Senior Organic Analytics Manager

Senior Organic Analytics Manager

The Senior Organic Analytics Manager is the primary day-to-day analytics partner for SEO, AEO, organic content, and DXP/CRO measurement within Channel Analytics. Working under the direction of the Sr. Director, Channel Analytics, this person leads analytical execution, develops measurement approaches, defines business and reporting requirements, conducts deep-dive analyses, and translates findings into clear recommendations. They partner closely with Analytics Solutions, which develops production dashboards, as well as SEO/AEO, Digital Experience, CRO, CRM, Data Engineering, and other analytics stakeholders. The role measures and evaluates organic strategy; it does not own SEO/content execution.

What You Will Do

• Lead monthly Organic MBR analysis and recurring performance diagnosis across SEO, AEO, website/DXP, and the organic funnel, including traffic, leads, applications/enrollments where available, conversion, YoY/MoM drivers, where performance is concentrated, opportunities, and risks.

• Analyze SEO performance using GA4, Google Search Console, and SEO platforms, including impressions, clicks, CTR, rankings/visibility, branded vs. non-branded demand where useful, landing-page/content performance, and where performance gains or declines are concentrated.

• Lead AEO measurement across AI visibility, citations, Citation Share/Share of Voice, prompts/topics, engine-level performance, AI referral traffic, competitive/source analysis, and downstream outcomes; partner with Profound or similar platform data as available.

• Design measurement for AEO, SEO, DXP, and CRO initiatives by establishing baselines, intervention dates, comparison groups or matched controls where appropriate, and post-launch reads; evaluate uncertainty, confounding, and whether observed changes are reasonably attributable to the intervention.

• Measure website and funnel performance from organic/AI discovery through landing-page behavior, forms, leads, applications, and enrollments; distinguish traffic-driven changes from conversion-driven changes and evaluate DXP migrations, site releases, and CRO changes.

• Reconcile GA4/GSC/SEO/AEO/CRM data, investigate material Organic performance changes, identify tracking or taxonomy issues before results reach leadership, and translate findings into 2–4 decision-ready insights rather than metric dumps.

• Define KPI logic, reporting requirements, analytical views, intervention/change logs, and data-quality needs; partner with Antonio/Analytics Solutions and Data Engineering to bring GA4, GSC, AEO platform, Salesforce, and intervention data into scalable reporting and Databricks-based workflows rather than relying on manual Excel processes.

What Success Looks Like

• Organic MBR analysis is delivered with clear drivers, concentrations, business implications, and recommended actions, allowing the Sr. Director to review and sharpen the story rather than perform the first-pass analysis.

• SEO, AEO, and DXP performance can be connected from visibility and search demand through website behavior, leads, applications, and enrollments, with known data limitations clearly documented.

• AEO reporting moves from manual snapshots toward a scalable history and measurement process with clear hero metrics, engine-level views, prompt/topic and URL-level analysis, intervention tracking, and credible post-launch reads.

• Material Organic, content, and website changes can be diagnosed quickly, including whether movement reflects demand, visibility, traffic quality, conversion, tracking, taxonomy, or maturation effects.

• The Senior Manager becomes the primary day-to-day analytics partner for Organic, AEO, and Digital Experience stakeholders, increasing Channel Analytics capacity while the Sr. Director retains overall strategy, prioritization, and cross-channel accountability.

How Impact Will be Measured

• Reliability, adoption, and usefulness of Organic MBR analysis and recurring SEO, AEO, DXP/CRO, and funnel reporting.

• Quality of business requirements, KPI definitions, analytical specifications, and data QA provided to Analytics Solutions and Data Engineering.

• Improved visibility into organic traffic quality, search/content effectiveness, AI-search performance, website conversion, and progression through application and enrollment.

• Quality and credibility of pilot, test, migration, and rollout measurement, including appropriate treatment of baselines, comparison groups, intervention timing, uncertainty, and confounding.

• Clarity and actionability of recommendations and evidence that insights influence SEO/AEO, content, DXP/CRO, partner, and prioritization decisions.

• Reduction in repetitive manual analysis and stakeholder confidence in the Organic analytics story presented to leadership.

What You’ll Bring to the Team

Experience & Skills That Matter Most (Required)

• 6+ years of hands-on experience in digital/web analytics, organic/SEO analytics, marketing analytics, or a closely related data-driven environment, with demonstrated strength diagnosing performance rather than only producing reports.

• Advanced SQL skills and the ability to independently pull, join, QA, and investigate complex web, marketing, and CRM datasets in cloud data environments.

• Strong analytical proficiency with GA4 and Google Search Console plus working knowledge of SEO data/tools such as Ahrefs, Semrush, or equivalent; understand traffic sources, landing pages, events, funnels, rankings/visibility, queries, content performance, and technical SEO concepts.

• Strong funnel analytics skills, including the ability to connect sessions and website behavior to leads, applications, enrollments, conversion rates, cohort/maturation considerations, and known attribution or identity-resolution limitations.

• Strong analytical diagnosis, data QA, and executive storytelling skills: identify whether unusual results are real or caused by tracking/taxonomy issues and translate findings into what happened, why, where it is concentrated, and what should happen next.

• Experience defining KPI logic, business requirements, and reporting specifications for BI/Analytics Solutions teams; strong Excel skills and enough data-visualization fluency to design useful reporting without being the production dashboard developer.

• Working knowledge of experimentation and causal measurement concepts, including pre/post design, control or matched-comparison groups, confounding, uncertainty/statistical significance, and the limits of correlation; deep experimental-design expertise is not required.

Experience That’s Great to Have (Preferred)

• AEO/generative-search literacy, including citations vs. mentions, prompts and prompt themes, AI visibility/Share of Voice, source attribution, branded vs. non-branded prompts, engine differences, AI referrals, zero-click/offsite discovery, and experience with Profound, Ahrefs Brand Radar, Semrush AI visibility tools, or similar platforms.

• Deeper experimentation/causal-inference experience, including matched controls, difference-in-differences, natural experiments, incrementality, or rollout measurement; Python or R experience for large-scale prompt/citation analysis, URL classification, topic clustering, or competitor analysis is also valuable.

• Experience with Databricks, BigQuery, Snowflake, Salesforce data, Power BI, GSC/API data, web scraping/log-file analysis, DXP/CRO teams, or higher-educ