responsibilities

Primary Functions

  • Manage end-to-end campaign setup, trafficking, and launch across platforms such as Google Ads, DV360, Campaign Manager (CM360), Meta Ads Manager, and major DSPs; ensure targeting, creatives, budgets, and pacing align with media plans.
  • Build, maintain, and QA campaign tagging and conversion tracking using Google Tag Manager (GTM), server-side tracking, and pixel implementations to ensure accurate cross-channel measurement.
  • Design, develop, and maintain automated reporting dashboards in Looker, Tableau, Power BI or Data Studio that surface KPIs (CTR, CPC, CPM, CPA, ROAS, conversion rate) for media and executive stakeholders.
  • Analyze campaign performance daily and weekly to identify optimization opportunities—adjust bids, audiences, creatives, and budgets to improve ROI and meet KPIs.
  • Implement and evaluate A/B and multivariate tests for creative, landing pages, and bidding strategies; translate test results into scalable optimization recommendations.
  • Conduct deep-dive analyses into audience segmentation, funnel drop-off, and lifetime value to inform targeting strategies and audience expansion for acquisition and retention programs.
  • Reconcile campaign spend, delivery discrepancies, and billing across ad servers, DSPs, and internal systems; work with finance to resolve invoicing and attribution mismatches.
  • Execute media pacing and delivery audits to ensure campaigns hit impression and conversion goals while remaining within daily and total budgets.
  • Partner with data engineering and analytics to integrate advertising data into the centralized data warehouse (BigQuery, Snowflake) and maintain ETL pipelines for near-real-time reporting.
  • Develop and maintain advanced SQL queries and data models to support attribution, cohort analysis, and cross-channel performance measurement.
  • Conduct multi-touch attribution modeling and implement measurement frameworks (last-click vs. data-driven attribution) to quantify incremental impact of advertising.
  • Create and present clear, actionable performance reports and insights to cross-functional stakeholders including marketing, product, and senior leadership.
  • Monitor and manage creative performance and ad quality metrics; coordinate with creative teams to iterate on messaging, assets, and formats that drive higher engagement and conversions.
  • Troubleshoot campaign delivery issues (creative rejections, tracking failures, low impressions) and coordinate remediation with platforms and technical teams.
  • Automate repetitive reporting and data quality checks using scripts (Python, Apps Script) to increase efficiency and reduce time to insight.
  • Forecast campaign performance and provide budget allocation recommendations to maximize reach, conversions, and ROI across channels.
  • Maintain up-to-date knowledge of privacy, consent and ad policy changes (GDPR, CCPA, iOS/ATT) and advise on measurement and targeting implications.
  • Support media planning by modeling scenarios, lifetime value (LTV) projections, and incremental lift analyses to inform bid strategies and audience investments.
  • Ensure campaign tagging taxonomy and naming conventions are consistent and documented for reliable cross-platform analysis and governance.
  • Perform competitive and market analysis using third-party tools and industry benchmarks to inform creative and media strategy.
  • Lead post-campaign analyses and create executive-facing recaps that summarize performance, learnings, and recommended next steps for future campaigns.
  • Evaluate emerging ad technologies (connected TV, audio, new DSP features) and pilot tests to expand channel mix and identify new performance opportunities.
  • Drive process improvements and best practices for ad operations, reporting cadence, and cross-functional collaboration to streamline media execution and decision-making.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Create and update documentation, runbooks, and SOPs for campaign setup, tagging, and reporting processes.
  • Assist in vendor evaluation and platform onboarding by documenting technical requirements and measurement capabilities.
  • Mentor junior analysts and share best practices for campaign analytics, reporting templates, and troubleshooting techniques.

Required Skills & Competencies

Hard Skills (Technical)

  • Proficiency in digital advertising platforms: Google Ads, Campaign Manager (CM360), Display & Video 360 (DV360), Meta/Instagram Ads Manager, The Trade Desk or other DSPs.
  • Strong SQL skills for data extraction, transformation, and cohort analysis in relational databases and cloud warehouses (BigQuery, Snowflake, Redshift).
  • Experience with analytics platforms: Google Analytics (GA4), Adobe Analytics, or similar tools for web and app measurement.
  • Advanced Excel skills: pivot tables, VLOOKUP/XLOOKUP, array formulas, and model building for budget and performance analysis.
  • Dashboarding and visualization: Looker, Tableau, Power BI, or Data Studio to craft executive and operational reports.
  • Tagging and tracking: Google Tag Manager (GTM), server-side tagging, pixels, UTM best practices, and event instrumentation.
  • Familiarity with attribution models, media mix modeling, and lift testing methodologies.
  • Programming/scripting: Python or R for automation, data cleaning, and statistical analysis (pandas, numpy, scipy).
  • Understanding of programmatic ecosystem: DSPs, SSPs, ad exchanges, PMP, RTB, and header bidding fundamentals.
  • A/B testing and experimentation platforms: Optimizely, Google Optimize, or internal experimentation frameworks.
  • Basic SQL + experience with ETL/BI pipelines and familiarity with data warehousing concepts.
  • Knowledge of privacy/compliance implications on measurement (consent management, device ID deprecation, cookieless strategies).
  • Experience reconciling ad server logs and measuring discrepancies between platforms.
  • Familiarity with bid strategies, automated bidding, and audience targeting techniques across paid search and paid social.

Soft Skills

  • Strong analytical and quantitative problem-solving abilities with a focus on actionable insights.
  • Excellent verbal and written communication; able to translate complex data into business recommendations for non-technical stakeholders.
  • Detail-oriented with a mindset for QA, accuracy, and process-driven execution.
  • Collaborative team player who partners effectively with media buyers, engineering, product, and creative teams.
  • Time management and prioritization skills in fast-paced, deadline-driven environments.
  • Curiosity and continuous learning orientation to stay current with ad tech and measurement trends.
  • Stakeholder management and presentation skills for regular status updates and executive briefings.
  • Initiative and ownership mindset—proactively identifies opportunities and drives execution end-to-end.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Marketing, Advertising, Statistics, Economics, Mathematics, Computer Science, Data Science, or related field.

Preferred Education:

  • Master's degree in Marketing Analytics, Data Science, Business Analytics, or an MBA with analytics emphasis.
  • Industry certifications such as Google Ads, Google Analytics (GA4), Display & Video 360, Meta Blueprint, or IAB programmatic certifications.

Relevant Fields of Study:

  • Marketing, Advertising, or Communications
  • Data Science, Statistics, Analytics, or Applied Mathematics
  • Computer Science or Information Systems
  • Economics, Business, or Finance

Experience Requirements

Typical Experience Range: 2–5 years working in digital advertising, ad operations, or marketing analytics; programmatic exposure preferred.

Preferred:

  • 3+ years of hands-on experience managing and analyzing paid media campaigns across multiple channels (search, social, display, programmatic).
  • Demonstrated experience building dashboards, automating reports, and delivering actionable insights that drove measurable business results.
  • Prior work with data warehouses (BigQuery, Snowflake), SQL-based analysis, and cross-platform attribution or lift studies.
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