Retail Analytics Using GIS Training Course

Participants can structure retail datasets for reliable spatial analysis and reporting.

• Relational data model linking stores, customers, transactions and territories
• Unique identifiers, data dictionaries and field-level quality rules
• Address standardisation before geocoding customer and competitor records
• Completeness, accuracy, timeliness and consistency checks for retail datasets
• Joining demographic variables to geographic boundary datasets
• Metadata records documenting source, date, scale and permitted use

Participants can geocode and validate retail locations for site and catchment analysis.

• Batch geocoding workflows for stores, branches, customers and competitors
• Match scores, candidate review and exception handling procedures
• Manual correction of unmatched addresses using authoritative reference layers
• Positional accuracy checks against imagery, roads and parcel boundaries
• Geocoding sensitivity for dense urban addresses and rural settlements
• Privacy controls for customer addresses and personally identifiable information

Participants can create clear retail maps that support operational and investment decisions.

• Base-map selection for site, catchment and network decision contexts
• Graduated symbols, choropleths and heat maps for retail measures
• Classification methods: natural breaks, quantiles, equal intervals and standard deviation
• Labels, annotation and scale choices for executive map readability
• Map legends, north arrows and source notes meeting reporting needs
• Visual hierarchy separating proposed sites from existing network assets

Participants can define and compare trade areas using appropriate retail catchment methods.

• Fixed-radius buffers for preliminary local market screening
• Drive-time polygons based on road networks and travel assumptions
• Walk-time catchments for convenience, pharmacy and urban retail formats
• Customer-origin analysis using geocoded loyalty and transaction records
• Huff gravity model concepts for competitive trade-area estimation
• Trade-area boundaries adjusted for barriers, crossings and local behaviour

Participants can measure customer access and identify gaps in retail or branch coverage.

• Network analyst routes, service areas and origin-destination cost matrices
• Travel-time assumptions by car, walking, transit and delivery vehicle
• Road restrictions, turn penalties and one-way streets within routing
• Coverage measures for population, households and priority customer segments
• Access gaps identified through overlapping service-area polygons
• Isochrone maps communicating travel-time equity and convenience patterns

Participants can estimate local market potential from demographic and socioeconomic indicators.

• Census variables relevant to retail demand, affluence and household structure
• Mosaic-style geodemographic segmentation for customer profiling
• Population growth, daytime population and household formation indicators
• Disposable income, expenditure indices and category-specific spending potential
• Small-area demographic profiling within defined retail catchments
• Market potential index calculations using weighted demographic indicators

Participants can map competitors and assess local competitive intensity around retail sites.

• Competitor taxonomy by format, price point, category and service model
• Point-density analysis revealing clusters of competing retail outlets
• Nearest-neighbour distances measuring immediate competitive proximity
• Competitor counts within drive-time, walking and customer-origin catchments
• Anchor tenants, complementary businesses and destination retail effects
• Market structure maps distinguishing direct, indirect and online competition

Participants can evaluate candidate sites through transparent multi-criteria location scoring.

• Site-selection criteria derived from retail strategy and format requirements
• Weighted linear combination for multi-criteria decision analysis
• Scoring access, visibility, demand, competition, cost and operational fit
• Normalising variables before combining measures with different scales
• Sensitivity testing of weights and threshold assumptions
• Site scorecards documenting evidence, judgement and approval rationale

Participants can use satellite and aerial imagery to assess physical site and market conditions.

• Satellite imagery sources, resolution, revisit frequency and licensing considerations
• Visual interpretation of rooftops, parking, access roads and land use
• Land-cover classification distinguishing built-up, vegetation and open land
• Change detection for construction, redevelopment and settlement expansion
• Night-time lights as a proxy indicator for activity concentration
• Imagery validation of proposed sites and competitor locations

Participants can map performance patterns and diagnose location-related sales variation.

• Sales, transaction, basket and customer metrics linked to store points
• Normalising sales measures by floor area, opening date and format
• Thematic mapping of comparable-store performance and growth trends
• Spatial autocorrelation concepts using Moran's I and local indicators
• Outlier stores identified through performance, demand and access comparisons
• Performance diagnostic narratives separating location factors from operational factors

Participants can identify potential cannibalisation and assess network interaction between outlets.

• Overlapping catchments as an initial cannibalisation risk measure
• Customer migration analysis before and after store openings
• Distance-decay functions estimating likely customer switching behaviour
• Sales transfer assumptions within new-store impact assessments
• Network interaction matrices comparing origin areas and store destinations
• Mitigation options through format differentiation, timing and territory adjustments

Participants can design balanced retail territories using geographic and commercial constraints.

• Territory design objectives: workload, potential, continuity and travel efficiency
• Contiguous territory boundaries built from small geographic units
• Balancing customer counts, sales potential and service workloads
• Natural barriers, administrative limits and account relationships in territory assignment
• Territory compactness measures and travel-time performance indicators
• Scenario comparison for territory realignment and staffing decisions

Participants can identify underserved markets and prioritise expansion opportunities across a network.

• White-space analysis comparing market potential against existing retail coverage
• Supply-demand gaps mapped by catchment, district and grid cell
• Location-allocation principles for new facility placement decisions
• Prioritisation matrices combining potential, feasibility and strategic fit
• Scenario modelling for openings, closures, relocations and format conversions
• Network plans linking proposed actions to measurable coverage targets

Participants can construct spatial inputs for realistic store and branch sales forecasts.

• Forecast input framework covering demand, access, competition and format
• Analog-store selection using comparable market and site characteristics
• Distance-decay assumptions within retail demand allocation models
• Gravity-model inputs for estimating customer attraction and share
• Scenario ranges reflecting opening ramps, competitor response and local growth
• Forecast documentation separating observed data from planning assumptions

Participants can communicate retail location findings through focused maps, dashboards and recommendations.

• Decision questions translated into map layers, indicators and dashboard views
• Key performance indicators for network coverage, potential and site viability
• Interactive filters for store format, geography, segment and scenario
• Executive story maps structuring evidence, findings and recommended actions
• Uncertainty statements covering data limitations and modelling assumptions
• Recommendation memos linking spatial findings to investment decisions

Participants can apply governance controls to retail spatial data, customer information and modelling decisions.

• Data protection principles for geocoded customers and household records
• Aggregation and masking methods protecting sensitive customer locations
• Licensing restrictions for demographic, mobility and imagery datasets
• Bias checks for location models affecting access and investment
• Version control for datasets, maps, models and recommendations
• Approval trails supporting auditability of property and network decisions

Participants can plan a practical retail GIS initiative from scope through operational adoption.

• Problem statements defining decisions, users, geography and required outputs
• Stakeholder mapping across commercial, property, operations and data teams
• Minimum viable dataset specification for a retail GIS project
• Data refresh schedules aligned with network planning and reporting cycles
• Acceptance criteria for maps, models, dashboards and recommendations
• Implementation roadmap covering pilots, governance and user adoption

Participants can build, review and present a complete GIS-based retail network and site-selection recommendation.

• Business brief defining expansion, rationalisation or service-coverage decision
• Integrated dataset containing stores, customers, demographics, competitors and road networks
• Trade-area analysis comparing access, demand and competitive conditions
• Weighted site scorecard ranking candidate locations against agreed criteria
• Network scenario assessing coverage gains and cannibalisation implications
• Executive map pack presenting findings, assumptions, risks and recommendation