Manager - Analytics

Job Requirements

Job Description: Manager Analytics & Personalization

Location: Bengaluru, India

Function: eCommerce – D2C

Reporting to: Head of D2C

Role Overview

We are looking for a data-driven, business-oriented Manager – Analytics & Personalization who will build and optimize algorithms to improve ROAS (Return on Ad Spend), strengthen CRM performance, track digital brand metrics, and drive growth through smarter retargeting and funnel optimization. This role will sit at the intersection of brand building and performance marketing, ensuring data and personalization fuel both immediate revenue and long-term brand equity.

Key Responsibilities

1. Algorithm Development & ROAS Optimization

• Build and deploy algorithms to determine and improve ROAS across paid channels.
• Partner with Paid Media and Affiliate teams to run experiments, track marginal returns, and guide investment allocations.
• Create predictive and prescriptive models for customer acquisition and retention efficiency.

2. Funnel Analytics & Drop-Off Insights

• Develop a statistical view of customer drop-offs across website and app funnels.
• Identify friction points in PDP, cart, and checkout journeys.
• Partner with product, UX, and marketing teams to design interventions that reduce drop-offs and improve conversions.

3. CRM & Personalization

• Work closely with CRM and Retention teams to improve segmentation, targeting, and personalization across channels (Email, WhatsApp, App Push, Web).
• Build propensity and RFM models to improve re-targeting efficiency.
• Collaborate with Martech teams to integrate personalization strategies across website, app, and campaigns.

4. Retargeting Strategy

• Optimize retargeting algorithms for abandoned carts, lapsed customers, and high-value cohorts.
• Design experiments to test creative + audience + frequency combinations for efficiency and scale.

5. Digital Brand Metrics, Data Enrichment & Insights

• Track and analyze digital brand health metrics, including:
•  - Share of Search (SoS) – brand searches vs competitors.
•  - Impression Share & Share of Voice (SOV) across paid and organic channels.
•  - Brand Lift Studies (awareness, recall, consideration).
•  - Engagement & sentiment metrics across social and content platforms.
• Enrich first-party data (CDP, CRM, app/web interactions) to create a unified customer view and uncover brand perception drivers.
• Build optimization frameworks that connect upper-funnel brand investments to mid- and lower-funnel outcomes (e.g., awareness traffic conversion).
• Partner with brand, CRM, and media teams to design experiments that measure how brand campaigns influence consideration, repeat visits, and loyalty.
• Ensure a stronger tie-in between brand building and performance outcomes — translating awareness and engagement into measurable business impact.
• Develop dashboards linking brand metrics to business KPIs, ensuring both performance (ROAS) and brand health are optimized simultaneously.

6. Analytics & Decision Support

• Create advanced dashboards and reports for leadership to monitor ROAS, CRM KPIs, funnel health, and brand outcomes.
• Provide data-backed recommendations to marketing, product, and business teams.
• Drive A/B test analytics and hypothesis validation for growth initiatives.

Work Experience

Key Skills & Competencies

• Strong expertise in data analytics, statistics, and predictive modeling.
• Hands-on experience with SQL, Python/R, GA4, CRM/CDP platforms, brand lift & digital measurement tools, and visualization platforms (Tableau/Power BI/Looker).
• Solid understanding of digital marketing metrics (CTR, CPC, ROAS, CVR, CPM) as well as brand metrics (SoS, Impression Share, Brand Lift, Engagement).
• Experience with funnel optimization, retargeting, and personalization algorithms.
• Strong business acumen: ability to connect brand building with performance outcomes.
• Analytical problem-solver with a structured, hypothesis-driven approach.
• Excellent collaboration and stakeholder management skills.

Qualifications

• MBA or Master’s in Analytics / Data Science / Marketing / related field preferred.
• 2–4 years of relevant experience in eCommerce, digital marketing analytics, personalization, or CRM optimization.
• Prior experience in consumer internet, D2C, or retail/eCommerce is a strong plus.