Manager, Media Analytics & Insights

Blend360•Columbia, MD

About The Position

Blend is seeking a Manager of Media Analytics & Insights to join our CX & MarTech function. This person will lead the analysis and interpretation of paid, owned, and earned media performance, helping clients understand what happened, why it happened, and what actions they should take next. The Manager will serve as a strategic analytics partner to client media, marketing, and measurement teams. You will oversee campaign reporting, performance diagnostics, test-and-learn analysis, and the development of actionable recommendations across channels including paid search, paid social, programmatic, display, video, connected television, and other digital and offline media. This is not simply a reporting role. The Manager will be responsible for transforming fragmented campaign, audience, creative, and business data into clear insights that improve media strategy, optimization, and investment decisions. You will lead client engagements, manage and develop analysts, establish standards for media analytics delivery, and help strengthen Blend’s broader media analytics and measurement capabilities.

Requirements

Approximately 5–8 years of experience in media analytics, marketing analytics, digital analytics, advertising effectiveness, or a related field.
Experience analyzing performance across multiple media channels, such as paid search, paid social, programmatic, display, video, connected television, audio, or offline media.
Experience leading analytics projects and managing or mentoring analysts.
Strong understanding of media metrics, campaign structures, buying approaches, optimization levers, and platform reporting.
Demonstrated ability to move beyond descriptive reporting and develop actionable insights and recommendations.
Experience developing campaign measurement plans, KPI frameworks, analytical requirements, and performance reporting strategies.
Strong understanding of the marketing funnel and how channel objectives and KPIs differ across awareness, consideration, acquisition, and retention.
Familiarity with attribution, incrementality testing, experimentation, and marketing mix modeling, including the strengths and limitations of each.
Experience identifying and resolving campaign data, tracking, taxonomy, or reporting issues.
Strong client-facing communication, presentation, facilitation, and stakeholder-management skills.
Ability to structure ambiguous business questions into practical analytical approaches.
Ability to manage multiple priorities and deliver high-quality work in a consulting or client-services environment.
Bachelor’s degree in analytics, statistics, economics, marketing, business, mathematics, computer science, or a related field, or equivalent professional experience.
Media platforms such as Google Ads, Campaign Manager 360, Display & Video 360, Meta Ads Manager, LinkedIn Campaign Manager, Amazon Ads, The Trade Desk, or similar platforms
Ad servers, demand-side platforms, social platforms, and media-planning or buying systems
Adobe Analytics, Google Analytics 4, or similar digital analytics platforms
SQL and cloud data environments such as Snowflake, Databricks, or BigQuery
Data visualization platforms such as Tableau, Power BI, or Looker
Media data aggregation and reporting platforms
Experimentation, conversion-lift, brand-lift, or geo-testing methodologies
Marketing mix modeling, multi-touch attribution, or other marketing-effectiveness approaches
Python or R for advanced analysis and automation
Sufficient technical fluency to interrogate campaign data, guide analytical work, identify measurement risks, and collaborate effectively with media, data, and technology specialists.

Nice To Haves

Consulting, media agency, advertising agency, or other client-services experience.
Experience leading media analytics across multiple clients, brands, markets, or business units.
Experience working directly with media planners, buyers, activation teams, and marketing leaders.
Experience integrating media-platform data with site, CRM, sales, customer, or other business-outcome data.
Experience evaluating audience, creative, channel, and campaign performance.
Experience contributing to proposals, statements of work, solution design, or account growth.
Experience in one or more industries such as financial services, healthcare, retail, telecommunications, travel, technology, or consumer products.
Familiarity with emerging uses of AI in campaign analysis, insight generation, optimization, and media operations.

Responsibilities

Lead media analytics projects from initial business question through analysis, insight development, and client activation.
Translate client objectives and campaign strategies into measurement plans, analytical requirements, and prioritized workstreams.
Serve as a primary analytics partner to client media, marketing, agency, and measurement stakeholders.
Manage project scope, timelines, risks, dependencies, and stakeholder expectations across one or more engagements.
Ensure that media analytics deliverables are accurate, strategically relevant, and connected to clear business decisions.
Identify opportunities to expand client relationships by connecting campaign analysis to broader measurement, customer analytics, and marketing technology needs.
Oversee recurring and ad hoc analysis of media campaigns across paid search, paid social, programmatic, display, online video, connected television, audio, direct partnerships, and offline channels.
Develop weekly, monthly, quarterly, and campaign-level performance narratives that clearly explain what happened, why performance changed, and what should happen next.
Diagnose performance shifts using channel, campaign, audience, placement, publisher, geography, device, funnel-stage, and creative-level analysis.
Evaluate media performance against campaign objectives, benchmarks, forecasts, and historical trends.
Identify emerging opportunities, performance risks, and inefficient investment before they become material issues.
Distinguish meaningful performance signals from normal variation, tracking issues, or misleading platform-reported results.
Translate complex campaign data into clear, actionable recommendations for media planners, channel owners, marketers, and executives.
Identify opportunities to improve budget allocation, audience strategy, channel mix, creative performance, frequency management, and campaign execution.
Partner with media teams to develop and evaluate optimization hypotheses.
Assess whether optimization decisions are supported by sufficient evidence and clearly communicate limitations or uncertainty.
Track whether recommendations were implemented and evaluate their subsequent impact.
Connect media metrics such as impressions, reach, engagement, traffic, and conversions to broader customer and business outcomes.
Build measurement frameworks and KPI structures aligned to campaign strategy, audience objectives, and business goals.
Define success metrics and evaluation approaches for awareness, consideration, acquisition, engagement, conversion, and retention campaigns.
Develop campaign learning agendas that establish the questions each campaign or test is expected to answer.
Support test-and-learn programs by defining hypotheses, success criteria, test designs, and analytical readouts.
Guide the interpretation of A/B tests, platform lift studies, geo experiments, audience tests, and creative tests.
Help clients understand the appropriate roles and limitations of platform reporting, attribution, incrementality testing, marketing mix modeling, and other measurement approaches.
Partner with data science and measurement teams on integrated solutions that connect campaign performance analysis with causal and business-outcome measurement.
Oversee the integrity, completeness, and consistency of campaign data used for reporting and analysis.
Identify and resolve discrepancies across media platforms, ad servers, site analytics, agency reports, and client data environments.
Establish quality-assurance processes for campaign naming, taxonomies, tracking parameters, KPI definitions, and reporting outputs.
Partner with media operations, analytics implementation, engineering, and MarTech teams to resolve tracking and data-quality issues.
Document analytical assumptions, known data limitations, and implications for interpretation.
Improve reporting and analytical processes through automation, standardization, and reusable tools.
Build strong relationships with client media, marketing, brand, agency, finance, analytics, and technology stakeholders.
Serve as a strategic connection point among media activation teams, marketing scientists, data scientists, and business leaders.
Facilitate working sessions that align stakeholders on campaign objectives, measurement priorities, performance findings, and recommended actions.
Communicate analytical findings clearly to both technical and nontechnical audiences.
Constructively challenge unsupported conclusions, weak measurement assumptions, or optimization decisions that are not grounded in evidence.
Help clients establish more effective operating rhythms between campaign execution, performance analysis, and strategic decision-making.
Manage and mentor analysts and senior analysts supporting media analytics engagements.
Provide clear direction on analytical approaches, priorities, and expected outputs.
Review analyses and deliverables for technical accuracy, analytical depth, strategic relevance, and communication quality.
Help team members develop stronger media knowledge, analytical judgment, business acumen, and client-consulting skills.
Create a collaborative environment with clear accountability, constructive feedback, and opportunities for professional growth.
Contribute to the development of Blend’s media analytics methods, accelerators, case studies, training materials, and points of view.