> For the complete documentation index, see [llms.txt](https://docs.growthfactor.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.growthfactor.ai/manage/my-stores.md). # 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: | Column | Description | | ------------------ | -------------------------- | | **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 | Field | Description | Used For | | ------------------ | ----------------------------------------- | ----------------------------------------- | | **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 | *** ### Editing Stores Keep your store data current to ensure accurate analysis across the platform. #### How to Edit 1. Locate the store in Table View or Map View 2. Click the **edit icon** (pencil) next to the store 3. Update any fields in the Edit Store modal 4. Click **Save Changes** #### Editable Fields All core fields can be modified: * Store Number * Square Footage * Address, City, State, ZIP Code * Annual Sales * Open Date #### 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 *** ### Deleting Stores Remove stores that are no longer part of your portfolio: 1. Locate the store in Table View 2. Click the delete option 3. 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. #### Map Layers Your stores appear on the Site Analysis map via the **All Stores** layer, 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. **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), contact your GrowthFactor team at to have it excluded from comparisons. *** ### Bulk Updates For large-scale data updates (annual sales refresh, 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: * **Site Analysis:** Stores appear on maps and power analog comparisons * **Sales Projections:** Store performance drives revenue forecasts * **Cannibalization:** Store locations determine overlap analysis * **Deal Dashboard:** Compare pipeline opportunities against your existing portfolio --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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