Geomarketing Strategy Course

Lesson 1 • Historical Evolution of Geomarketing

Traces geomarketing from paper maps to AI-driven platforms. Provides context for understanding why current tools and methods exist.

Lesson 2 • What Geomarketing Is and Does

Defines geomarketing, its scope, and how spatial thinking transforms marketing strategy. Anchors the chapter by framing geography as a business asset.

Lesson 3 • The Geomarketing Workflow

Outlines the end-to-end process from data collection to strategic recommendation. Sets expectations for the skills developed throughout the course.

Lesson 1 • Vector and Raster Data Models

Explains the two fundamental spatial data models and their respective strengths. Provides the technical vocabulary needed for all subsequent data work.

Lesson 2 • Points of Interest and Business Data

Examines commercial datasets listing physical locations of businesses and amenities. Connects POI data to competitive analysis and site selection.

Lesson 3 • Data Quality and Preprocessing

Addresses common data quality issues and the cleaning steps required before analysis. Ensures students can produce reliable inputs for spatial models.

Lesson 4 • Mobility and Behavioral Data

Introduces GPS traces, mobile signals, and transaction data as behavioural proxies. Establishes how movement data enriches static demographic profiles.

Lesson 1 • Hotspot and Cluster Detection

Introduces statistical methods for identifying geographic concentrations of activity. Connects cluster findings to targeting and resource allocation decisions.

Lesson 2 • Proximity and Buffer Analysis

Teaches distance-based operations to define catchment zones and accessibility. Directly supports trade area delineation covered in later chapters.

Lesson 3 • Spatial Aggregation and Zonal Statistics

Explains how to summarise data within geographic units for comparison. Supports market sizing and performance benchmarking tasks.

Lesson 4 • Spatial Joins and Overlay Operations

Covers techniques for combining multiple spatial layers to enrich datasets. Enables students to link demographic, POI, and behavioural data in one view.

Lesson 1 • Customer-Derived Trade Areas

Uses actual customer address data to empirically define trade areas. Validates model-based zones against observed purchasing behaviour.

Lesson 2 • Gravity and Spatial Interaction Models

Teaches Reilly's Law and Huff Model to predict consumer allocation across locations. Connects probabilistic trade areas to market share estimation.

Lesson 3 • Trade Area Overlap and Cannibalisation

Analyses how overlapping trade areas affect network performance and sales. Directly informs site selection and network optimisation decisions.

Lesson 4 • Simple Geometric Methods

Covers radius rings and drive-time polygons as fast, practical delineation tools. Introduces limitations that motivate more advanced gravity models.

Lesson 1 • Mapping and Visualising Segments

Translates segment assignments into thematic maps for strategic communication. Connects segmentation outputs to targeting and media planning workflows.

Lesson 2 • Building Custom Segmentation Models

Guides students through creating proprietary segments using clustering algorithms. Produces segments tailored to a specific brand's customer base.

Lesson 3 • Principles of Geographic Segmentation

Explains how geography refines traditional segmentation by adding spatial context. Establishes the logic connecting place, lifestyle, and consumer behaviour.

Lesson 4 • Segment-Based Targeting and Activation

Converts segment maps into actionable targeting lists for media and field teams. Closes the loop between analysis and marketing execution.

Lesson 1 • Predictive Sales Modelling for Sites

Uses regression and machine learning to forecast revenue at candidate locations. Connects spatial inputs to financial projections for business cases.

Lesson 2 • Scoring and Ranking Candidate Sites

Builds a quantitative scoring model that ranks locations by composite suitability. Enables objective, repeatable site comparison across large candidate sets.

Lesson 3 • Site Selection Criteria and Frameworks

Defines the business, demographic, and competitive factors used to evaluate locations. Provides a structured framework applied throughout the chapter.

Lesson 4 • Network Optimisation and Rationalisation

Applies optimisation techniques to improve network efficiency and profitability. Addresses both expansion and closure decisions within a portfolio.

Lesson 1 • Direct Mail and Physical Media Planning

Applies trade area and segment data to optimise direct mail and out-of-home placements. Connects spatial outputs to traditional media buying workflows.

Lesson 2 • Spatial Targeting Strategy

Defines how geographic prioritisation improves campaign efficiency and ROI. Establishes the targeting logic that drives all subsequent campaign decisions.

Lesson 3 • Territory Design and Sales Force Alignment

Uses spatial balancing methods to create equitable and efficient sales territories. Supports field team productivity and fair quota assignment.

Lesson 4 • Digital Geotargeting and Geofencing

Covers location-based digital advertising techniques including geofencing and radius targeting. Links online campaign mechanics to offline spatial strategy.

Lesson 1 • Customer Journey Spatial Analysis

Maps multi-touchpoint customer paths through physical and digital spaces. Reveals spatial patterns in the path to purchase for strategic optimisation.

Lesson 2 • Predictive Spatial Modelling

Extends regression to spatial econometric models that account for geographic dependence. Produces more accurate forecasts than aspatial alternatives.

Lesson 3 • Real-Time Location Analytics

Introduces streaming location data pipelines and real-time decision triggers. Prepares students for dynamic, event-driven geomarketing applications.

Lesson 4 • Scenario Modelling and Strategic Simulation

Builds what-if models to test strategic decisions before committing resources. Integrates all prior analytical skills into a strategic advisory output.