Loyalty Analytics Manager - Hybrid | Insight-Driven Retention

Harnham; Greater London; Hybrid; GBP 45,000 - 75,000; Full time

Benefits offered by this job

Hybrid work model

Competitive benefits

Job summary

Harnham is seeking a Marketing Analytics Manager (Loyalty) to own the loyalty analytics agenda, guiding retention, frequency and lifetime value through insights and segmentation. The role leads reporting and testing across loyalty initiatives.

Based in London with hybrid work (2 days per week in Central London), you will collaborate with Marketing, Ecommerce, Product and Data Science to maximise programme performance and influence senior stakeholders.

Qualifications

• Strong SQL and data visualization experience.
• Experience in marketing analytics within a consumer-facing environment.
• Good understanding of loyalty and CRM metrics, including retention, CLV, segmentation, and RFM.
• Ability to influence senior stakeholders and communicate complex insights clearly.
• Python experience is advantageous but not essential.

Responsibilities

• Defining the loyalty analytics strategy and influencing customer decision-making
• Driving customer segmentation and measuring the impact of loyalty initiatives
• Supporting personalised targeting, promotions, and CRM activity
• Building and enhancing reporting using SQL, Power BI, and Databricks
• Designing and evaluating tests across loyalty, rewards, and communications
• Partnering with Marketing, Ecommerce, Product, and Data Science teams to maximise programme performance

Skills

SQL

Data visualization

Marketing analytics

Stakeholder communication

Python

Tools

Power BI

Databricks

SQL

Job description

Harnham is seeking a Marketing Analytics Manager (Loyalty) to own the loyalty analytics agenda, guiding retention, frequency and lifetime value through insights and segmentation. The role leads reporting and testing across loyalty initiatives.

Based in London with hybrid work (2 days per week in Central London), you will collaborate with Marketing, Ecommerce, Product and Data Science to maximise programme performance and influence senior stakeholders.