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.

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.

Key Responsibilities

The Senior Customer Growth Manager will be responsible for:

  • 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.

Requirements

The successful candidate should have:

  • 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.

Desirable Experience

The following would be advantageous:

  • 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.

The Person

My client is looking for someone who is analytical, commercially sharp and confident working at senior level. The right person will not simply produce reports; they will use insight to change decisions, improve customer outcomes and drive measurable commercial growth.

This role would suit someone who enjoys working in a fast-paced environment where data, customer behaviour and commercial performance are closely connected. The successful candidate will be comfortable challenging assumptions, testing new approaches and helping the business make smarter decisions about how it acquires, retains and grows its customer base.

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