This is a newly created role to manage a team of analysts to deliver reporting, MI and insights across the span of the commercial team. While the team remains relatively small (i.e. 2/3 analysts) it is anticipated that the ‘Head of’ role will also undertake and deliver some analysis and may own some aspects of regular reporting.
Candidates will have a strong commercial understanding (e.g. marketing return on investment, pricing levers) and a good understanding of the marketing and business development life cycle. Financial Services experience required.
This team’s output is a critical input to understanding the performance of current and future customer and commercial activities and to making timely decisions in order to improve effectiveness and make both tactical commercial decisions and as input to longer term strategic questions.
This role will establish close relationships with the key decision makers in the commercial team and develop a clear understanding of their priorities and challenges so that the analytics team can be focussed on supporting their needs. Manage team to deliver MI, reporting and analysis to support commercial performance including:
Manage team to deliver insight on customer behaviour behaviours / outcomes including:
- Marketing reporting, campaign analysis and marketing RoI
- Distribution performance (new business & retention), including intermediary analysis
- Developments in existing customer base (e.g. increased contributions, insolvencies etc
- Forecasting to manage demand & inform commercial planning
Support the development & implementation of routine reporting to:
- Product decisions (e.g. investment choice, retirement decisions, use of advice etc)
- Member outcomes (e.g. forecasts vs retirement target)
- Usage of online customer portals , public website etc
- employers providing insights about their workforce
- Advisers providing data & insights about their clients
- Excel expert
- Good working knowledge of Power BI (or reporting/visualization tools e.g. Cognos, Tableaux)
- Google Analytics - basic working knowledge
- Familiarity with analytics toolkits (e.g. Python, R, SAS)
- Understanding of Data Lakes
- Background/Good working knowledge of structured data methodologies
- Marketing automation tools