Head of Commercial Analytics

My client is a long-established Irish consumer services business with a substantial national customer base and a strong presence across membership, protection, insurance and assistance-related products. The business is undergoing a significant period of commercial development, with a particular focus on improving customer value, strengthening retention, increasing acquisition efficiency and making better use of data across the customer lifecycle.

About the Role

They are now seeking a Senior Customer Growth Manager to take ownership of the insight, analytics and customer growth agenda across a high-volume personal lines environment. This is a senior commercial role for someone who can turn complex data into clear, practical recommendations that influence decision-making. The successful candidate will work across customer analytics, CRM, digital performance, acquisition, renewals, pricing, retention and commercial strategy. This is not a reporting role. My client needs someone who can use data to shape what happens next: where to invest, which customers to target, which journeys to improve, where leakage is occurring, and how commercial teams should respond. The role will suit a highly analytical, commercially minded candidate who has operated in a fast-moving consumer, insurance, financial services, subscription, utilities, telecoms or similar high-volume trading environment.

Responsibilities

• Leading the customer growth analytics agenda across acquisition, retention, renewals, cross-sell and customer value.
• Using customer, pricing, behavioural and trading data to identify opportunities to improve conversion, retention, persistency and overall customer lifetime value.
• Analysing renewal journeys and identifying where customers are being lost, where save activity can be improved, and where targeted interventions will have the greatest impact.
• Improving acquisition performance across digital, direct and partner channels by assessing conversion, cost of acquisition, customer quality and quote-to-sale performance.
• Developing data-led recommendations that influence channel investment, campaign targeting, pricing decisions and operational priorities.
• Building and refining customer segmentation approaches to identify high-value, high-risk and high-potential customer groups.
• Working with churn, propensity, lifetime value and behavioural models to support smarter acquisition and retention activity.
• Establishing structured testing frameworks for campaigns and customer interventions, including hypotheses, control groups, success measures and post-campaign analysis.
• Translating test results into clear commercial actions that can be adopted by marketing, sales, digital, pricing and operational teams.
• Acting as a senior voice for customer insight, ensuring that commercial decisions are supported by evidence rather than instinct.
• Identifying early warning signs in customer behaviour, such as increased switching, reduced conversion, emerging churn risk or changes in channel performance.
• Using CRM and behavioural data to understand where sales, renewals and retention activity are succeeding or failing.
• Developing next-best-action recommendations to support more relevant customer contact, better timing and improved commercial outcomes.
• Analysing digital customer journeys to identify friction points, switching behaviour, drop-off patterns and opportunities for personalisation.
• Supporting the development of attribution models to help the business understand which activity is driving profitable growth.
• Identifying cross-sell, bundling and multi-product opportunities using customer value, behavioural and product holding data.
• Using insight to improve the performance of product panels, pricing approaches and partner relationships.
• Ensuring that acquisition, retention and customer growth activity is aligned with relevant regulatory requirements and customer outcome expectations.
• Supporting fair value analysis and identifying any customer outcome risks that may emerge from pricing, renewal or retention activity.
• Creating a clear growth MI framework that gives senior stakeholders meaningful visibility of performance, trends, risks and opportunities.
• Presenting complex analysis in a simple, commercial and persuasive way to senior leadership and cross-functional teams.
• Helping embed a more data-driven commercial culture across the organisation.

Qualifications

• 7–10 years’ experience in a high-volume, commercially focused trading environment.
• Strong experience across customer retention, renewals, acquisition, CRM, customer analytics or commercial performance.
• A proven track record of using data to improve conversion, reduce churn, increase retention or improve customer persistency.
• Experience working with large customer datasets and turning analysis into practical commercial recommendations.
• Strong understanding of customer lifecycle performance, including acquisition, onboarding, engagement, renewal, retention and cross-sell.
• Experience working with customer segmentation, churn analysis, propensity models or customer lifetime value analysis.
• A strong understanding of how pricing, customer behaviour, channel performance and retention activity interact.
• Experience identifying customer switching behaviour and the signals that suggest a customer is likely to leave.
• Strong analytical capability, with the ability to spot trends, question assumptions and explain findings clearly.
• Experience operating in a regulated environment, ideally within insurance, financial services or another consumer-facing regulated sector.
• An understanding of Irish consumer protection requirements, or the ability to quickly interpret and apply regulatory expectations.
• Strong stakeholder management skills, with the ability to influence senior commercial, marketing, digital, pricing and operational colleagues.
• The ability to challenge decisions constructively and support alternative recommendations with evidence.
• Excellent communication skills, with the ability to turn complex data into clear business narratives.

Required Skills

• Experience within insurance, financial services, utilities, telecoms, subscription services, motoring services or another high-volume consumer environment.
• Experience with BI and analytics tools such as Power BI, Tableau or similar.
• Experience building, commissioning or interpreting dashboards and commercial MI.
• Familiarity with CRM platforms and customer campaign management.
• Experience with statistical or predictive modelling, such as churn scoring, propensity modelling, decision trees or logistic regression.
• Exposure to digital analytics, UX testing, conversion rate optimisation or customer journey analysis.
• Knowledge of product panel economics, partner performance, pricing optimisation or remarketing activity.
• Experience embedding data and insight into everyday operational decision-making.
• Strong understanding of customer risk frameworks and how data can be used to identify potential customer outcome issues.

Preferred Skills

The following would be advantageous:

• Experience within insurance, financial services, utilities, telecoms, subscription services, motoring services or another high-volume consumer environment.