How Model Builder Takes the Guesswork Out of Location Decisions

Growing a multi-site business is no easy endeavor in today’s ultra-competitive, uncertain climate.

Any retailer knows that making intelligent location decisions requires more than great instincts and luck. Powerful analytics paired with accurate, current data that you can trust are the name of the game. Choosing great locations and markets involves creating a well-planned expansion strategy, understanding your customers’ needs and behaviors, weighing and evaluating your competitors, and more.

Why You Need to Create a Site Screening Model to Find Sites

The obvious answer to how to identify sites that meet your chain’s requirements is to create a model. The problems:

1. Creating models has traditionally been a job for highly trained analysts with a deep understanding of data analytics and machine learning.
2. Small or growing retailers rarely have such a person on their team who has the skills to build models.
3. Many research platforms on the market lack any sort of tool that the average user has the skills to use…or the time to learn.

This reality is exactly what led our development team at SiteSeer to create Model Builder and enhance it over the past several years. We’ve continued to make Model Builder better and better, and our retailer and broker/developer clients have told us that there is no other tool on the market quite like it.

What makes Model Builder so great?

First, it is truly build-it-yourself. We developed Model Builder with growing retailers with small teams in mind, knowing that a research department with seasoned analysts is not a luxury that most chain business have until they are larger!

Second, Model Builder is very powerful—even for the superuser. It’s powered by SiteSeer’s proprietary location decision engine and uses leading data sources.

Model Builder takes the guesswork out of choosing new sites. Let’s talk about how.

First Things First: Choosing KPIs

The first thing a user does in Model Builder is choose the key performance indicators that matter most to their chain or business.

There are many KPIs to choose from in the SiteSeer system--factors like customer demographics, minimum population in the trade area, customers’ lifestyle characteristics, site characteristics (like sites that are co-located with grocery stores, or sites within two miles of a highway), nearest competitors, and more.

This input is the underpinning of a model—and the more precise you are, the more accurate the output of a model. You can be broad when choosing the factors that are essential to your chain business’s success, but the results might not provide you with results that are very accurate or helpful.

But what if you’re a small retail chain with just a few locations or a growing restaurant chain that’s only existed for a few years? Not every chain business has a deep understanding of the key performance indicators that drive their business like you’d expect from the retail research teams at Starbucks or McDonald’s. If you have just a few restaurants or stores, you might not have sufficient data to analyze to get this kind of insight.

Solution: Location Profiles

We recognized this challenge early on and came up with a solution: Location Profiles.

Location Profiles are essentially ready-built templates of the success factors of hundreds of chains across the United States. Our development team analyzed the historical development pattern of each chain to determine their KPIs and created Location Profiles that SiteSeer users can clone and adapt as they see fit.

These are the perfect solution for SiteSeer users that like what Model Builder can do but need a starting point to create models for their chain.

Let’s say you’re the owner of a pizza restaurant with four locations in the Boise market. You have some sense of your chain’s success factors, but you browse our Location Profiles and come across Mod Pizza—a business that you’ve often considered “what you want to be when you grow up.”

You can clone the Mod Pizza Location Profile and adjust any variables to align them better with your business and goals. That might include changing the income variables and site criteria slightly or tweaking the customer demographics. We know you’re thinking it already: this saves you a lot of time! And best of all, you’ll have a detailed model that you can continue to fine tune as you incorporate different data sources (from your own business and from our third-party data sources).

Hot Spots and Site Scorecards

So, you clone a Location Profile, adjust the variables that matter to your business, run your model—and voila!—you see the results in front of you. There are two primary outputs of Model Builder: the Site Scorecard report and the Hot Spot.

After you build a model with all the variables that are important to your business and run it, SiteSeer works its magic. By that, we mean SiteSeer runs your site selection profile against potential locations across the region or market you tell it to analyze. The visual output of that analysis is a map with a Hot Spot theme.

• A Hot Spot color codes the map so that the most viable (i.e., “hot”) locations stand out and the least viable (i.e., the least similar to your site selection profile) are left unshaded. You can zoom into the “hottest” spot on the map, right click to obtain a street address, and run a Site Scorecard for that specific location.
• A Site Scorecard is basically a report card for a location using grading of A through F. A site (address) that fits your success criteria very closely would receive an A, while a location that doesn’t closely match most of the KPIs you put into SiteSeer when building your model might receive a D or F.

Lastly, Model Builder’s Prospects functionality lets you adjust site criteria and even add new variables while looking at the map with Hot Spots. You’ll see in real time how those changes to your KPIs might impact your list of good sites (and your Hot Spots). The Checklist functionality helps you determine whether a specific site passes or fails your absolute must-have site requirements.

Finding Available Retail/Commercial Space

So, let’s say our fictional Boise pizza chain might find that an address on 123 Johnson Avenue scored high on the Site Scorecard. They want to know if there are available properties for sale or lease there (or close by).

They could get that data from a commercial broker, of course, but they could also get it right within the SiteSeer platform when they subscribe to Resimplifi data.

Resimplifi is live commercial real estate listing data. It’s available to SiteSeer subscribers now, and our development team is currently integrating the data across the platform so that soon, users will be able to do even more analysis of sites right in SiteSeer.

Build Site Screening Models Like Today’s Leading Retail Chains

Model Builder is powerful, easy to use, and getting better all the time. It is affordable for small and mid-sized retail chains and other chain businesses that want to perform the best possible location analysis but do not have the resources to invest in platforms that require that models be custom-built by their in-house analysts.

That said, SiteSeer does have a professional services team for our clients that prefer to have us build models that they can use in SiteSeer. We perform this type of engagement for many of our retail clients—but with Model Builder, you can create and adjust models yourselves for the price of your SiteSeer subscription plan. We’ve built this tool using best practices in location analytics and even created Location Profiles to give users a head start on model building.

Step Up Your Site Selection with SiteSeer

Intrigued? Contact us for a demo of SiteSeer. We’ll show you how Model Builder and SiteSeer’s other functionality can support your data-driven decision making.