Senior CRM Manager

Senior CRM Manager

Core responsibilities

• Own the CRM platform: configuration, data structure, integrations and access.
• Define the customer data model and keep it segmented by behaviour, demographics and lifecycle stage.
• Define and track CRM KPIs with Product, Marketing and Analytics stakeholders, and agree the targets each campaign is held to.
• Set the lifecycle strategy across onboarding, activation, renewal and win-back, and decide which channels carry it.
• Support data-driven decisions across teams by turning CRM data into recommendations leadership can act on.
• Direct the Junior CRM Manager: set priorities, review campaign work before it ships, and raise the team's technical standard.

Day-to-day responsibilities

• Set up and maintain engagement channels (email, push, in-app, SMS) and the templates behind them.
• Own workflow automation inside the CRM: triggers, sequences, scoring and suppression rules.
• Build and run lifecycle and retention campaigns end to end, including segmentation, testing and post-campaign read-outs.
• Produce CRM performance reports and dashboards for leadership on a fixed weekly and monthly cadence.
• Run exploratory analysis on customer behaviour to find trends worth acting on, and present findings to non-technical stakeholders.
• Build ad-hoc predictive models where they change a decision, such as churn risk or propensity to renew.
• Own resolution of customer queries and complaints that come through CRM touchpoints, and fix the process that caused them.
• Product or marketing analytics that do not feed a CRM segment, campaign or touchpoint.

What we are looking for

• 7+ years in CRM, lifecycle or retention marketing, including ownership of a CRM platform end to end.
• Hands-on administration of a major CRM or engagement platform: segmentation, automation builder, integrations, data hygiene.
• A record of lifecycle programmes you designed and shipped; with the retention or revenue numbers they moved.
• SQL strong enough to pull and validate your own segments without waiting on Analytics.
• Comfort presenting to leadership and translating customer data into a recommendation, not just a chart.
• Experience with predictive modelling (churn, propensity, LTV) or close partnership with a data science team.
• Experience setting standards for, or mentoring, a junior CRM hire.
• Python or R for ad-hoc analysis.