Huff Model Calibration By Real Data (Business Analyst)
Summary
Statistically calibrates the Huff Model using observed customer data for each store location in the study area.
Learn more about how Huff Model Calibration By Real Data works
Usage
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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 calibration output of this tool is used as an input for the Advanced Huff Model.
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The customer data must contain information from a sample of households in each subgeography area within the study area. There must be customer data for each existing and competitive store location in the study area. The customer information is converted in the model to proportions for each subgeography area.
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The Potential Customers Geographic Level parameter value is usually polygon features representing subareas where potential customers live. You can also input point features; 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.Learn more about adding business listings
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Store Attraction Fields, 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 on.
Syntax
| Parameter | Explanation | Data Type |
PotenCustGeogLevel |
Polygon features representing subareas where potential customers live. Point features (for example, block centroids) that have associated demographic data can also be used. | Feature Layer |
GeogIDField |
The unique identifier of the Potential Customers Geographic Level. | Field |
CustomersWithAssignedStoreID |
Point features (typically a Business Analyst customer file) containing customer data and an associated store ID. | Feature Layer |
AssociatedStoreID |
The store ID field in the customer layer that assigns each customer to a store. | 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 |
StoreAttractionFields [StoreAttractionFields,...] |
The values that measure how attractive a store is to consumers. | Field |
DistanceCalculationMethod |
Assigns the method used to calculate distances between geographic areas defined by the potential customers layer parameter and stores from the competitive store layer.
| String |
OutputCalibrationFolder |
The output folder that will contain the Huff Model calibration result file. | Folder |
AnalizeSelectedCustomersOnly (Optional) |
Uses only selected features to generate the Huff Model Calibration By Real Data.
| Boolean |
ExcludeOutlyingCustomers (Optional) |
Optionally sets a cutoff distance to remove outlying points from the model.
| Boolean |
CutoffDistance (Optional) |
The threshold to exclude outlying customers from the analysis. | Double |
MeasureUnits (Optional) |
The units used with the distance values. By default, the units defined in the Business Analyst preferences will be selected.
| String |
NeedReportOutput (Optional) |
Generates a Huff model calibration report based on real data.
| Boolean |
ReportTitle (Optional) |
The report title for the calibration report | String |
ReportFile (Optional) |
The name for the calibration report file. | String |
ReportFormats [ReportFormats,...] (Optional) |
Format of the output report. More than one format may be selected.
| String |
Code Sample
# Name: HuffModelCalibrationByRealData.py
# Description: Generates a calibrated model around two San Francisco stores using Sales as a predictor.
# Author: Esri
# Import system modules
import arcview
import arcpy
arcpy.ImportToolbox("C:\Program Files (x86)\ArcGIS\Desktop10.2\Business Analyst\ArcToolbox\Toolboxes\Business Analyst Tools.tbx")
try:
# Acquire extension license
arcpy.CheckOutExtension("Business")
arcpy.CheckOutExtension("Network")
# Define input and output parameters for the Huff Model Calibration by Real Data tool
Potential = "C:/ArcGIS/Business Analyst/US_2013/Data/BDS/esri_bg.bds"
SalesId = "ID"
Cust = "C:/temp/sf_cust.shp"
AssocStoreId = "STORE_ID"
Store = "C:/temp/sf_stores.shp"
StoreId = "STORE_ID"
AttractionField = "SALES"
OutPath = "C:/temp/Calibration_Realdata"
# Create Huff Model Calibration by Real Data
arcpy.HuffModelCalibrationByRealData_ba(Potential, SalesId, Cust, AssocStoreId, Store, StoreId, AttractionField, "DRIVE_TIME", OutPath, "false", "false")
# Release extension license
arcpy.CheckInExtension("Business")
arcpy.CheckInExtension("Network")
except:
print arcpy.GetMessages(2)