If you’ve ever considered purchasing a real estate site selection model, you know that the industry is filled with unfamiliar terms. Researching the various solutions can feel daunting, but fortunately it doesn’t have to be that way.
In this blog, we’ll explain the most common real estate site selection model types so you can navigate the vendor landscape like a pro. No statistics degree required.
Related: How to Choose the Right Site Selection Services
Benchmark Site Score Model
What is it? Benchmark models are based on a core real estate principle: success is driven by having the right types of customers within the right distance of your location.
An analyst defines who your best customers are by leveraging your customer and location performance data combined with Buxton’s household analytics and then calculates how far those customers travel to visit your existing locations. After defining your best customers and calculating your drive time trade area, Buxton then introduces other factors that influence location performance, such as competition and cotenants. By testing a combination of variables, we identify the ones that explain performance.
What is the output of the model? A benchmark site score model produces an index score that compares the expected performance of a site to your existing sites, based on the variables included in the model. The site score sheet usually lists the individual variables that make up the overall score, so you can dive deeper into understanding the site’s dynamics.
Is it for me? If you have 21-50 locations that have been open for at least a year, then a benchmark site score model is likely a great fit for you.
Theoretical Benchmark Site Score Model
What is it? For the brands with a limited network size, Buxton also provides theoretical benchmark models, also sometimes called industry site score models, that are based on Buxton’s industry experience to ensure a solution that is able to be applied across the country. While a benchmark model and a theoretical model work in much the same way, it’s important to note that the variables included in a theoretical model have not necessarily been tested for correlation with performance.
What is the output of the model? Like a benchmark model, a theoretical benchmark model also produces an index score that compares the expected performance of a site to your existing sites, based on the variables included in the model. The site score sheet also lists the individual variables that make up the overall score.
The primary difference between a benchmark and a theoretical model is that, if you don’t have enough locations to benchmark, then other comparable sites will be included in the theoretical model for comparison.
Is it for me? Customer value site score models are ideal for companies with 0-20 locations that have been open for at least a year. The models can even be developed for companies that don’t collect customer data, since a customer profile can be developed based on similar concepts.
Forecasting Site Score Model
What is it? A forecasting site score model, also called a predictive model, is the most complex of the three site selection model types. It builds on the benchmark model by looking at how your locations affect each other, which is referred to as “cannibalization.” Additionally, the forecasting model is built in a way that enables you to forecast a specific performance indicator, such as sales, number of units sold, or number of visits.
What is the output of the model? Unlike a customer value or benchmark model, a forecasting site score model produces an actual performance forecast, such as $1.2 million in annual sales. Index scores for the underlying variables are usually provided.
Is it for me? Producing a statistically reliable forecast requires a large sample set of good quality data. Companies with 51+ locations open for at least a year typically have the data required to develop a forecasting site score model.
Best practices in Implementing Site Selection Model
Effective site selection models are essential for a successful site selection strategy. Here are five best practices to ensure a smooth implementation:
- Determine Your Objectives: Defining your objectives early helps you select the right model and identify any necessary customization to align with your goals.
- Secure Stakeholder Buy-In: Aligning stakeholders around the objectives promotes a unified approach and ensures the project progresses efficiently.
- Prioritize Technology and Support: A robust analytics platform is as important as the model itself. Choose a provider that offers ongoing analysis and strong client support.
- Prepare Your Data: Data-driven decision-making depends on clean, organized data. Streamline your customer and location data to avoid delays.
- Assign Dedicated Personnel: Ensure your organization has the right team in place to manage the model’s features and facilitate adoption.
Following these practices enables a strategic, data-driven site selection process.
Examples of Site Selection Model Implementation
Since 1994, Buxton has built thousands of models for brands across various industries, including retail, restaurant, healthcare, hospitality, and more. One particular brand that partnered with Buxton saw tremendous growth thanks to Buxton site selection models. This brand, a global fitness franchise, went from 14 locations to over 1,500 studios in 25 countries. Initially, the brand used Buxton's benchmark site selection model to identify potential markets and optimal studio locations. As the company experienced explosive growth, they upgraded to a forecasting model to better support their expanding franchise operations. Buxton’s analytics, integrated through its SCOUT platform, played a key role in guiding franchise sales, pinpointing ideal locations, and refining marketing strategies. This data-driven approach enabled the brand to enter international markets with confidence, significantly boosting franchise sales and global growth.
Buxton also helped a casual restaurant brand identify growth opportunities across the U.S. Like the global fitness franchise, Buxton initially used a benchmark model to evaluate thousands of potential sites, recommending 277 new locations. As the brand opened more and more locations, Buxton upgraded the model to a more sophisticated forecasting tool. This shift allowed the brand to prioritize expansion into new markets and select optimal sites. Locations recommended by Buxton performed 12.4% better than those not recommended, validating the effectiveness of Buxton’s site selection models. As a result, the brand expanded from 41 to 77 markets, particularly into eastern regions, significantly improving its market presence and performance.
Both the global fitness franchise and casual restaurant brand experienced remarkable growth through Buxton’s site selection models. As their businesses expanded, Buxton’s models evolved from benchmark to advanced forecasting tools, helping them make data-driven decisions that fueled their success.
Buxton's proven ability to adapt to business needs and drive growth can do the same for your brand, ensuring your expansion strategy is built on reliable, actionable insights.
Want to learn more? Check out our site selection analysis solutions.
