|  | Excerpt from: Globally AWhere
| | | December 03, 2008 | | Credit worthiness is a newly volatile and more important factor in business intelligence. But the impacts are not universal, and geography affects your analysis. | Meaningful customer data has probably never been more plentiful than it is today. Sharp-eyed analysts are noting preferences and details in customer behavior that no one dreamed of tracking even a few years ago. And the proliferation of data has exploded recently, as the recession (yes, the Fed now says it’s a bona-fide recession) has driven greater scrutiny of credit-worthiness and solvency.
The data is out there (links below). That doesn’t mean it’s easy to find, easy to access, or free. It also usually doesn't have the frame of reference to draw meaningful conclusions for your business, nor is it interactive in a way that lets you bring your questions to bear.
Several of our clients are now experiencing unusual sales behavior in different areas, and are seeking causative factors. Let's look at some questions they are addressing today:
- Is sales volatility related to an increase in foreclosures?
- Are former homeowners turning to discount chains instead of more expensive options because their financial circumstances have declined?
- Where is unemployment spiking?
- How are credit delinquencies shifting buying patterns?
What if you suspect some other factors are at work? Even if you have the data, putting different spreadsheets next to each other on the desk is not the way to extract actionable insight.
Geo-analytics can make sense of questions like these. Knowing how to get the data isn’t the solution; it’s a first step toward answering your question. The ability to mashup and compare external economic data with internal sales data within the geographic context of your business can provide a new level of insight.
Let's look at a simple map. Here we see the most basic of correlations: the red and green shapes are counties; red ones have increased mortgage and credit card delinquencies and green ones have decreasing delinquencies.  The various color dots and triangles are different types of WalMart stores. If you are selling consumer packaged goods at WalMart, this could help you not only better reveal correlations and predict sales, but also shift inventory to optimize the best producing stores in the strongest economic regions.
In this static picture, there is only a finite amount of information, but still enough to make some quick observations. For our clients, we are providing a more dynamic service that provides three additional benefits:
- Custom sales data represented on a map, including growth trends.
- The ability to see tighter correlations by turning layers on and off.
- A view of trends over time.
These benefits result in the ability to answer questions like "which stores which stores meet the criteria credit score below X and quarterly change Y?”, then visualize the geographic clusters where special promos will get the attention of the "right customers."
In these times, this kind of competitive advantage can provide the ability to survive while your competitors permanently slip below the line.
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