Exploring SimplyMap Data: Sales At Gift and Souvenir Shops

Most people in the United States could probably guess which cities are popular amongst tourists – Los Angeles and New York. But can you guess how much money is spent in novelty and souvenir shops at these popular destinations? In this quick SimplyMap report, we will use data from the Retail Market Power data package to find the answers to that. The figures might surprise you! Let’s get started.

First, create a new Ranking Report.


Next, navigate through this path: Retail Market Power » Stores » Miscellaneous Store Retailers » Office Supplies, Stationery, & Gift Stores.

Use the variable titled, RMP: Retail Sales from Gift, Novelty, and Souvenir Stores [NAICS 45322] ($), 2014. Image below for reference.

Exploring SimplyMap Data: Life Stage Clusters

Is there a specific age group and income bracket you are specifically interested in researching for a target location? Our Life Stages module has the information you need. Life Stages, by EASI is a premium data set available for trial or purchase to all SimplyMap subscribers. In this brief write up, we’ll take a look at some of the options available within this data package.

The Life Stages module is broken down into three folders:

Young Households – Very Young <25 and Young 25-34
Middle Age Households – Middle Age 35-44 and Late Middle Age 45-54
Older Households – Nearly Senior 55-64, Senior 65-74 and Oldest 75+

Each of these folders is further broken down by family types and income.The income data has three tiers: lower income, moderate income and higher income. Let’s get started with a demonstration.

Exploring SimplyMap Data: Walking to Work in the US

In this quick SimplyMap report, we use Census data to help us identify which city in the United States has the highest percentage of residents who reported walking to work as their mode of transportation. Have any cities in mind? Let’s find out!

First, click New Ranking from the top of your SimplyMap screen.


For the variable, follow this path: Census Data » People and Households » Employment » Travel to Work » Mode.