Job Summary
IITIL is seeking a highly analytical and business-focused Analytics Head to establish and lead the organization’s marketing, sales, customer, digital, and business-performance analytics function.
The Analytics Head will be responsible for creating a reliable measurement framework, integrating data from multiple platforms, building executive dashboards, improving attribution and forecasting, and converting data into actionable business insights.
This role will work closely with leadership, marketing, sales, CRM, finance, and business teams to improve decision-making, performance visibility, operational efficiency, and revenue growth. The ideal candidate combines advanced analytical capabilities with commercial understanding and can communicate complex findings in a clear and decision-oriented manner.
Key Responsibilities Analytics Strategy
- Define and execute IITIL’s analytics strategy aligned with business, marketing, sales, and customer objectives.
- Establish a roadmap for data integration, reporting, dashboards, attribution, forecasting, and advanced analytics.
- Define how performance should be measured across campaigns, channels, customer segments, accounts, services, and markets.
- Create an analytics operating model covering data ownership, governance, reporting standards, and stakeholder access.
- Identify high-impact use cases where analytics can improve growth, productivity, and decision-making.
Measurement Framework and KPI Governance
- Define key performance indicators for brand, content, social media, lead generation, CRM, sales, and customer engagement.
- Establish consistent business definitions, calculation methods, targets, and reporting frequencies.
- Create a centralized metric dictionary and reporting governance framework.
- Ensure teams use consistent and trusted data in reviews and decision-making.
- Review existing metrics and eliminate conflicting or low-value reporting.
Marketing and Campaign Analytics
- Measure campaign reach, engagement, conversion, lead quality, pipeline contribution, revenue influence, and return on investment.
- Analyse performance across paid media, search, social media, email, events, webinars, content, and account-based programs.
- Develop multi-touch and source-based attribution approaches appropriate for enterprise sales cycles.
- Identify the audiences, channels, messages, and assets that drive the strongest outcomes.
- Recommend campaign and budget optimizations based on performance data.
Sales and Revenue Analytics
- Build analytics around pipeline, conversion, sales velocity, win rates, deal size, forecast accuracy, and revenue performance.
- Analyse performance by region, industry, service line, account segment, source, and sales stage.
- Identify pipeline bottlenecks and revenue risks.
- Partner with sales leaders to improve forecasting, resource allocation, and account prioritization.
- Develop models that support opportunity scoring and pipeline planning.
Customer and Account Analytics
- Build account-level views combining engagement, campaign, sales, opportunity, and customer data.
- Identify high-potential accounts, buying signals, engagement trends, cross-sell opportunities, and churn indicators.
- Support account-based marketing and strategic account programs with actionable insights.
- Develop segmentation models based on industry, company size, behavior, needs, and commercial value.
- Analyse customer journeys and lifecycle performance.
Digital and Content Analytics
- Analyse website traffic, search visibility, user behavior, content engagement, conversions, and digital journeys.
- Measure the performance of blogs, reports, case studies, videos, landing pages, and thought-leadership assets.
- Identify content gaps, high-performing themes, audience interests, and conversion opportunities.
- Work with content, social media, and digital teams to improve engagement and organic growth.
- Develop dashboards for website and content performance.
Data Integration and Quality
- Partner with CRM, IT, marketing operations, and business teams to integrate data from relevant systems.
- Define data requirements, source-of-truth rules, validation standards, and refresh schedules.
- Monitor data accuracy, completeness, consistency, and reliability.
- Resolve discrepancies across CRM, advertising, marketing automation, web analytics, finance, and other platforms.
- Build documented and auditable data pipelines and reporting processes.
Dashboards and Business Reporting
- Develop executive, operational, and campaign-level dashboards.
- Automate recurring reports wherever possible.
- Present insights through clear narratives, visualizations, trends, risks, and recommended actions.
- Tailor reporting for leadership, marketing, sales, and operational audiences.
- Support monthly, quarterly, and annual business reviews.
Forecasting and Advanced Analytics
- Build forecasting models for leads, pipeline, conversions, revenue, and campaign outcomes.
- Develop lead-scoring, account-prioritization, propensity, and segmentation models.
- Apply statistical techniques to identify patterns, correlations, and performance drivers.
- Explore responsible use of artificial intelligence and machine learning for prediction and insight generation.
- Continuously test and improve model accuracy.
Team and Stakeholder Leadership
- Build and manage a team of business analysts, marketing analysts, data analysts, and reporting specialists.
- Partner with leadership, finance, sales, marketing, CRM, and technology teams.
- Translate stakeholder questions into analytical requirements and decision-ready outputs.
- Build analytical capability among business teams through training and self-service reporting.
- Manage analytics vendors, data providers, consultants, and technology partners.
Required Qualifications
- Bachelor’s degree in Statistics, Mathematics, Economics, Data Science, Business Analytics, Engineering, Computer Science, or a related field.
- 10+ years of experience in business analytics, marketing analytics, sales analytics, revenue operations, or data analysis.
- 5+ years of experience leading analytics teams or functions.
- Experience in B2B technology, SaaS, IT services, consulting, or enterprise business environments is preferred.
- Strong experience in CRM analytics, web analytics, campaign measurement, business intelligence, and data visualization.
- Working knowledge of SQL, spreadsheet modelling, forecasting, segmentation, and analytical tools.
- Proven ability to integrate and validate data from multiple business systems.
- Strong commercial judgment, communication, presentation, and stakeholder-management skills.
Preferred Skills
- Analytics strategy and KPI governance
- Marketing and campaign analytics
- Sales, pipeline, and revenue analytics
- Customer and account segmentation
- Attribution and performance measurement
- Forecasting and predictive modelling
- Dashboarding and data visualization
- SQL and advanced spreadsheet modelling
- CRM, web analytics, and business-intelligence platforms
- Data integration, quality, and governance
- AI and machine-learning applications in analytics
- Ability to translate complex data into practical business recommendations
Work Location: Remote
