What is Huff Modeling?
Huff Modeling is a technique primarily used in trade area analysis to calculate the likelihood of attracting customers to specific locations. This method considers various factors such as the geographical location of the store, the inherent attractiveness of the store or service, and the distance that potential customers would need to travel. By assessing these elements, Huff Modeling provides insights into the possible reach and effectiveness of different trade areas.
Huff Model Use Cases:
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Trade Area Division: Segment your market into distinct trade areas, which are geographic regions where customers are likely to shop, based on factors such as location characteristics and customer demographics.
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Customer Locations: Identify where your existing customers or potential leads are situated within each trade area.
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Store/Service Attractiveness Assessment: Evaluate how appealing your store or service is to customers in each trade area. Consider aspects like store size, product range, service quality, and overall brand perception.
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Probability Calculation: Utilize Huff Modeling to determine the likelihood of customers choosing your store over competitors within a trade area. This calculation takes into account the attractiveness of your store and the distance customers must travel.
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Trade Area Optimization: Analyze the data to balance the potential of each trade area. This step involves adjusting the scope and focus of trade areas to maximize customer attraction and retention.
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Resource Allocation: Strategically allocate marketing and operational resources to trade areas with a higher probability of attracting customers. This ensures a more efficient use of resources and better return on investment.
Creating a Huff Model Analysis
Create Huff Analysis
- At the top of the Layers Panel, click on the
The Operations, Analysis, & Plugins window will open.
- Under the "Analysis" heading > "Models" subheading, click on the link: "Visit Probability (huff)".
- Under the "Prospect Site" heading, click the button: "Select".
- Click to select the marker from the list.
- Under the "Competitors" heading, click the button: "Select".
- Click to select the folder from the list.
- Under the "Customers" heading, click the button: "Select".
- Click to select the folder from the list.
- Under the "Attractiveness" heading, select the demographic data from the drop-down menu.
- Under the "Alpha" heading, enter the attractiveness parameter.
Alpha quantifies the attractiveness of a location or customer. It reflects how appealing or desirable a place is for potential visitors or shoppers. A higher Alpha value indicates a more attractive location, suggesting that people are more likely to visit or purchase there.
- Under the "Beta" heading, enter the distance decay parameter.
Beta accounts for the distance factor in the model. It represents how quickly the likelihood of visiting or purchasing decreases as the distance from the location or customer increases. A higher Beta value indicates that the influence of distance on the likelihood of visits or purchases decreases more slowly, making locations closer to customers more appealing.
- Click the "RUN ANALYSIS" button.
- A pop-up will appear with the "At Site Probability" and "Avg Customer Probability". Click the "Ok".
- In the top-right corner of the Operations and Analysis window, click on the "X" button.
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