Product Review: BusinessMAP Financial
by Hal Reid
October 04, 2006

ESRI, Inc.
380 New York Street
Redlands, CA 92373
800-970-0033

BusinessMAP Financial is a bold new step, creating a product for a specific vertical by combining both an affordable mapping solution and a surprisingly vast dataset. Traditionally, Business Geographic products have always had two hurdles - especially for new users, of 1) being perceived as difficult to use; and 2) expensive. BusinessMAP Financial addresses both those challenges in an easy to use, affordable product targeted at the financial services industry.

The key factor in any desktop mapping product is the data that comes with it. This is the dataset that come with this product (from the ESRI Web site).

• ESRI's demographic data with estimates and projection
• Community Tapestry Segmentation System
• Credit Union Data from National Credit Union Administration
• BranchInfo Data from RPM Consulting
• MarketBank Data from RPM Consulting
• D&B Business Listings (over 18 million business listings)
• Community Development Financial Institution Data
• Aggregate total employee data from infoUSA
• Street-level map data for North America from Tele Atlas

1. Select an area in Jackson and identify a bank to study
2. Create three drivetime polygons around that bank
3. Look at the demographics within the drivetimes
4. Look at the net worth profile within the drivetimes
5. Look at the competition within the drivetimes
6. Look at the deposits potential within the drivetimes
7. Look at the retail loan potential within the drivetimes
8. Determine the nature of the lifestyle segments within those drive times

Step 1
This is an image of the map of the Jackson area, and the polygon I used to select banks.

(Click for larger image)

A list of banks within the selected polygon show up below the map (in the yellow area). I randomly picked The Bank of the South for this hypothetical analysis.

Step 2
By right clicking on the record for the Bank of the South, I selected drivetimes from the pop-up menu. I could have select radii (or ring study), just zoomed to this bank or done a number of other things by just a right click on the record in the data view, as shown below, which is handy.

(Click for larger image)

When I selected 'Drive Time Analysis' a new dialog appears. I then get a choice of drivetime lengths, and options about how to display them, including color and transparency. I also get to choose the symbol for the bank location.


From this dialogue, I selected to 5, 10 and 15-minute drivetimes.

The Drivetime map. (Click for larger image)

Now that I have created drivetime polygons, I can generate reports about those geographies. The templates for these reports generate MS PowerPoint images or Excel files automatically. All reports contain the and tables, charts and other information specific to the type of report template selected.

In my sample workflow, each report is run by clicking on Reports at the top of the screen, selecting drivettime, and then the report template type.

Step 3
The first report I created was a demographic profile (below). This report is produced in MS PowerPoint and includes a set of slides for each drivetime polygon. You have a chance to modify some of the elements of the reports - depending on which template is used, including the title. I just used the defaults here.

These are the slides for the 5-minute drive-time polygon. (Click for larger image)

Step 4
Then I created a net worth profile. This is probably a better assessment of economic strength of households than income. The table below is from the report for the 5-minute drivetime polygon; 10 and 15 minutes tables are in the complete report.

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This is this same data as a chart.

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Step 5
The next report is the competitive profile. The table below is the summary at the top of the report showing the assets, deposits and the total banks within each of the drivetime polygons. The complete report includes the data for the individual drivetime polygons, including a list of all the banks in that geography, the bank names, the branch names, branch numbers, deposits and assets.

This table summarizes the number of bank competitors and total assets and deposits. (Click for larger image)

Step 6
The next report is deposit potential. This table and graph come from that report.

(Click for larger image)

(Click for larger image)

Step 7
Retail loan potential is the fourth report I created. The summary table and a chart showing the retail loan potential come from that report.

(Click for larger image)

(Click for larger image)

Step 8
The chart below is based on the LifeModes Tapestry data. As in the other reports, this report uses the drivetime polygons, and a list of the categories and the number of households for each drivetime and category.

This is a table of the predominate LifeMode categories, sorted by the five minute drivetime column. (Click for larger image)

This is the chart produced by the report showing the percentages of all lifestyle categories for each drivetime. At the right are the lifestyle category codes. The report shows their name and code.

Color Coding Map
The screen below includes a wealth of information. Bank locations are represented by circles and the amount of each deposit is shown by the size and color of the circle. This information is then overlaid on census tracts thematically color-coded to show deposit potential. Bottom line - bankers can see their location, their competitor's location, the growth potential they have at that location, and potential of other under-served locations.

(Click for larger image)

I've only shown some of the features of BusinessMAP Financial in this workflow. All these reports required minimal effort and ran almost automatically. With the demographics, deposit, loan potential and the lifestyle information from Tapestry, this eight-step workflow provides a comprehensive profile of this particular bank and the environment it is operating within. The entire process took just a few minutes.

You can do even more with additional data - BusinessMAP Financial comes with a catalog of additional data products. If we had customer data for this bank, we could map customer locations, too, to see concentrations within the drivetime polygons. We could also use customer location information for direct marketing or even rank them geographically by deposits or loans. By understanding some of the basics, such as who lives around the branch and what are their characteristics, we can understand how best to maximize the product mix for the branch and understand how it can be best positioned among its competition.

Ed. note: Hal Reid has performed several consulting engagements relating to ESRI's BusinessMap. These have primarily been in the area of contributions to the content of the user's manual and exploration of augmented or new features, and do not affect his ability to provide an impartial review of this product.