Consumer Insights Metrics: Develop a thorough understanding of our product, business and marketing objectives strategy; leverage the same to define and measure the right
User-Level Campaign-Level metrics that could serve as key inputs to marketing strategy evolution and good leading indicators to business and user outcomes. Conduct detailed analyses of consumer/customer behaviours and journeys across all products, devices, channels, and markets to unearth critical insights and opportunities
Cross-functional Collaboration: Partner closely with Marketing teams (Organic / Paid / Lifecycle / Consumer) , MarTech teams and Commercial teams to align on a cohesive and data-driven marketing strategy, measurement frameworks and success metrics; share actionable insights recommendations on user/segment evolution and marketing performance to continuously help enhance optimize marketing ROI
User Segmentation Audience Refinement for Marketing: Build and refine consumer agent segmentation models, identify key micro-segments, enable build of look-alike audiences across various markets and products; work closely with Marketing MarTech teams to then drive enhanced data activation targeted marketing campaigns
Measurement Frameworks for Marketing Effectiveness: Propose, align and build robust analytics frameworks and methodologies to measure the effectiveness of marketing spend and campaigns, including attribution models, market mix models, payback periods, CAC computation, and LTV/Cohort modelling as applicable. Leverage combination of inbuilt and external tools platforms to help operationalize the same
Data Storytelling Presenting Narratives: Critique, contextualize, and communicate data insights to provide actionable recommendations. Answer not only the what but also the why, so what, and now what
Experimentation Champion: Champion and refine experimentation best practices across the various marketing teams, including hypothesis formulation, experiment design, metrics definition, audience selection, uplift measurement
Were looking for someone who:
Analytics Experience: Proven experience in marketing analytics, with a strong foundation on statistics, experimentation, marketing attribution segmentation frameworks.
Experience in e-commerce or digital/consumer product sectors is highly preferred.
Technical Proficiency: Expertise in advanced SQL, data modelling, and familiarity with various BI/Analytics platforms (Looker/ MixPanel/Tableau), Customer Data Platforms (Segment, mParticle), and MarTech/Attribution platforms (Braze, AppsFlyer)
Core Values Own It Deliver It; Respect Care for Each Other; Have Fun Celebrate Success Push Beyond Good; Create Whats Next