Marketing and Customer Insight Analyst

Job description

Chill Insurance are currently on the lookout for a Marketing and Customer Insight Analyst to join our team. About the Company Chill Insurance Limited (“Chill”) is a multi-channel insurance intermediary regulated by the Central Bank of Ireland. Founded in 2007, Chill has scaled to become one of Ireland’s leading insurance intermediaries. Chill Insurance is backed by Private Equity house Livingbridge and having invested significantly in the infrastructure and operational teams in the business we are now in a position to take advantage of a number of opportunities (both organic and acquisitive) which should lead to a more than doubling in the size of the business in the coming few years. Chill’s sister companies include Quote Devil Insurance, an insurance intermediary, and Ivernia Insurance Ltd, an MGA insurer . The finance team support all three businesses and the consolidated Three Rock Group parent entities and this role will provide support across the full group. Purpose Own and embed TRG’s behavioural segmentation and customer decisioning frameworks, ensuring they translate into clear, commercially impactful CRM strategies. This role acts as the internal authority on how customer behaviour is defined, segmented, and activated—driving the shift toward data-led personalisation, next-best-action (NBA), and propensity-driven marketing across the customer lifecycle. Operating as a senior individual contributor, the role provides analytical leadership and decisioning frameworks that directly shape CRM performance and commercial outcomes. KEY RESPONSIBILITIES Behavioural Segmentation Ownership Act as the internal SME and owner of TRG’s behavioural segmentation model. Validate, challenge, and approve segmentation methodology, outputs, and ongoing evolution. Translate segments into clear commercial strategies across acquisition, conversion, retention, and cross-sell. Ensure segmentation is consistently and effectively applied across CRM and marketing activity. Decisioning, NBA & Personalisation Define and evolve next-best-action (NBA) frameworks and decisioning logic. Establish how behavioural data, segmentation, and context drive: Targeting; Timing; Message and proposition Develop scalable personalisation approaches that move beyond static campaigns to behaviour-led journeys. Ensure decisioning logic is embedded within CRM execution. Propensity Modelling & Activation Identify and prioritise key propensity use cases (e.g. conversion, churn, cross-sell). Translate model outputs into actionable CRM rules, triggers, and journey design. Ensure propensity-led strategies are measurable and continuously optimised. Insight-Led Optimisation & Testing Define and lead the test-and-learn roadmap , ensuring strong hypotheses and statistical rigour. Analyse customer journeys to identify drop-offs, triggers, and optimisation opportunities. Provide clear recommendations to improve enquiry generation, conversion, and retention. Performance & Commercial Insight Develop performance frameworks linking segments, decisioning, and campaigns to commercial outcomes . Produce clear, actionable insight on what is driving performance and where to focus next. Evaluate effectiveness of segmentation, NBA, and propensity approaches. Data & Martech Enablement Define requirements for data and Martech to support segmentation, decisioning, and personalisation. Ensure data structures enable accurate targeting, measurement, and optimisation. Partner with technical teams to embed decisioning into CRM workflows. Cross-Functional Influence Act as the go-to expert on behavioural insight and customer decisioning. Influence CRM, Data, and Marketing teams to adopt segmentation-led and test-and-learn approaches. Support the successful activation of segmentation within day-to-day CRM delivery. CORE SKILLS Strong analytical capability — confident with SQL and data visualisation. Working knowledge of Python or similar tools to explore data, validate outputs, and interrogate model performance (not required to build models from scratch). Strong understanding of propensity modelling, predictive analytics, and AI-driven decisioning concepts (e.g. classification models, uplift modelling, next-best-action frameworks). Familiarity with AI-enabled marketing approaches (e.g. real-time decisioning, recommendation engines, automated content optimisation). Ability to interpret, challenge, and refine model outputs and ensure they translate into practical marketing applications. Experience translating segmentation, behavioural data, and model outputs into CRM strategies and journeys . Understanding of personalisation and decisioning systems , including how rules and models interact in execution. Strong commercial mindset — able to prioritise activity based on value impact. Excellent communicator — able to simplify complex analytics into clear business actions. Experience working with CRM and marketing automation platforms.