#marketing-analytics

Develop comprehensive digital marketing strategies with data-driven planning and multi-channel integration. Strategic planning framework: 1. Market analysis: competitor research, target audience personas, SWOT analysis, market size estimation. 2. Goal setting: SMART objectives, KPI definition, revenue targets, ROI expectations (3:1 minimum). 3. Channel selection: owned/earned/paid media mix, budget allocation, channel attribution modeling. Customer journey mapping: 1. Awareness stage: content marketing, SEO, social media presence, brand storytelling. 2. Consideration: email nurturing, retargeting campaigns, comparison content, webinars. 3. Decision: product demos, testimonials, limited-time offers, sales enablement. 4. Retention: loyalty programs, customer success, upselling campaigns. Budget allocation strategy: 1. 80/20 rule: 80% proven channels, 20% experimental, quarterly budget reviews. 2. Channel distribution: search (30%), social (25%), content (20%), email (15%), other (10%). 3. Performance tracking: cost per acquisition (CPA), lifetime value (LTV), attribution modeling. Analytics and measurement: 1. UTM tracking: campaign source, medium, content parameters, Google Analytics integration. 2. Conversion funnel: awareness → interest → consideration → purchase → advocacy. 3. A/B testing: headlines, creative assets, landing pages, 95% statistical significance. Technology stack: CRM integration, marketing automation, attribution tools, customer data platform (CDP) for unified customer view.

Implement advanced marketing analytics for data-driven decision making and campaign optimization. Analytics foundation: 1. Google Analytics 4: event tracking, conversion goals, audience segments, attribution modeling. 2. UTM parameters: campaign tracking, source/medium identification, content performance analysis. 3. Customer data platform: unified customer view, cross-channel attribution, lifetime value calculation. Key performance indicators: 1. Acquisition metrics: cost per acquisition (CPA), customer acquisition cost (CAC), traffic sources. 2. Engagement metrics: session duration, pages per session, bounce rate, social engagement. 3. Conversion metrics: conversion rate, revenue per visitor, average order value, return on ad spend (ROAS). Advanced analytics: 1. Cohort analysis: customer retention, churn analysis, lifetime value trends, behavioral patterns. 2. Multi-touch attribution: customer journey analysis, channel contribution, assisted conversions. 3. Predictive analytics: customer lifetime value prediction, churn probability, purchase propensity. Reporting and visualization: 1. Dashboard creation: real-time metrics, executive summaries, campaign performance, trend analysis. 2. Automated reporting: weekly/monthly reports, anomaly detection, performance alerts. 3. Data storytelling: insights communication, actionable recommendations, stakeholder presentations. Testing framework: 1. A/B testing: statistical significance, sample size calculation, test duration (1-2 weeks minimum). 2. Multivariate testing: multiple elements, interaction effects, complex optimization scenarios. 3. Incrementality testing: true causal impact, geo-experiments, holdout groups. Data integration: CRM connectivity, social media APIs, advertising platforms, marketing automation tools for comprehensive performance analysis.