Summary  
This chapter covers implementing code to instrument and capture user events throughout a multi-step process, calculate key performance metrics like drop-off rates and value metrics, and segment data by attributes to identify friction points.

General domain of usage  
E-commerce

**E-commerce analytics** is the process of tracking and analyzing online shopping behavior to improve sales performance and the customer experience.

Definition

### Common E-Commerce Metrics
- **Average Order Value (AOV)**: the average amount each customer spends per order;
- **Customer Lifetime Value (CLV)**: how much revenue the average customer generates over their entire relationship with your brand;
- **Device performance**: mobile vs. desktop;
- **Cart abandonment**: how many customers add items but don't buy.

E-commerce analytics gives businesses a clear, data-driven understanding of how people shop online, from the moment they view a product to the moment they buy (and buy again). By tracking the sales funnel, analyzing device behavior, monitoring cart abandonment, and focusing on value-based metrics like AOV and CLV, companies can remove friction, improve the shopping experience, and make smarter decisions about where to invest time and budget.

Which actions directly reduce checkout friction? (Select two)

Gain a structured understanding of how marketing performance is measured, analyzed, and improved across channels. The material covers essential metrics, tracking frameworks, and analytics tools used to evaluate web, SEO, social, paid media, email, and e-commerce performance. It also explores data preparation, dashboarding, attribution models, experimentation, and forecasting. By connecting insights to budget decisions and ROI optimization, the focus shifts from reporting numbers to driving smarter, evidence-based marketing decisions.

Build the essential groundwork for working confidently with marketing data. Explore how performance is measured, how reliable tracking systems are structured, which platforms power modern analytics, and why responsible data handling matters. By the end, you'll understand not just what to measure, but how to collect accurate insights and use them ethically to support smarter marketing decisions.

Break down how performance is measured across key digital channels. Learn how to evaluate traffic quality, engagement signals, paid efficiency, email performance, and online sales behavior. The focus is on understanding how each channel contributes to growth and how to compare them using meaningful, channel-specific metrics.

Here, you'll move from raw numbers to actionable insight. Learn how to structure datasets, build clear dashboards, interpret patterns, automate reporting workflows, and translate findings into decisions. The emphasis is on clarity, accuracy, and turning complex data into strategic direction.

Explore how to evaluate multi-touch customer journeys, run structured experiments, forecast future performance, and allocate budget for maximum return. The goal is to move from reactive analysis to proactive, data-driven decision-making.

E-commerce Performance Tracking

Common E-Commerce Metrics

1. Which actions directly reduce checkout friction? (Select two)

2. Match the funnel stage to its insight