My Stores
My Stores is your central hub for managing your existing location portfolio. View, edit, and organize all your stores in one place—keeping the data that powers your sales projections, cannibalization analysis, and analog modeling accurate and up to date.
Accessing My Stores
Navigate to My Stores in the left sidebar under the Manage section. The page displays all locations in your organization's store database.
Views
Toggle between two views depending on your task:
Table View
Displays stores in a spreadsheet-style format with sortable columns:
Number
Store number or identifier
Address
Street address
City
City name
State
State abbreviation
Zip
ZIP code
Square Footage
Store size in square feet
Sales
Annual sales figure
Open Date
Date the store opened
Sorting: Click any column header to sort ascending or descending. This helps you quickly find stores by location, performance, size, or tenure.
Searching: Use the search bar to filter stores by address, city, or other attributes. Results update as you type.
Map View
Displays all stores as pins on an interactive map. This view helps you:
Visualize your geographic footprint
Identify regional clusters and coverage gaps
Understand spatial relationships between locations
Plan expansion in the context of existing stores
Click any pin to view that store's details.
Store Information
Each store record contains the following fields:
Core Fields
Store Number
Your internal identifier for the location
Reference and organization
Address
Street address
Geocoding, mapping, and location analysis
City
City name
Location identification
State
State
Regional filtering and analysis
ZIP Code
Postal code
Geographic grouping
Square Footage
Store size
Sales PSF calculations, analog matching
Annual Sales
Revenue figure
Analog modeling, sales projections
Open Date
When the store opened
Maturity assessment, analog filtering
Tags
Tags are customizable labels you assign to stores for filtering and organization. Common tag categories include:
Geography: Region, state, urban/suburban/rural
Format: Store type, size tier, prototype version
Performance: Top performer, underperformer, new store
Characteristics: Drive-through, mall location, freestanding
Tags are flexible—create whatever categories help you segment your portfolio meaningfully.
Editing Stores
Keep your store data current to ensure accurate analysis across the platform.
How to Edit
Locate the store in Table View or Map View
Click the edit icon (pencil) next to the store
Update any fields in the Edit Store modal
Click Save Changes
Editable Fields
All core fields can be modified:
Store Number
Square Footage
Address, City, State, ZIP Code
Annual Sales
Open Date
Tags
When to Update
Update store records when:
Sales figures change: Refresh annual sales with current actuals for accurate projections
Store renovations: Update square footage if the store expands or contracts
Corrections: Fix any data entry errors discovered during analysis
Reclassification: Add or modify tags as your segmentation strategy evolves
Managing Tags
Tags enable powerful filtering throughout the platform. When you filter by tags in Quick Search, only matching stores are used for analog comparisons and appear as filtered pins on the map.
Adding Tags
Open the Edit Store modal for any location
Click the Tags dropdown
Start typing to search existing tags or create a new one
Select a tag to apply it, or choose "Create [tag name]" to add a new tag
Save changes
Removing Tags
Open the Edit Store modal
Click the X next to any tag to remove it
Save changes
Tag Strategy
Design tags that support your analysis workflow:
Filter for regional analogs:
Tag stores by state or region → Filter to compare a Texas site only against Texas stores
Segment by format:
Tag stores as "Urban," "Suburban," "Rural" → Filter to compare similar site types
Exclude outliers:
Tag stores affected by unusual circumstances (construction, temporary closure) → Exclude them from analog sets
Track performance tiers:
Tag stores as "Top Quartile," "New Store," etc. → Quickly identify comparison groups
Deleting Stores
Remove stores that are no longer part of your portfolio:
Locate the store in Table View
Click the delete option
Confirm deletion
Caution: Deleted stores are removed from your database and will no longer appear in analog modeling, cannibalization analysis, or map views. Only delete stores that have permanently closed or were entered in error.
How Store Data Powers the Platform
Your store database is the foundation for key platform features:
Sales Projections
Analog modeling compares searched sites against your existing stores. Accurate sales and square footage data directly impacts projection quality.
Sales figures determine performance benchmarks
Square footage enables PSF calculations
Location attributes drive similarity matching
Cannibalization Analysis
The platform calculates trade area overlap between searched sites and your existing stores. Store locations must be accurate for meaningful cannibalization estimates.
Filtering and Comparisons
When you apply tag-based filters in Quick Search:
Only stores matching your filter criteria are used as analogs
Filtered stores appear as purple pins on the map
Projections recalculate based on the filtered comparison set
Map Layers
Your stores appear on the Quick Search map via the All Stores and Filtered Stores layers, providing context when evaluating new sites.
Data Quality Best Practices
Keep sales current. Outdated sales figures skew projections. Update annually at minimum, or more frequently if your business is seasonal or rapidly changing.
Verify addresses. Incorrect addresses affect geocoding, which impacts trade area analysis and cannibalization calculations. Ensure addresses are complete and accurate.
Use consistent tagging. Establish tag naming conventions and apply them consistently. "TX" and "Texas" as separate tags fragments your data.
Audit periodically. Review your store database quarterly to catch closures, relocations, or data errors before they affect analysis.
Document unusual stores. If a store has circumstances that make it a poor analog (temporary construction impact, non-standard format), tag it so you can exclude it from comparisons when appropriate.
Bulk Updates
For large-scale data updates (annual sales refresh, new tag rollout, portfolio restructuring), contact your GrowthFactor team. Bulk imports and updates can be processed to avoid manual entry for large portfolios.
Related Features
Store data integrates with:
Quick Search: Stores appear on maps and power analog comparisons
Sales Projections: Store performance drives revenue forecasts
Cannibalization: Store locations determine overlap analysis
Filters: Tags enable filtered analog sets
Deal Dashboard: Compare pipeline opportunities against your existing portfolio
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