Assistant Manager - CRM

Assistant Manager – Customer Growth& CRM Lifecycle

About the Role

We are looking for a data-driven and customer-centric Assistant Manager – Customer Growth & CRM Lifecycle with 2.5–5 years of experience, preferably in E-commerce or M-commerce, to drive repeat customer growth, retention, and CRM-led revenue across Tata CLiQ Fashion and Luxury.

This role will own customer growth by identifying high-impact customer cohorts, building lifecycle strategies, and delivering personalized communications across CRM channels. The role will work closely with Business, Category, Product, Technology, Analytics, and Loyalty teams to improve repeat purchases, customer lifetime value, and channel effectiveness.

What You’ll Do

Customer Growth & Retention:

• Drive repeat customer growth, retention, purchase frequency and CRM-led revenue.
• Develop cohort-based strategies across new, active, repeat, dormant and high-value customers.
• Build lifecycle journeys covering onboarding, second purchase, repeat purchase, cross-sell, loyalty and win-back.
• Translate business revenue targets into customer, cohort and CRM plans.

CRM Lifecycle & Campaign Management:

• Plan and execute personalized campaigns across Push Notifications, WhatsApp, SMS, RCS, Email, In-App Messages, App Inbox and Native Displays.
• Own the CRM campaign calendar aligned to business priorities and customer lifecycle stages.
• Ensure campaigns are targeted, personalized, tested and delivered with high quality and accuracy.
• Continuously optimize communication frequency, channel mix and customer experience.

CRM Channel Health & Platform Ownership:

• Own channel health metrics including reachability, deliverability, CTR, conversion, engagement, unsubscribe rates and customer fatigue.
• Monitor channel-wise revenue contribution, ROI and ROAS and identify optimization opportunities.
• Manage CRM platform capabilities, data quality, campaign automation and journey orchestration.
• Work with Product and Technology teams to implement new triggers, personalization capabilities and platform enhancements.

Analytics & Experimentation:

• Analyze customer behaviour, campaign performance and lifecycle movement to identify growth opportunities.
• Measure key KPIs including repeat customers, retention rate, reactivation, purchase frequency, orders per customer, CRM GMV, CTR, conversion and ROAS.
• Conduct A/B tests and experiments to continuously improve customer engagement and business performance.
• Develop and leverage machine learning models and predictive analytics for churn prediction, customer reactivation, purchase propensity, customer lifetime value (CLV) and next-best-action recommendations.
• Build dashboards and present actionable insights to stakeholders.

Cross-Functional Collaboration:

• Partner with Business, Category, Product, Technology, Customer Service, Analytics and Creative teams to deliver customer growth initiatives.
• Collaborate with stakeholders to develop relevant customer offers, improve customer experience and resolve campaign or platform issues.
• Benchmark industry best practices and recommend new CRM capabilities, automation and customer engagement initiatives.

Skills We Are Looking For

Technical Skills:

• SQL & Data Analysis: Strong proficiency in SQL, including complex joins, CTEs, aggregations, and customer-level data analysis.
• Python: Working knowledge of Python, particularly Pandas and NumPy, for data manipulation, analysis, and workflow automation.
• Statistical Analysis & Experimentation: Understanding of descriptive statistics, regression analysis, hypothesis testing, A/B testing, and campaign uplift and incrementality analysis.
• Data Visualization & Reporting: Proficiency in Excel, including Pivot Tables and VLOOKUP/XLOOKUP, and experience with BI tools such as Power BI or Tableau for dashboard development and performance reporting.
• Automation & Analytics: Ability to automate recurring reports, data extracts, campaign performance tracking, and analytical workflows using SQL and Python.
• Data Science & Machine Learning: Understanding of predictive modelling techniques for customer segmentation, churn prediction, customer lifetime value (CLV), purchase propensity, and customer reactivation.

Desired Skills:

• Passion for customer growth, retention, and lifecycle marketing in E-commerce/M-commerce.
• Strong analytical thinking, problem-solving skills, and a data-driven approach to decision-making.
• Understanding of customer cohorts, RFM segmentation, loyalty programs, repeat purchase behaviour, and customer lifetime value.
• Familiarity with regression analysis, data science, and machine learning models for customer targeting and campaign optimization.
• Knowledge of CRM campaign measurement, customer journey analysis, and cross-channel performance optimization.
• Awareness of AI-driven personalization, recommendation systems, and next-best-action frameworks.
• Ability to translate customer insights into actionable CRM strategies and measurable business outcomes.

Key Success Metrics

• Repeat Customer Growth
• Retention & Reactivation Rate
• CRM-led GMV & Revenue
• Purchase Frequency & Orders per Customer
• Channel Health (Reachability, Deliverability, CTR, Conversion)
• Channel ROAS & Campaign ROI
• Automation & Lifecycle Journey Contribution
• Customer Engagement & Personalization Effectiveness