Advanced Huff Model (Business Analyst)
Summary
Creates a probability surface to predict the sales potential of an area based on distance and attractiveness factors. Creates a probability surface to predict the sales potential of an area based on distance and attractiveness factors
Usage
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The results of the Huff Model can be used to:
- Estimate market potential.
- Define and analyze market potential.
- Assess economic impact of a new site location.
- Forecast sales and potential of existing stores and outlets.
- Assess the impact of competitive and environmental changes on outlet performance.
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The first step to executing this tool is to define a study area that includes all the trade areas of all competing stores being analyzed.
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The Sales Potential Layer is usually a polygon features representing subareas where the potential customers live. Point features can also be used; for example, block centroids that have associated demographic data.
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The Competitive Store Layer should include all competitive locations in a given study area. This layer should also include any of your existing store locations in the study area, since they will act as competitors to a new store location. In most cases, the competitive store layer will be a Business Analyst store layer.
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Competitive store locations can be extracted from the Add Business Listings function in Business Analyst.
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A higher Distance Coefficient indicates that distance will have a greater impact on consumer behavior. For example, consumers are more willing to travel farther for high-order goods, such as automobiles and furniture, than they are for low-order goods, such as groceries.
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The output of the Huff Model generates probabilities and estimated sales for each subgeographic area. The output probabilities can be used to define primary market (trade) areas for a new store location. For example, a trade area can be created using the Dissolve By Attribute tool to create a primary market area that includes all the subgeography areas that have a probability higher than 40 percent of patronizing the new store location.
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The spatial reference of the output feature class will be the same as the Sales Potential Layer.
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The Potential Sales Field measure the attractiveness of a store. The values in this field, also known as predictor values, often include attributes of a store, such as square footage, number of parking spaces, advertising, store hours, prices, age, appearance, signage, accessibility, and so forth.
Syntax
| Parameter | Explanation | Data Type |
SalesPotentialLayer |
The input feature class that contains the data used to calculate the numeric potential of the Huff Model. This is typically expressed in annual sales data. | Feature Layer |
SalesPotentialLayerIDFieldName |
The unique identifier of the sales potential layer. | Field |
PotentialSalesFldName |
The field containing the values used to calculate the sales potential of the Huff Model. | Field |
StoreLayer |
The layer that contains the competitive points (usually stores) used to determine how sales are influenced and distributed across the analysis area. | Feature Layer |
StoreIDField |
The unique identifier of the competitive store layer. | Field |
WayToDefineStoreLocation |
The method used to generate the potential store layer:
| String |
WayToDefineParams |
Input method for the parameters for the Advanced Huff Model:
| String |
DistanceCalculationMethod |
Assigns the method used to calculate distances between geographic areas defined by the potential customer's layer parameter and stores from the competitive stores layer.
| String |
DistanceCoefficient |
The value that determines how much of a factor travel distance is to the consumer. | Double |
AttractionVariables [[Variable, {Potential Store Value}, {Coefficient}],...] |
The values that measure how attractive a store is to consumers. | Value Table |
OutputFeatureClass |
The feature class that will contain the Huff Model results. | Feature Class |
ExtentSourceLayer (Optional) |
The input feature class used to define the extent of the analysis. | Feature Layer |
Longitude (Optional) |
The x-coordinate (longitude) for the potential site. | Double |
Latitude (Optional) |
The y-coordinate (latitude) for the potential site. | Double |
PotentialStoreLayer (Optional) |
The existing point feature class that will be used to define the potential store location. | Feature Layer |
PotentialStoreOID (Optional) |
The unique identifier for the potential store location. | Long |
PathToCalibratedResult (Optional) |
The existing Huff Model calibration file. | Folder |
Code Sample
# Name: HuffModelExample.py
# Description: Analyzes stores in the San Francisco area to determine the estimated annual sales.
# Author: ESRI
# Import system modules
import arcpy
arcpy.ImportToolbox("C:\Program Files\ArcGIS\Desktop10.0\ArcToolbox\Toolboxes\Business Analyst Tools.tbx")
try:
# Acquire extension license
arcpy.CheckOutExtension("Business")
arcpy.CheckOutExtension("Network")
# Define input and output parameters for the Advanced Huff Model tool
SalesLayer = "C:/Program Files/ArcGIS/Desktop10.0/Business Analyst/Data/BDS/esri_bg.bds"
SalesId = "ID"
Potential= "TOTPOP_CY"
CompLayer = "C:/temp/sf_stores.shp"
StoreId = "STORE_ID"
AttractionParam= "SALES 500000 1.75"
OutPath = "C:/temp/Huff_adv.shp"
Extent = "C:/temp/analysis_extent.shp"
# Create Advanced Huff Model
arcpy.HuffModelAdvanced_ba(SalesLayer, SalesId, Potential, CompLayer, StoreId, "BY_COORDINATES", "MANUALLY", "DRIVE_TIME", "-1.5", AttractionParam, OutPath, Extent, "-122.46", "37.76")
# Release extension license
arcpy.CheckInExtension("Business")
arcpy.CheckInExtension("Network")
except:
print arcpy.GetMessages(2)