Demographic Location Analysis Example
In this section I’ll give an example of a simple demographic analysis where we look at the population around candidate business locations. I’ll keep it very simple so that the steps and logic behind the analysis can be understood.
Let’s say you are going to open a restaurant around the Tempe, Mesa, Gilbert area in Arizona. You have 2 candidate locations:
Location 1: Tempe
Location 2: Mesa
Demographic analysis estimates the number of people that live close by to each location and compares expected demand between the options.
For estimating the number of people living in an area different data sources can be used. The most common approach is to use the US census datasets. The US Census Bureau performs a census every year and reports analysis out of census data that estimates the number of people living at a very granular level by geography.
Here’s a visual example for one aspect of census data, population by community:
Each circle on the map above represents about 1000-10000 people and covers all the people within 5 mile radius of each location.
The area of each circle represents the size of the population in that area.
Based on this we can calculate the number of people within 1 mile 3 miles and 5 for each location:
Looking at these numbers we can see that the Tempe location has an advantage under 4 miles but the Gilbert location has more population within a larger radius.
So which location is better? Still not clear.
The best way to reason about this is thinking about your customers and how specialized your business is.
If this is a burger joint that has many competitors all around the city, the Tempe location wins. People don’t travel long distances when there’s multiple competitors close to them. If this is a specialized restaurant, for example an authentic Italian family restaurant then the Gilbert location wins. There’s more people within 7 miles where we can expect people would travel for a specialized hard to find experience.
This was the simplest demographic analysis we can make. Just take the population within a range and draw some common sense conclusions with it.
We can make the analysis deeper with looking at
- Income levels
- Age distribution
- Family types
- Competitors
We’ll be looking into each of those in other blog posts.
If you are in the process of picking a location for your business please contact me. I am looking for people to work with to build a product around these ideas and need feedback from people who need to make a similar decision for a real case. I can do this type of analysis for free for your case and in return you can give me your feedback about the clarity of the reports and usability of the maps.
Analyze Income
When we look at income data we get a similar plot as follows. In this plot, the size of each circle represents typical income levels in that area. The larger the circle the higher the typical income in that area.
Even from an initial look, location 2 seems better in terms of income levels. There are many small circles particularly to the west of location 1 and there are many medium to large size circles around location 2.
When we tabulate the data we can see this more clearly.
Particularly of 1 to 5 miles, location 2 is close to higher income areas. This is very favorable for most businesses.
One critical assumption we are making here is being close to people with higher income is better. This would be the case for most businesses that are not specifically targeted for lower income groups. For example if the business is an ultra cheap taco stand or a payday loan franchise then the reverse might be true.
Let’s continue our demographic analysis (by now I think you understand what this means a little bit better) by looking at the typical age of the people around candidate locations. The plot below shows the typical age of people around candidate locations.
From visual inspection not much difference can be seen between 2 locations. Looks like there’s senior communities to the northeast of location 2 which might be or might not be relevant depending on our business.
When we tabulate the results nothing too significant sticks out. Typical person around location 2 is slightly older. But that’s not very significant. In our demographic analysis we can conclude that in terms of age both locations are fairly equal.
One other benefit of doing an analysis like this is helping us see opportunities. For example if our business is a business that would be popular among senior people then analysis suggests that looking for a location north east of location 1 might be a good idea.