We have been conditioned to think big is always better. Never has this line of thinking been more prevalent than in the use of customer information. Huge data warehouses hold terabytes of company information to be queried by decision makers.

However more data does not mean better intelligence. False conclusions can easily be reached when the users of information do not know their customers.

In one case a huge car manufacturer found through its data warehouse that a certain color sedan was outselling all other colors in multiple locations. This information was quickly acted upon and resulting in an increase in the production of the popular colored sedan.

At first glance this was touted as a huge success. But on further investigation it was learned that because of extremely poor sales certain colored sedans were being highly discounted to move them off the lot!

In another example a large oil company assumed the customers for its high octane premium gas were high-end automobile owners such as Jaguars, BMW, and Lexus. However a follow-up customer survey found it were the older Classic car owners that comprised the customer segment.

Marketing to customers based on sales history alone is not enough for today's customer challenge. One customer who will communicate personal needs to a company may be worth five names in a database.

When companies view data superficially (without digging deeper into the underlying circumstances) they leave themselves open to false assumptions.

In times like these it would be foolish to believe that even a large transactional database can provide the correct guidance for reaching puzzled customers.

Data should never be viewed as the ultimate answer but rather a starting point for more meaningful questions. The real challenge is to get past the text book answer that the customer information is telling you and get to “why has this happened”.

• What did we do right (or wrong) to cause a change?

• What has changed in the equation?

• How did everyone feel one month or two months or six months after the fact? Was it still right?

Customer data should always be reviewed but the value is the investigation as to its underlying cause. While changes in customer behavior can often be attributed to uncontrollable factors (such as customers moving or businesses closing or a one time event), they can also reveal a change that may escalate.

Because it is much easier to access, small business customer information is just as useful as giant data warehouses (often much more).

An added benefit to the small business is the fact that a large corporation must be very sure of their business intelligence before they roll out a high risk project. A small company can try several different initiatives with much less risk. Therefore they have a much greater chance of hitting a homerun.