Sales Analysis Course

Lesson 1 • Sales Data Sources and Types

Maps the landscape of data sources feeding sales analysis. Distinguishes structured from unstructured data and primary from secondary sources.

Lesson 2 • What Sales Analysis Means

Defines sales analysis and its role in business decision-making. Establishes shared vocabulary used throughout the course.

Lesson 3 • The Sales Analysis Workflow

Outlines the end-to-end process from question framing to insight delivery. Provides a repeatable framework applied in every subsequent chapter.

Lesson 1 • Structuring Data for Analysis

Teaches normalization, field naming, and table relationships for sales datasets. Proper structure accelerates every analysis technique covered later.

Lesson 2 • Data Cleaning Fundamentals

Addresses duplicate records, missing values, and inconsistent formatting. Establishes quality standards that prevent downstream analytical errors.

Lesson 3 • Data Validation and Quality Checks

Introduces validation rules and audit techniques to confirm data integrity. Students apply checks before any metric calculation begins.

Lesson 1 • Cohort and Cross-Tab Analysis

Groups customers by acquisition period and cross-tabulates variables to find patterns. Extends descriptive analysis into multi-dimensional comparisons.

Lesson 2 • Summarizing Sales Performance

Uses totals, averages, medians, and distributions to describe sales outcomes. Builds the baseline view of performance used in all comparative analyses.

Lesson 3 • Time-Based Sales Analysis

Analyzes sales across daily, weekly, monthly, and annual periods. Establishes period-over-period comparison skills used in trend analysis.

Lesson 4 • Segmentation and Grouping

Breaks sales data into meaningful segments by product, region, channel, and rep. Segmentation reveals performance differences hidden in aggregate numbers.

Lesson 1 • Forecast Accuracy and Error Metrics

Introduces MAE, MAPE, and RMSE to measure and improve forecast quality. Accurate error measurement is essential before forecasts inform business plans.

Lesson 2 • Seasonality and Cyclicality

Decomposes sales time series into seasonal and cyclical components. Enables accurate period comparisons by removing seasonal distortion.

Lesson 3 • Forecasting Fundamentals

Covers naive, moving-average, and exponential smoothing forecast models. Students select the appropriate model based on data characteristics.

Lesson 4 • Scenario and Assumption-Based Forecasting

Builds best-case, base-case, and worst-case forecast scenarios using variable assumptions. Prepares students to communicate forecast uncertainty to decision-makers.

Lesson 1 • Sales Funnel Structure and Stages

Defines standard funnel stages from lead to closed deal and maps data to each. Provides the structural foundation for all pipeline metrics.

Lesson 2 • Win/Loss Analysis

Examines closed-won and closed-lost deals to surface competitive and process patterns. Findings directly inform sales strategy and coaching priorities.

Lesson 3 • Pipeline Velocity and Deal Aging

Measures how fast deals move through the pipeline and flags stalled opportunities. Velocity metrics connect pipeline health to revenue timing.

Lesson 4 • Conversion Rate Analysis by Stage

Calculates stage-to-stage conversion rates and identifies where deals stall. Pinpoints the highest-leverage improvement opportunities in the pipeline.

Lesson 1 • Customer Lifetime Value Analysis

Calculates historical and predictive customer lifetime value (CLV) using purchase data. CLV guides acquisition investment and retention prioritization decisions.

Lesson 2 • Customer Revenue Segmentation

Segments customers by revenue, frequency, and recency using RFM and tiering methods. Enables targeted retention and growth strategies for each segment.

Lesson 3 • Churn and Retention Analysis

Measures customer churn rate, retention rate, and survival curves over time. Identifies early warning signals that precede customer attrition.

Lesson 4 • Product and SKU Performance Analysis

Ranks products by revenue, margin, and growth rate to guide portfolio decisions. Connects product performance to customer segment preferences.

Lesson 1 • Building a Sales Performance Dashboard

Assembles KPIs into a structured dashboard layout optimized for management review. Applies data visualization principles to maximize insight delivery speed.

Lesson 2 • Performance Variance Analysis

Decomposes gaps between actual and target performance into volume, price, and mix effects. Variance analysis directs corrective action to the right root cause.

Lesson 3 • Benchmarking and Target Setting

Uses historical data and industry references to set realistic, motivating performance targets. Proper benchmarking prevents both sandbagging and unachievable goals.

Lesson 4 • Individual and Team Scorecards

Builds rep-level and team-level scorecards using quota attainment, activity, and pipeline metrics. Scorecards create accountability and coaching focus.

Lesson 1 • Building Executive-Level Recommendations

Structures analytical findings into concise, evidence-based recommendations for senior leaders. Applies the pyramid principle and data storytelling to maximize impact.

Lesson 2 • Market and Competitive Analysis

Integrates external market data with internal sales data to assess competitive position. Provides context that transforms internal metrics into strategic intelligence.

Lesson 3 • Territory and Quota Analysis

Evaluates territory balance using market potential, workload, and historical performance data. Analytical territory design improves equity and revenue coverage.

Lesson 4 • Go-to-Market Effectiveness Analysis

Measures channel, segment, and campaign ROI to evaluate go-to-market strategy performance. Connects sales analysis to marketing and product investment decisions.